Classification and prognosis prediction of acute lymphoblastic leukemia by gene expression profiling

BACKGROUND OF THE INVENTION

[0003] Pediatric acute lymphoblastic leukemia (ALL) is one of the great success stories of modern cancer therapy, with contemporary treatment protocols achieving overall long-term event free survival rates approaching 80% (Schrappe et al. (2000) Blood 95:3310-22; Silverman et al.(2001) Blood 97:1211-18; and Pui and Evans (1998) N. Eng. J. Med. 339:605-15). This success has been achieved in part by using risk-adapted therapy that involves tailoring the intensity of treatment to each patient's risk of relapse. This approach was developed following the realization that pediatric ALL is a heterogeneous disease consisting of various leukemia subtypes that differ markedly in their response to chemotherapy (reviewed in Pui and Evans (1998) N. Eng. J. Med. 339:605-15). By tailoring the intensity of treatment to a patient's relative risk of relapse, patients are neither under-treated or over-treated, and are thus afforded the highest chance for a cure.

[0004] Critical to the success of this approach has been the accurate assignment of individual patients to specific risk groups. Although risk assignment is influenced by a variety of clinical and laboratory parameters, the genetic alterations that underlie the pathogenesis of individual leukemia subtypes figure prominently in most classification schemes (Silverman L B et al. (2001) Blood 97:1211-18; and Pui and Evans (1998) N. Engl. J. Med. 339:605-15). Through systematic immunophenotyping and cytogenetic analysis, and the subsequent molecular cloning of the genes targeted by the identified chromosomal rearrangements, a number of genetically distinct leukemia subtypes have been defined. These include B-lineage leukemias that contain t(9;22)[BCR-ABL], t(1;19)[E2A-PBX1], t(12;21)[TEL-AML1], rearrangements in the MLL gene on chromosome 11, band q23, or a hyperdiploid karyotype (i.e., >50 chromosomes), and T-lineage leukemias (T-ALL) (Silverman et al.(2001) Blood 97:1211-18; and Pui and Evans (1998) N. Eng. J. Med. 339:605-15). The underlying genetic lesions in these leukemia subtypes influence the response to cytotoxic drugs. For example, leukemias that express the E2A-PBX1 fusion protein respond poorly to conventional antimetabolite-based treatment, but have cure rates approaching 80% when treated with more intensive therapies (Raimondi et al. (1990) J. Clin. Oncol. 8:1380-88; and Hunger (1996) Blood 87:1211-1224). Similarly, BCR-ABL expressing ALLs, or infants with MLL rearrangements have exceedingly poor cure rates with conventional chemotherapy, and allogeneic hematopoietic stem cell transplantation with HLA matched sibling donor has already been shown to improve outcome for patients with the former leukemia subtype (Pui et al. (1991) Blood 77:440-46; Heerema et al. (1999) Leukemia 13:679-86; Arico et al. (2000) N. Engl. J. Med. 342:998-1006; and Biondi et al. (2000) Blood 96:24-33).

[0005] Unfortunately, the accurate assignment of patients to specific risk groups is a difficult and expensive process, requiring intensive laboratory studies including immunophenotyping, cytogenetics, and molecular diagnostics (Pui and Evans (1998) N. Eng. J. Med. 339:605-15; and Pui et al. (2001) Lancet Oncology 2:597-607). Moreover, these diagnostic approaches require the collective expertise of a number of professionals, and although this expertise is available at most major medical centers, it is generally unavailable in developing countries. Accordingly, there remains a need for rapid, less expensive methods of assigning patients affected by ALL into known leukemia risk groups and identifying patients for whom there is a high risk that conventional therapeutic approaches will fail.

BRIEF SUMMARY OF THE INVENTION

[0006] The present invention provides methods and compositions useful for diagnosing and choosing treatment for subjects affected by leukemia. The claimed methods include methods of assigning a subject affected by leukemia to a leukemia risk group, methods of predicting whether a subject affected by leukemia has an increased risk of relapse, methods of predicting whether a subject affected by leukemia has an increased risk of developing secondary acute myeloid leukemia (AML), methods to aid in the determination of a prognosis for a subject affected by leukemia, methods of choosing a therapy for a subject affected by leukemia, and methods of monitoring the disease state in a subject undergoing one or more therapies for leukemia. Methods of screening test compounds to identify therapeutic compounds useful for the treatment of leukemia and molecular targets for these therapeutic compounds are also provided.

[0007] The claimed methods comprise providing an expression profile of a sample from a subject affected by leukemia and comparing this subject expression profile to one or more reference expression profiles. In one embodiment, the reference profiles are associated with leukemia risk groups, and the subject expression profile is compared to one or more of these risk group reference profiles to thereby assign the subject affected by leukemia to a leukemia risk group. In another embodiment, one or more reference profiles are associated with relapse of leukemia and the subject expression profile is compared to one or more of these relapse reference profiles to determine if the subject has an increased risk of relapse. In yet another embodiment, one or more reference profiles are associated with secondary AML, and the subject expression profile is compared to one or more of these reference profiles to determine whether the subject has an increased risk of developing secondary AML.

[0008] The present invention also provides compositions useful for diagnosing and choosing a therapy for subjects affected by leukemia. These compositions include arrays comprising a plurality of capture probes that can bind specifically to nucleic acid molecules that are differentially expressed in leukemia risk groups, in leukemia subjects who have relapsed, or in leukemia subjects who have developed secondary AML. Also provided is a computer-readable medium comprising digitally-encoded expression profiles comprising values representing the expression levels of genes that are differentially expressed in leukemia risk groups, in leukemia subjects who have relapsed, or in leukemia subjects who have developed secondary AML. Additional compositions of the invention include kits comprising an array of capture probes that can bind specifically to nucleic acid molecules that are differentially expressed in leukemia risk groups, in leukemia subjects who have relapsed, or in leukemia subjects who have developed secondary AML, and a computer-readable medium having digitally encoded expression profiles with values representing the expression level of a nucleic acid molecule detected by the array.

DETAILED DESCRIPTION OF THE INVENTION

[0009] The present invention provides a single platform, expression analysis, that can accurately identify each of the known prognostically and therapeutically relevant subgroups of leukemia and predict the risk of relapse and the risk of secondary (therapy-induced) AML in patients having leukemia. The methods and compositions of the invention provide tools useful in choosing a therapy for leukemia patients, including methods for assigning a leukemia patient to a leukemia risk group, methods of predicting whether a leukemia patient has an increased risk of relapse, methods of predicting whether a leukemia patient has an increased risk of developing secondary (therapy-induced) AML, methods of choosing a therapy for a leukemia patient, methods of determining the efficacy of a therapy in a leukemia patient, and methods of determining the prognosis for a leukemia patient.

[0010] The methods of the invention comprise the steps of providing an expression profile from a sample from a subject affected by leukemia and comparing this subject expression profile to one or more reference profiles that are associated with a particular physiologic condition, such as a leukemia risk group, the occurrence of relapse, or the development of secondary AML. By identifying the leukemia risk group reference profile that is most similar to the subject expression profile, the subject can be assigned to a leukemia risk group. Similarly, the risk that a subject affected by leukemia will relapse or develop secondary AML can be predicted by determining whether the expression profile from the subject is sufficiently similar to a reference profile associated with relapse or a reference profile associated with the development of secondary AML. In another embodiment, the subject expression profile is from a subject affected by leukemia who is undergoing a therapy to treat the leukemia. The subject expression profile is compared to one or more reference expression profiles of the invention to monitor the efficacy of the therapy.

[0011] Expression Profiles

[0012] As used herein, an “expression profile” comprises one or more values corresponding to a measurement of the relative abundance of a gene expression product. Such values may include measurements of RNA levels or protein abundance. Thus, the expression profile can comprise values representing the measurement of the transcriptional state or the translational state of the gene. See, U.S. Pat. Nos. 6,040,138, 5,800,992, 6,020135, 6,344,316, and 6,033,860, which are hereby incorporated by reference in their entireties.

[0013] The transcriptional state of a sample includes the identities and relative abundance of the RNA species, especially mRNAs present in the sample. Preferably, a substantial fraction of all constituent RNA species in the sample are measured, but at least a sufficient fraction to characterize the transcriptional state of the sample is measured. The transcriptional state can be conveniently determined by measuring transcript abundance by any of several existing gene expression technologies.

[0014] Translational state includes the identities and relative abundance of the constituent protein species in the sample. As is known to those of skill in the art, the transcriptional state and translational state are related.

[0015] In some embodiments, the expression profiles of the present invention are generated from samples from subjects affected by leukemia, including subjects having leukemia, subjects suspected of having leukemia, subjects having a propensity to develop leukemia, or subjects who have previously had leukemia, or subjects undergoing therapy for leukemia. The samples from the subject used to generate the expression profiles of the present invention can be derived from a variety of sources including, but not limited to, single cells, a collection of cells, tissue, cell culture, bone marrow, blood, or other bodily fluids. The tissue or cell source may include a tissue biopsy sample, a cell sorted population, cell culture, or a single cell. Sources for the sample of the present invention include cells from peripheral blood or bone marrow, such as blast cells from peripheral blood or bone marrow.

[0016] In selecting a sample, the percentage of the sample that constitutes cells having differential gene expression in leukemia risk groups, relapse, or secondary AML should be considered. Samples may comprise at least 20%, at least 30%, at least 40%, at least 50%, at least 55%, at least 60%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, or at least 95% cells having differential expression in leukemia risk groups, relapse, or secondary AML, with a preference for samples having a higher percentage of such cells. In some embodiments, these cells are blast cells, such as leukemic cells. The percentage of a sample that constitutes blast cells may be determined by methods well known in the art; see, for example, the methods described elsewhere herein.

[0017] In some embodiments of the present invention, the expression profiles comprise values representing the expression levels of genes that are differentially expressed in leukemia risk groups, in subjects affected by leukemia who have relapsed, or in subjects affected by leukemia who have developed secondary AML. The term “differentially expressed” as used herein means that the measurement of a cellular constituent varies in two or more samples. The cellular constituent may be upregulated in a sample from a subject having one physiologic condition in comparison with a sample from a subject having a different physiologic condition, or down regulated in a sample from a subject having one physiologic condition in comparison with a sample from a subject having a different physiologic condition. For example, in one embodiment, the differentially expressed genes of the present invention may be expressed at different levels in different leukemia risk groups. In another embodiment, the differentially expressed genes are expressed in different levels in subjects affected by leukemia who will relapse after conventional treatment in comparison with subjects affected by leukemia who will not relapse and thus will remain in continuous complete remission. In yet another embodiment, the differentially expressed genes are expressed in different levels in subjects affected by leukemia who will develop secondary AML in comparison with subjects affected by leukemia who will not develop secondary AML.

[0018] The present invention provides groups of genes that are differentially expressed in diagnostic leukemia samples of patients in different risk groups, or in patients that go on to develop a relapse or a therapy induced (secondary) AML. Some of these genes were identified based on gene expression levels for 12,600 probes in 360 leukemia samples. Values representing the expression levels of the nucleic acid molecules detected by the probes were analyzed using five different statistical metrics to identify genes that were differentially expressed in leukemia risk groups. The methods used to analyze the expression level values to identify differentially expressed genes were the Chi-square statistics method, the Correlation-based Feature Selection method, the T-statistics method, the Wilkins' method, and the self-organizing map and discriminant analysis with variance metric. Although different methods of analysis resulted in the selection of different groups of differentially expressed genes, the genes selected by each method could be used to create an expression profile that could accurately determine whether a leukemia patient should be assigned to a risk group, with an overall diagnostic accuracy of about 96%. See, the Experimental section.

[0019] Additional genes that are differentially expressed in diagnostic leukemia samples were identified based on gene expression levels for 26,825 probes in a subset of 132 leukemia samples selected from the 360 leukemia samples described above. A chi-squared metric followed by permutation test was used to identify discriminating genes for the T-ALL, E2A-PBX1, TEL-AML1, BCR-ABL, MLL rearrangement, and Hyperdiploid >50 chromosomes. Genes whose expression is limited to a single B-cell lineage were also identified, and are provided in Tables 70-74.

[0020] Thus, distinct sets of differentially expressed genes that can be used to distinguish the T-lineage, hyperdiploid >50 chromosomes, BCR-ABL, E2A-PBX1, TEL-AML1, and MLL gene rearrangement risk groups are provided. Examples of genes that are differentially expressed in the T-ALL risk group are shown in Tables 7, 14, 21, 28, 35, 59, and 67. Examples of genes that are differentially expressed in the E2A-PBX1 risk group are shown in Tables 3, 10, 17, 24, 31, 55, 64, and 71. Examples of genes that are differentially expressed in the TEL-AML1 risk group are shown in Tables 8, 15, 22, 29, 36, 60, 68, and 74. Examples of genes that are differentially expressed in the BCR-ABL risk group are shown in Tables 2, 9, 16, 23, 30, 54, 63, and 70. Examples of genes that are differentially expressed in the MLL risk group are shown in Tables 5, 12, 19, 26, 33, 57, 66, and 73. Examples of genes that are differentially expressed in the Hyperdiploid>50 risk group are shown in Tables 4, 11, 18, 25, 32, 56, 65, and 72.

[0021] The present invention further provides a seventh leukemia risk group, herein termed “Novel,” that can be distinguished from the previously-described leukemia risk groups based on expression profiling. The expression profiles from subjects in the Novel risk group are distinguishable from those of the T-ALL, E2A-PBX1, TEL-AML1, BCR-ABL, MLL, and Hyperdiploid >50 risk groups. Subjects assigned to the Novel risk group have similar expression profiles. Examples of genes that are differentially expressed in the Novel leukemia risk group are shown in Tables 4, 11, 18, 25, 32, and 58.

[0022] Similarly, sets of differentially expressed genes associated with leukemia patients in the T-ALL, Hyperdiploid >50, TEL-AML1, MLL, and Other (i.e. not the T-ALL, hyperdiploid >50, TEL-AML1, MLL, E2A-PBX1, or BCR-ABL) risk groups who have undergone relapse were identified. Examples of differentially expressed genes associated with relapse in subjects in the T-ALL risk group are shown in Table 44. Examples of differentially expressed genes associated with relapse in subjects in the hyperdiploid >50 risk group are shown in Table 45. Examples of differentially expressed genes associated with relapse in subjects in the TEL-AML1 risk group are shown in Table 46. Examples of differentially expressed genes associated with relapse in subjects in the MLL risk group are shown in Table 47. Examples of differentially expressed genes associated with relapse in subjects in the E2A-PBX1, BCR-ABL, and Novel risk group are shown in Table 48.

[0023] The invention also provides genes that are differentially expressed in subjects affected by TEL-AML1 who have developed secondary (treatment-induced) AML. Examples of such genes are shown in Table 52.

[0024] The present invention also reveals genes with a high differential level of expression in leukemic compared to normal cells. These highly differentially expressed genes are selected from the genes shown in Tables 2-36 and 44-48, 63-68, and 70-74. These genes and their expression products are useful as markers to detect the presence of minimal residual disease (MRD) in a patient. Antibodies or other reagents or tools may be used to detect the presence of these telltale markers of MRD.

[0025] The expression profiles of the invention comprise one or more values representing the expression level of a gene having differential expression in a leukemia risk group, in subjects affected by leukemia who will relapse after conventional therapy, or in subjects affected by leukemia who will develop secondary AML after conventional therapy. Each expression profile contains a sufficient number of values such that the profile can be used to distinguish one leukemia risk group from another, or to distinguish subjects who will relapse after conventional therapy from those who will not relapse, or to distinguish subjects who will develop secondary AML after conventional therapy from those who will not develop secondary AML. In some embodiments, the expression profiles comprise only one value. For example, it can be determined whether a subject affected by leukemia is in the T-ALL risk group based only on the expression level of the CD3D antigen (NCBI Accession No. AA919102; see Table 14). Similarly, it can be determined whether a subject affected by leukemia is in the E2A-PBX1 risk group based only on the expression level of the cDNA of NCBI Accession No. AL049381 (see Table 10). In other embodiments, the expression profile comprises more than one value corresponding to a differentially expressed gene, for example at least 2 values, at least 3 values, at least 4 values, at least 5 values, at least 6 values, at least 7 values, at least 8 values, at least 9 values, at least 10 values, at least 11 values, at least 12 values, at least 13 values, at least 14 values, at least 15 values, at least 16 values, at least 17 values, at least 18 values, at least 19 values, at least 20 values, at least 22 values, at least 25 values, at least 27 values, at least 30 values, at least 35 values, at least 40 values, at least 45 values, at least 50 values, at least 75 values, at least 100 values, at least 125 values, at least 150 values, at least 175 values, at least 200 values, at least 250 values, at least 300 values, at least 400 values, at least 500 values, at least 600 values, at least 700 values, at least 800 values, at least 900 values, at least 1000 values, at least 1200 values, at least 1500 values, or at least 2000 or more values.

[0026] It is recognized that the diagnostic accuracy of assigning a subject to a leukemia risk group, determining whether a subject has an increased risk for relapse, or determining whether a subject has an increased risk of developing secondary AML will vary based on the number of values contained in the expression profile. Generally, the number of values contained in the expression profile is selected such that the diagnostic accuracy is at least 85%, at least 87%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%, as calculated using methods described elsewhere herein, with an obvious preference for higher percentages of diagnostic accuracy.

[0027] It is recognized that the diagnostic accuracy of assigning a subject to a leukemia risk group, determining whether a subject has an increased risk for relapse, or determining whether a subject has an increased risk of developing secondary AML will vary based on the strength of the correlation between the expression levels of the differentially expressed genes and the associated physiologic condition. When the values in the expression profiles represent the expression levels of genes whose expression is strongly correlated with the physiologic condition, it may be possible to use fewer number of values in the expression profile and still obtain an acceptable level of diagnostic or prognostic accuracy.

[0028] The strength of the correlation between the expression level of a differentially expressed gene and the presence or absence of a particular physiologic state may be determined by a statistical test of significance. For example, the chi square test used to select genes in some embodiments of the present invention assigns a chi square value to each differentially expressed gene, indicating the strength of the correlation of the expression of that gene and the presence or absence of the associated physiologic condition. Similarly, the T-statistics metric and the Wilkins' metric both provide a value or score indicative of the strength of the correlation between the expression of the gene and the absence or presence of the associated physiologic conditions. These scores may be used to select the genes whose expression levels have the greatest correlation with a particular physiologic state in order to increase the diagnostic or prognostic accuracy of the methods of the invention, or in order to reduce the number of values contained in the expression profile while maintaining the diagnostic or prognostic accuracy of the expression profile.

[0029] For example, in one embodiment the chi square test is used to determine the significance of the differentially expressed genes whose expression levels are included in the array, and only those genes having a chi square value of more than 20, more than 25, more than 30, more than 35, more than 40, more than 45, more than 50, more than 55, more than 60, more than 65, more than 70, more than 75, more than 80, more than 90, more than 100, more than 120, more than 140, more than 160, more than 180, or more than 200 are selected.

[0030] In another embodiment, the T-statistics metric is used to determine the significance of the differentially expressed genes whose expression levels are included in the array, and only those genes with a score having an absolute value of greater than 4, greater than 5, greater than 6, greater than 7, greater than 8, greater than 9, greater than 10, greater than 12, greater than 25, greater than 27, greater than 30, or greater than 35 are selected.

[0031] In yet another embodiment, the Wilkins' metric is used to determine the significance of the differentially expressed genes whose expression levels are included in the array, and only those genes having a score of greater than 0.55, greater than 0.57, greater than 0.59, greater than 0.61, greater than 0.63, greater than 0.65, greater than 0.67, greater than 0.69, greater than 0.71, greater than 0.73, greater than 0.75, greater than 0.77, greater than 0.79, greater than 0.81, greater than 0.83, or greater than 0.85 are selected.

[0032] Each value in the expression profiles of the invention is a measurement representing the absolute or the relative expression level of a differentially expressed genes. The expression levels of these genes may be determined by any method known in the art for assessing the expression level of an RNA or protein molecule in a sample. For example, expression levels of RNA may be monitored using a membrane blot (such as used in hybridization analysis such as Northern, Southern, dot, and the like), or microwells, sample tubes, gels, beads or fibers (or any solid support comprising bound nucleic acids). See U.S. Pat. Nos. 5,770,722, 5,874,219, 5,744,305, 5,677,195 and 5,445,934, which are expressly incorporated herein by reference. The gene expression monitoring system may also comprise nucleic acid probes in solution.

[0033] In one embodiment of the invention, microarrays are used to measure the values to be included in the expression profiles. Microarrays are particularly well suited for this purpose because of the reproducibility between different experiments. DNA microarrays provide one method for the simultaneous measurement of the expression levels of large numbers of genes. Each array consists of a reproducible pattern of capture probes attached to a solid support. Labeled RNA or DNA is hybridized to complementary probes on the array and then detected by laser scanning. Hybridization intensities for each probe on the array are determined and converted to a quantitative value representing relative gene expression levels. See, the Experimental section. See also, U.S. Pat. Nos. 6,040,138, 5,800,992 and 6,020,135, 6,033,860, and 6,344,316, which are incorporated herein by reference. High-density oligonucleotide arrays are particularly useful for determining the gene expression profile for a large number of RNA's in a sample.

[0034] In one approach, total mRNA isolated from the sample is converted to labeled cRNA and then hybridized to an oligonucleotide array. Each sample is hybridized to a separate array. Relative transcript levels are calculated by reference to appropriate controls present on the array and in the sample. See, for example, the Experimental section.

[0035] In another embodiment, the values in the expression profile are obtained by measuring the abundance of the protein products of the differentially-expressed genes. The abundance of these protein products can be determined, for example, using antibodies specific for the protein products of the differentially-expressed genes. The term “antibody” as used herein refers to an immunoglobulin molecule or immunologically active portion thereof, i.e., an antigen-binding portion. Examples of immunologically active portions of immunoglobulin molecules include F(ab) and F(ab′)2 fragments which can be generated by treating the antibody with an enzyme such as pepsin.

[0036] The antibody can be a polyclonal, monoclonal, recombinant, e.g., a chimeric or humanized, fully human, non-human, e.g., murine, or single chain antibody. In a preferred embodiment it has effector function and can fix complement. The antibody can be coupled to a toxin or imaging agent.

[0037] A full-length protein product from a differentially-expressed gene, or an antigenic peptide fragment of the protein product can be used as an immunogen. Preferred epitopes encompassed by the antigenic peptide are regions of the protein product of the differentially expressed gene that are located on the surface of the protein, e.g., hydrophilic regions, as well as regions with high antigenicity. The antibody can be used to detect the protein product of the differentially expressed gene in order to evaluate the abundance and pattern of expression of the protein. These antibodies can also be used diagnostically to monitor protein levels in tissue as part of a clinical testing procedure, e.g., to, for example, determine the efficacy of a given therapy. Detection can be facilitated by coupling (i.e., physically linking) the antibody to a detectable substance (i.e., antibody labeling). Examples of detectable substances include various enzymes, prosthetic groups, fluorescent materials, luminescent materials, bioluminescent materials, and radioactive materials. Examples of suitable enzymes include horseradish peroxidase, alkaline phosphatase, β-galactosidase, or acetylcholinesterase; examples of suitable prosthetic group complexes include streptavidin/biotin and avidin/biotin; examples of suitable fluorescent materials include umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansyl chloride or phycoerythrin; an example of a luminescent material includes luminol; examples of bioluminescent materials include luciferase, luciferin, and aequorin, and examples of suitable radioactive material include 125I, 131I, 35S or 3H.

[0038] Once the values comprised in the subject expression profile and the reference expression profile or expression profiles are established, the subject profile is compared to the reference profile to determine whether the subject expression profile is sufficiently similar to the reference profile. Alternatively, the subject expression profile is compared to a plurality of reference expression profiles to select the reference expression profile that is most similar to the subject expression profile.

[0039] Any method known in the art for comparing two or more data sets to detect similarity between them may be used to compare the subject expression profile to the reference expression profiles. In some embodiments, the subject expression profile and the reference profile are compared using a supervised learning algorithm such as the support vector machine (SVM) algorithm, prediction by collective likelihood of emerging patterns (PCL) algorithm, the k-nearest neighbor algorithm, or the Artificial Neural Network algorithm. Each of these algorithms is described in the Experimental section of the application. To determine whether a subject expression profile shows “statistically significant similarity” or “sufficient similarity” to a reference profile, statistical tests may be performed to determine whether the similarity between the subject expression profile and the reference expression profile is likely to have been achieved by a random event. An example of such a statistical test is the permutation test described in the Experimental section; however, any statistical test that can calculate the likelihood that the similarity between the subject expression profile and the reference profile results from a random event can be used. The accuracy of assigning a subject to a risk group based on similarity between an expression profile for the subject and an expression profile for the risk group depends in part on the degree of similarity between the two profiles. Therefore, when more accurate diagnoses are required, the stringency with which the similarity between the subject expression profile and the reference profile is evaluated should be increased. For example, in various embodiments, the p-value obtained when comparing the subject expression profile to a reference profile that shares sufficient similarity with the subject expression profile is less than 0.20, less than 0.15, less than 0.10, less than 0.09, less than 0.08, less than 0.07, less than 0.06, less than 0.05, less than 0.04, less than 0.03, less than 0.02, or less than 0.01.

[0040] In some embodiments, the assignment of a subject affected by leukemia to a leukemia risk group, the prediction of whether a subject affected by leukemia has an increased risk of relapse, or the prediction of whether a subject by affected by leukemia has an increased risk of developing secondary AML is used in a method of choosing a therapy for the subject affected by leukemia. A therapy, as used herein, refers to a course of treatment intended to reduce or eliminate the affects or symptoms of a disease, in this case leukemia. A therapy regiment will typically comprise, but is not limited to, a prescribed dosage of one or more drugs or hematopoietic stem cell transplantation. Therapies, ideally, will be beneficial and reduce the disease state but in many instances the effect of a therapy will have non-desirable effects as well. Thus, the methods of the invention are useful for monitoring the effectiveness of a therapy even when non-desirable side-effects are observed.

[0041] Arrays, Computer-Readable Medium, and Kits

[0042] The present invention provides compositions that are useful in determining the gene expression profile for a subject affected by leukemia and selecting a reference profile that is similar to the subject expression profile. These compositions include arrays comprising a substrate having a capture probes that can bind specifically to nucleic acid molecules that are differentially expressed in leukemia risk groups, subjects affected by leukemia who will relapse after conventional therapy, or subjects affected by leukemia who will develop secondary AML after conventional therapy. Also provided is a computer-readable medium having digitally encoded reference profiles useful in the methods of the claimed invention. The invention also encompasses kits comprising an array of the invention and a computer-readable medium having digitally-encoded reference profiles with values representing the expression of nucleic acid molecules detected by the arrays. These kits are useful for assigning a subject affected by leukemia to a leukemia risk group, predicting whether a subject affected by leukemia has an increased risk of relapse, and predicting whether a subject affected by leukemia has an increased risk of developing secondary AML.

[0043] The present invention provides arrays comprising capture probes for detecting the differentially expressed genes of the invention. By “array” is intended a solid support or substrate with peptide or nucleic acid probes attached to said support or substrate. Arrays typically comprise a plurality of different nucleic acid or peptide capture probes that are coupled to a surface of a substrate in different, known locations. These arrays, also described as “microarrays” or colloquially “chips” have been generally described in the art, for example, in U.S. Pat. Nos. 5,143,854, 5,445,934, 5,744,305, 5,677,195, 6,040,193, 5,424,186, 6,329,143, and 6,309,831 and Fodor et al. (1991) Science 251:767-77, each of which is incorporated by reference in its entirety. These arrays may generally be produced using mechanical synthesis methods or light directed synthesis methods which incorporate a combination of photolithographic methods and solid phase synthesis methods.

[0044] Techniques for the synthesis of these arrays using mechanical synthesis methods are described in, e.g., U.S. Pat. No. 5,384,261, incorporated herein by reference in its entirety for all purposes. Although a planar array surface is preferred, the array may be fabricated on a surface of virtually any shape or even a multiplicity of surfaces. Arrays may be peptides or nucleic acids on beads, gels, polymeric surfaces, fibers such as fiber optics, glass or any other appropriate substrate, see U.S. Pat. Nos. 5,770,358, 5,789,162, 5,708,153, 6,040,193 and 5,800,992, each of which is hereby incorporated in its entirety for all purposes. Arrays may be packaged in such a manner as to allow for diagnostics or other manipulation of an all-inclusive device. See, for example, U.S. Pat. Nos. 5,856,174 and 5,922,591 herein incorporated by reference.

[0045] The arrays provided by the present invention comprise capture probes that can specifically bind a nucleic acid molecule that is differentially expressed in leukemia risk groups, a nucleic acid molecule that is differentially expressed in subjects affected by leukemia who will relapse after conventional therapy, or a nucleic acid molecule that is differentially expressed in subjects affected by leukemia who will develop secondary AML after conventional therapy. These arrays can be used to measure the expression levels of nucleic acid molecules to thereby create an expression profile for use in methods of determining the diagnosis and prognosis for leukemia patients, and for monitoring the efficacy of a therapy in these patients as described elsewhere herein.

[0046] In some embodiments, each capture probe in the array detects a nucleic acid molecule selected from the nucleic acid molecules designated in Tables 2-36, 44-49, 52, 54-60, 63-68, and 70-74. The designated nucleic acid molecules include those differentially expressed in leukemia risk groups selected from the T-ALL risk group (Tables 7, 14, 21, 28, 35, 59, and 67); E2A-PBX1 risk group (Tables 3, 10, 17, 24, 31, 55, 64, and 71), TEL-AML1 risk group (Tables 8, 15, 22, 29, 36, and 60, 68, and 74), BCR-ABL risk group (Tables 2, 9, 16, 23, 30, 54, 63, and 70), MLL risk group (Tables 5, 12, 19, 26, 33, 57, 66, and 73), Hyperdiploid >50 risk group (Tables 4, 11, 18, 25, 32, 56, 65, and 72), and Novel risk group (Tables 6, 13, 20, 27, 34, and 58), those differentially expressed in subjects affected by leukemia who will relapse after conventional therapy (Tables 44-48), and those differentially expressed in subjects affected by TEL-AML1 who will develop secondary AML after conventional therapy (Table 52).

[0047] The arrays of the invention comprise a substrate have a plurality of addresses, where each addresses has a capture probe that can specifically bind a target nucleic acid molecule. The number of addresses on the substrate varies with the purpose for which the array is intended. The arrays may be low-density arrays or high-density arrays and may contain 4 or more, 8 or more, 12 or more, 16 or more, 20 or more, 24 or more, 32 or more, 48 or more, 64 or more, 72 or more 80 or more, 96, or more addresses, or 192 or more, 288 or more, 384 or more, 768 or more, 1536 or more, 3072 or more, 6144 or more, 9216 or more, 12288 or more, 15360 or more, or 18432 or more addresses. In some embodiments, the substrate has no more than 12, 24, 48, 96, or 192, or 384 addresses, no more than 500, 600, 700, 800, or 900 addresses, or no more than 1000, 1200, 1600, 2400, or 3600 addressees.

[0048] The invention also provides a computer-readable medium comprising one or more digitally-encoded expression profiles, where each profile has one or more values representing the expression of a gene that is differentially expressed in a leukemia risk group, the expression level of a gene that is differentially expressed in subjects affected by leukemia who will relapse after conventional therapy, or the expression level of a gene that is differentially expressed in subjects affected by leukemia who will develop secondary AML after conventional therapy. Such profiles are described elsewhere herein. In some embodiments, the digitally-encoded expression profiles are comprised in a database. See, for example, U.S. Pat. No. 6,308,170.

[0049] The present invention also provides kits useful for diagnosing, treating, and monitoring the disease state in subjects affected by leukemia. These kits comprise an array and a computer readable medium. The array comprises a substrate having addresses, where each address has a capture probe that can specifically bind a nucleic acid molecule that is differentially expressed in at least one leukemia risk group, in a subject affected by leukemia who will relapse after conventional therapy, or in a subject affected by leukemia who will develop secondary AML after conventional therapy. The results are converted into a computer-readable medium that has digitally-encoded expression profiles containing values representing the expression level of a nucleic acid molecule detected by the array.

[0050] Methods of Screening and Therapeutic Targets

[0051] The methods and compositions of the invention may be used to screen test compounds to identify therapeutic compounds useful for the treatment of leukemia. In one embodiment, the test compounds are screened in a sample comprising primary cells or a cell line representative of a particular leukemia risk group. After treatment with the test compound, the expression levels in the sample of one or more of the differentially-expressed genes of the invention are measured using methods described elsewhere herein. Values representing the expression levels of the differentially-expressed genes are used to generate a subject expression profile. This subject expression profile is then compared to a reference profile associated with the leukemia risk group represented by the sample to determine the similarity between the subject expression profile and the reference expression profile. Differences between the subject expression profile and the reference expression profile may be used to determine whether the test compound has anti-leukemogenic activity.

[0052] The test compounds of the present invention can be obtained using any of the numerous approaches in combinatorial library methods known in the art, including: biological libraries; spatially addressable parallel solid phase or solution phase libraries; synthetic library methods requiring deconvolution; the ‘one-bead one-compound’ library method; and synthetic library methods using affinity chromatography selection. The biological library approach is limited to polypeptide libraries, while the other four approaches are applicable to polypeptide, non-peptide oligomer or small molecule libraries of compounds (Lam (1997) Anticancer Drug Des. 12:145).

[0053] Examples of methods for the synthesis of molecular libraries can be found in the art, for example in DeWitt et al. (1993) Proc. Natl. Acad. Sci. USA 90:6909; Erb et al. (1994) Proc. Natl. Acad. Sci. USA 91:11422; Zuckermann et al. (1994). J. Med. Chem. 37:2678; Cho et al. (1993) Science 261:1303; Carell et al. (1994) Angew. Chem. Int. Ed. Engl. 33:2059; Carell et al. (1994) Angew. Chem. Int. Ed. Engl. 33:2061; and in Gallop et al. (1994) J. Med. Chem. 37:1233. Libraries of compounds may be presented in solution (e.g., Houghten (1992) Biotechniques 13:412-421), or on beads (Lam (1991) Nature 354:82-84), chips (Fodor (1993) Nature 364:555-556), bacteria (U.S. Pat. No. 5,223,409), spores (U.S. Pat. No. 5,223,409), plasmids (Cull et al. (1992) Proc. Natl. Acad. Sci. USA 89:1865-1869) or on phage (Scott and Smith (1990) Science 249:386-390); (Devlin (1990) Science 249:404-406); (Cwirla et al. (1990) Proc. Natl. Acad. Sci. U.S.A. 97:6378-6382); (Felici (1991) J. Mol. Biol. 222:301-310).

[0054] Candidate compounds include, for example, 1) peptides such as soluble peptides, including Ig-tailed fusion peptides and members of random peptide libraries (see, e.g., Lam et al. (1991) Nature 354:82-84; Houghten et al. (1991) Nature 354:84-86) and combinatorial chemistry-derived molecular libraries made of D- and/or L-configuration amino acids; 2) phosphopeptides (e.g., members of random and partially degenerate, directed phosphopeptide libraries, see, e.g., Songyang et al. (1993) Cell 72:767-778); 3) antibodies (e.g., polyclonal, monoclonal, humanized, anti-idiotypic, chimeric, and single chain antibodies as well as Fab, F(ab′)2, Fab expression library fragments, and epitope-binding fragments of antibodies); 4) small organic and inorganic molecules (e.g., molecules obtained from combinatorial and natural product libraries; 5) zinc analogs; 6) leukotriene A4 and derivatives; 7) classical aminopeptidase inhibitors and derivatives of such inhibitors, such as bestatin and arphamenine A and B and derivatives; 8) and artificial peptide substrates and other substrates, such as those disclosed herein above and derivatives thereof.

[0055] The present invention discloses a number of genes that are differentially expressed in leukemia risk groups, in subjects affected by leukemia who will relapse after conventional therapy, or in subjects affected by leukemia who will develop secondary AML after conventional therapy. These differentially-expressed genes are shown in Tables 2-36 and 44-48, and 52. Because the expression of these genes is associated with leukemia risk factors, these genes may play a role in leukemogenesis. Accordingly, these genes and their gene products are potential therapeutic targets that are useful in methods of screening test compounds to identify therapeutic compounds for the treatment of leukemia.

[0056] The differentially-expressed genes of the invention may be used in cell-based screening assays involving recombinant host cells expressing the differentially-expressed gene product. The recombinant host cells are then screened to identify compounds that can activate the product of the differentially-expressed gene (i.e. agonists) or inactivate the product of the differentially-expressed gene (i.e. antagonists).

[0057] Any of the leukemogenic functions mediated by the product of the differentially expressed gene may be used as an endpoint in the screening assay for identifying therapeutic compounds for the treatment of leukemia. Such endpoint assays include assays for cell proliferation, assays for modulation of the cell cycle, assays for the expression of markers indicative of leukemia, and assays for the expression level of genes differentially expressed in leukemia risk groups as described above.

[0058] Modulators of the activity of a product of a differentially-expressed gene identified according to these drug screening assays provided above can be used to treat a subject with leukemia. These methods of treatment include the steps of administering the modulators of the activity of a product of a differentially-expressed gene in a pharmaceutical composition as described herein, to a subject in need of such treatment.

[0059] The following examples are offered by way of illustration and not by way of limitation.

EXAMPLES

Example 1

[0060] To determine if gene expression profiling of leukemic cells could identify known biologic ALL subgroups, 327 diagnostic bone marrow (BM) samples were analyzed with AFFYMETRIX® oligonucleotide microarrays (Affymetrix Inc., Santa Clara, Calif.) containing 12,600 probe sets.

[0061] In an initial analysis of the gene expression data set (12,600 probe sets in 327 leukemia samples; greater than 4×106 data elements), an unsupervised two-dimensional hierarchical clustering algorithm was used to group leukemia samples with similar gene expression patterns against clusters of similarly expressed genes. This analysis clearly identified 6 major leukemia subtypes that corresponded to T-ALL, hyperdiploid with >50 chromosomes, BCR-ABL, E2A-PBX1, TEL-AML1, and MLL gene rearrangement. Moreover, within the heterogeneous collection of leukemias that were not assigned to one of these subtypes, a novel subgroup of 14 cases was identified that had a distinct gene expression profile. The separation of these seven leukemia subgroups was also seen using the multidimensional scaling procedure of discriminant analysis with variance (DAV), in which the data are reduced into component dimensions consisting of linear combinations of discriminating genes. For example, using the three component dimensions that accounted for 72.8% of the variance of gene expression among the subgroups, it was possible to distinguish T-ALL (43 cases), E2A-PBX1 (27 cases), TEL-AML1 (79 cases) and hyperdiploid >50 (64 cases) from the remaining ALL subtypes (114 cases). Similarly, using three different components that account for an additional 16.1% of the variance in gene expression mad it possible to discriminate cases with BCR-ABL (15 cases), MLL gene rearrangement (20 cases) and the novel subgroup of ALL (14 cases).

[0062] Statistical methods were used to identify those genes that best define the individual groups. Expression profiles were obtained using the top 40 genes per subgroup as selected by a Chi square metric. Distinct groups of genes distinguish cases defined by E2A-PBX1, MLL, T-ALL, hyperdiploid >50, BCR-ABL, the novel subgroup, and TEL-AML1. In addition to these specific subgroups, 65 cases (20% of the total) were identified that did not cluster into any of the leukemia subtypes. The expression profiles of these latter cases varied markedly, suggesting that they represent a heterogeneous group of leukemias. Nearly identical results were obtained when the hierarchical clustering was performed with genes selected by other statistical metrics.

[0063] For T-ALL, two gene clusters that discriminated this subtype from B-lineage cases were identified. One cluster was expressed at high and one cluster was expressed at low levels. In contrast the top ranked discriminating genes for each of the other leukemia subtypes consisted primarily of genes that were overexpressed within the specific leukemia subtype. With the exception of T-ALL, the identified expression profiles do not represent a specific differentiation stage of the leukemic blasts. For example, although E2A-PBX1 is almost exclusively found in ALLs with a pre-B cell immunophenotype (Hunger (1996) Blood 87:1211-24), the identified expression profile was specific for the E2A-PBX1 genetic lesion and not the pre-B immunophenotype.

[0064] To confirm that the microarray analysis provided an accurate reflection of actual gene expression levels, the microarray data was compared with results for RNA levels obtained by real-time RT-PCR (5 genes). In addition, the corresponding protein levels were assessed by immunophenotype analysis performed by flow cytometry using nine specific cell surface antigens). A very high degree of correlation was observed between the levels of RNA expression detected by quantitative RT-PCR and microarray analysis. Similarly, in agreement with results from immunophenotying, T-lineage restricted RNA expression was observed for CD2, CD3, and CD8, whereas B-lineage restricted expression was observed for CD19, and CD22. In addition, the level of CD10 RNA expression closely correlated with protein levels, with high expression detected in TEL-AML1 leukemias, intermediate levels in E2A-PBX1 and low to undetectable expression in cases with rearrangements of MLL. Thus, microarray analysis provides an accurate reflection of expression levels for most genes, and can be used to accurately detect the expression of the more common surface antigens used in the diagnostic evaluation of pediatric ALL patients.

[0065] The majority of the leukemia subtype specific genes identified through this study were not previously known to have a restricted pattern of expression. In addition to their use as diagnostic and subclassification markers, these genes provide unique insights into the underlying biology of the different leukemia subtypes. For example, E2A-PBX1 leukemias were characterized by high expression of the c-Mer receptor tyrosine kinase (MERTK), a known transforming gene (Graham et al. (1994) Cell Growth Differ. 5:647-657); and Georgescu et al. (1999) Mol. Cell. Biol. 19:1171-81), suggesting that C-MER may be involved in the abnormal growth of these cells. Similarly, HOXA9 and MEIS1 were exclusively expressed in cases having MLL rearrangements, indicating that they may be directly involved in MLL mediated alterations in the growth of the leukemic cells. Interestingly, high expression of MTG16, a homologue of ETO (Gamou et al. (1998) Blood 91:4028-4037), was found in TEL-AML1 cases. Alteration of ETO family members in both t(8;21) acute myeloid leukemia (by translocation) (Downing (1999) Br. J. Hematol. 106:296-308) and TEL-AML1 (by altered expression) suggests that alteration in the biologic function of ETO genes is mechanistically involved in these leukemias. Little is known about the underlying molecular pathogenesis of hyperdiploid ALL >50 chromosomes, which clinically is distinct from hyperdiploid cases having 47-50 chromosomes. This distinction is supported by the marked differences in gene expression profiles between these two subgroups. Although hyperdiploid >50 ALLs have an excellent prognosis, the specific genetic lesions responsible for the aberrant proliferation in these cases remains poorly understood. Interestingly, almost 70% of the genes that define this subgroup are localized to either chromosome X or 21. Moreover, the class defining genes on chromosome X were overexpressed in the hyperdiploid >50 chromosomes ALLs irrespective of whether the leukemic blasts had a trisomy of this chromosome (data not shown). Detailed analysis will be required to determine the specific signaling pathways that are disrupted as a result of the altered expression of these genes. Lastly, the novel subgroup of ALL was defined by high expression of a group of genes, including the receptor phosphatase PTPRM, and LHFPL2, a gene that is a part of the LHFP-like gene family, the founding member of which was identified as the target of a lipoma-associated chromosomal translocation (Petit et al. (1999) Genomics 57:438-41).

[0066] Expression Profiling as a Diagnostic Tool

[0067] A major goal of this study was to develop a single platform of expression profiling to accurately identify the known, prognostically important leukemia subtypes. To this end, computer-assisted learning algorithms were used to develop an expression-based leukemia classification. Through a reiterative process of error minimization, these algorithms learn to recognize the optimal gene expression patterns for a leukemia subtype. Classification was approached using a decision tree format, in which the first decision was T-ALL versus B-lineage (non-T-ALL), and then within the B-lineage subset, cases were sequentially classified into the known risk groups characterized by the presence of E2A-PBX1, TEL-AML1, BCR-ABL, MLL chimeric genes, and lastly hyperdiploid with >50 chromosomes. Cases not assigned to one of these classes were left unassigned. Classification was performed using a Support Vector Machine (SVM) algorithm with a set of discriminating genes selected by a correlation-based feature selection (CFS), or if this method selected greater than 20 genes for a particular class, by using the top 20 ranked genes selected by a chi-square metric, or one of the other metrics detailed in the Experimental Procedures section. This approach resulted in an accurate class prediction in a randomly selected training set that consisted of two-thirds of the total cases (215 cases). When this classification model was then applied to a blind test set consisting of the remaining 112 samples, an overall accuracy of 96% was achieved for class assignment. The number of genes required for optimal class assignment varied between classes. A single gene was sufficient to give 100% accuracy for both T-ALL and E2A-PBX1, whereas 7-20 genes were required for prediction of the other classes. Only slight differences were observed in the prediction accuracy of individual classes when the process was repeated using genes selected by a number of other metrics, including T-statistics, a novel metric referred to as Wilkins', or genes selected by a combination of self organizing maps (SOM) and DAV. Moreover, nearly identical results were obtained when the various sets of selected genes were used in a number of different supervised learning algorithms, including κ-Nearest Neighbor (κ-NN), Artificial Neural Network (ANN), and prediction by collective likelihood of emerging patterns (PCL).

[0068] Four cases initially appeared to be misclassified as TEL-AML1 by gene expression analysis since they lacked a detectable chimeric transcript by RT-PCR. Upon further analysis by FISH, however, one of these cases was shown to have a TEL-AML1 fusion, presumably, a variant rearrangement that could not be detected with the amplification primers used for the TEL-AML1 RT-PCR assay. In each of the three remaining cases, re-examination of the karyotypes revealed translocations involving the p arm of chromosome 12. FISH analysis demonstrated that two of these cases had deletion of one TEL allele, whereas the remaining case had a partial deletion of one TEL allele. Thus, the identified expression profiles appear to reflect an abnormality of the TEL transcription factor, and may in fact provide a more accurate means of identifying a specific leukemia subtype defined by its underlying biology. Collectively, these data demonstrate that the single platform of gene expression profiling can accurately identify the known prognostic subtypes of ALL.

[0069] Use of Expression Profiles to Identify Patients at High Risk of Treatment Failure

[0070] Relapse and the development of therapy-induced acute myeloid leukemia (AML) are the major causes of treatment failure in pediatric ALL. To determine if expression profiling might further enhance the ability to identify patients who are likely to relapse, the expression profiles of the four groups of leukemic samples were compared. The groups of samples used for this comparison were: 1)diagnostic samples of patients that developed hematological relapses (n=32); (ii) diagnostic samples from patients who remained in continuous complete remission (CCR) (n=201); (iii) diagnostic samples from patients who developed therapy-induced AML (n=16); and (iv) leukemic samples collected at the time of ALL relapse (n=25). Using DAV, distinct gene expression profiles were identified for each of these groups.

[0071] To further assess the predictive power of the different gene expression profiles, supervised learning algorithms were used. Because of the overwhelming differences in the expression profiles of the different leukemia subtypes, it was not possible to identify a single expression signature that would predict relapse irrespective of the genetic subtype. However, within individual leukemic subtypes, distinct expression profiles could be defined that predicted relapse. Class assignment was performed using a SVM supervised learning algorithm with discriminating genes selected by CFS, or if this method returned >20 genes, the top 20 genes selected by T-statistics. For both the T-lineage and hyperdiploid >50 subgroups, expression profiles identified those cases that went on to relapse with an accuracy of 97% and 100%, respectively, as assessed by cross validation. Moreover, the predictive accuracy was statistically significant when compared to results from an analysis of 1000 random permutations of the specific patient data set. Similarly, expression profiles predictive of relapse were identified for TEL-AML, MLL, or cases that lacked any of the known genetic risk features. Although the predictive accuracy of these latter expression profiles was very high as assessed by cross validation, it did not reach statistical significance when compared to results from an analysis of 1000 random permutations of the same patient data set, likely secondary to the limited number of cases. The patterns of expression for a combination of genes, rather than expression levels of a single gene were found to have the greatest predictive accuracy. Since few known risk-stratifying biologic features have been previously identified for either T-ALL or hyperdiploid >50 ALL, the results suggest that the identified expression profiles provide independent risk stratifying information.

[0072] A distinct expression profile was identified in the ALL blasts from patients who developed therapy-induced AML. Because secondary AML is thought to arise from a hematopoietic stem cell that is distinct from that giving rise to the primary leukemia, it is difficult to understand how the biology of the original ALL blasts could predict the risk of developing a therapy-induced complication. However, when the accuracy of expression profiling was evaluated in within the TEL-AML1 subgroup, a distinct expression signature consisting of 20 genes was defined. This profile identified, with 100% accuracy in cross validation, all patients who developed secondary AML, with a p value of 0.031 as assessed by comparison to results from an analysis of 1000 random permutations of the patient data set. Genes within this signature included RSU1, a suppressor of the Ras signaling pathway, and Msh3, a mismatch repair enzyme.

[0073] Overview of Experimental Procedures

[0074] A. Tumor Samples

[0075] The diagnosis of ALL was based on the morphologic evaluation of the bone marrow and on the pattern of reactivity of the leukemic blasts with a panel of monoclonal antibodies directed against lineage-associated antigens. A total of 389 pediatric acute leukemia samples were analyzed in this study, from which high quality gene expression data was obtained on 360 (93%). The successfully-analyzed samples included 332 diagnostic BM, 3 diagnostic peripheral bloods (PB), and 25 relapsed ALL samples from BM or PB. 264 (79%) of the diagnostic ALL BM samples and all relapse samples were from patients enrolled on St. Jude Children's Research Hospital Total Therapy Studies XIIIA or XIIIB and corresponded to 64% of the patients treated on these protocols. The details of these protocols have been previously published (Pui et al. (2000) Leukemia 14:2286-94). The remaining samples were obtained from patients treated on St. Jude Total Therapy Studies XI, XII, XIV, XV, or by best clinical management. All protocols and consent forms were approved by the hospital's institutional review board, and informed consent was obtained from parents, guardians, or patients (as appropriate). The composition of the data sets used for the identification of gene expression profiles predictive of specific genetic subtypes, hematological relapse, and risk of developing secondary AML are described below.

[0076] B. Gene Expression Profiling

[0077] RNA was extracted from cryopreserved mononuclear cell suspensions from diagnostic BM aspirates or PB samples using TRIZOL® (Invitrogen Corp., Carlsbad, Calif.) according to the manufacturer's instructions, and the RNA integrity was assessed by using an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, Calif.). cDNA was synthesized using a T-7 linked oligo-dT primer and cRNA was then synthesized with biotinylated UTP and CTP. The labeled RNA was then fragmented and hybridized to HG_U95Av2 oligonucleotide arrays (Affymetrix Incorporated, Santa Clara, Calif.) according to the manufacturer's instructions.

[0078] Arrays were scanned using a laser confocal scanner (Agilent) and the expression value for each gene was calculated using AFFYMETRIX® Microarray Software version 4.0. The average intensity difference (AID) values were normalized across the sample set and minimum quality control standards were established for including a sample's hybridization data in the study. 10% of samples were run in duplicate to ensure consistency of data acquisition throughout the study. A high level of reproducibility was observed between replicate samples, with fewer than 1% of genes showing a variation in average intensity difference of greater than 2-fold.

[0079] C. Statistical Analysis

[0080] Unsupervised hierarchical clustering, principal component analysis (PCA), discriminant analysis with variance (DAV), and self organizing maps (SOM) were performed using GeneMaths software (version 1.5, Applied Maths, Belgium). Data reduction to define the genes most useful in class distinction was performed using a variety of metrics as detailed below. Genes selected by the various metrics were used in supervised learning algorithms to build classifiers that could identify the specific genetic or prognostic subgroups. The algorithms used included k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), prediction by collective likelihood of emerging patterns (PCL), an artificial neural network (ANN), and weighted voting. Performance of each model was initially assessed by leave-one-out cross validation on a randomly selected stratified training set consisting of two-thirds of the total cases. True error rates of the best performing classifiers were then determined using the remaining third of the samples as a blinded test group. Details of the individual metrics and supervised learning algorithms are described below.

[0081] Detailed Experimental Procedures

[0082] A. RNA Extraction, Labeling, Hybridization, and Data analysis

[0083] Mononuclear cell suspensions from diagnostic BM aspirates or peripheral blood (PB) samples were prepared from each patient and an aliquot was cryopreserved. RNA was extracted using TRIZOL® following the manufacture's recommended protocol as described above. RNA integrity was assessed by electrophoresis on the Agilent 2100 Bioanalyzer (Agilent, Palo Alto, Calif.).

[0084] First and second strand cDNA were synthesized from 5-15 μg of total RNA using the SuperScript Double-Stranded cDNA Synthesis Kit ((Invitrogen Corp., Carlsbad, Calif.) and an oligo-dT24-T7 (5′-GGC CAG TGA ATT GTA ATA CGA CTC ACT ATA GGG AGG CGG-3′; SEQ ID NO: 1) primer according to the manufacturer's instructions. cRNA was synthesized and labeled with biotinylated UTP and CTP by in vitro transcription using the T7 promoter coupled double stranded cDNA as template and the T7 RNA Transcript Labeling Kit according the manufacturer's instructions (Enzo Diagnostics Inc., Farmingdale N.Y.). Briefly, double stranded cDNA synthesized from the previous steps was washed twice with 70% ethanol and resuspended in 22 μl RNase-free water. The cDNA was incubated with 4 μl of 10× each reaction buffer, 1 μl of biotin labeled ribonucleotides, 2 μl of DTT, 1 μl of RNase inhibitor mix and 2 μl 20× T7 RNA polymerase for 5 hours at 37° C. The labeled cRNA was separated from unincorporated ribonucleotides by passing through a CHROMA SPIN-100 column (Clontech, Palo Alto, Calif.) and precipitated at −20° C. for 1 hr to overnight.

[0085] The cRNA pellet was resuspended in 10 μl Rnase-free H2O and 10.0 μg was fragmented by heat and ion-mediated hydrolysis at 95° C. for 35 minutes in 200 mM Tris-acetate, pH 8.1, 500 mM KOAc, 150 mM MgOAc. The fragmented cRNA was hybridized for 16 hr at 45° C. to HG_U95Av2 AFFYMETRIX® oligonucleotide arrays (Affymetrix, Santa Clara, Calif.) containing 12,600 probe sets from full-length annotated genes together with additional probe sets designed to represent EST sequences. Arrays were washed at 25° C. with 6×SSPE (0.9M NaCl, 60 mM NaH2PO4, 6 mM EDTA, 0.01% Tween 20) followed by a stringent wash at 50° C. with 100 mM MES, 0.1M NaCl2, 0.01% Tween 20. The arrays were then stained with phycoerythrin conjugated streptavidin (Molecular Probes, Eugene, Oreg.).

[0086] Arrays were scanned using a laser confocal scanner (Agilent, Palo Alto, Calif.) and the expression value for each gene was calculated using AFFYMETRIX® Microarray software (MAS 4.0). The signal intensity for each gene was calculated as the average intensity difference (AID), represented by [Σ(PM−MM)/(number of probe pairs)], where PM and MM denote perfect-match and mismatch probes, respectively. Expression values were normalized across the sample set by scaling the average of the fluorescent intensities of all genes on an array to a constant target intensity of 2500, then any AID over 45,000 was capped to a value of 45,000. All AID's less than 100, including negative values and absent calls were converted to a value of 1. In addition, a variation filter was used to eliminate any probe set in which fewer than 1% of the samples had a present call, or if the Max AID−Min AID across the sample set was less than 100. The average intensity differences for each of the remaining genes were analyzed. For some metrics the data was log transformed prior to analysis. The minimum quality control values required for inclusion of a sample's hybridization data in the study were 10% or greater present calls, a GAPDH/Actin 3′/5′ ratio<5, and use of a scaling factor that was within 3 standard deviations from the mean of the scaling values of all chips analyzed.

[0087] The average percent present calls for theoverall data set was 29.7%, and for each of the genetic subgroups was BCR-ABL (31.1%), E2A-PBX1 (28.9%), Hyper >50 (31%), MLL (29.8%), T-ALL (29.1%), TEL-AML1 (28.5%), Novel (30.2%), others (31.1%). In addition, each sample had >75% blasts. The average percentage blasts for the overall data set used to define the genetic subtypes was 93%, and for each genetic subtype was BCR-ABL (92%), E2A-PBX1 (96%), Hyper >50 (93%), MLL (93%), T-ALL (91%), TEL-AML1 (92%), Novel (95%), and others (94%).

[0088] B Reproducibility of Microarray Data

[0089] The reproducibility of the AFFYMETRIX® microarray system was assessed by comparing the gene expression profiles of RNA extracted from duplicate cryopreserved diagnostic leukemic samples from 23 patients with single RNA samples from 13 patients analyzed on two separate arrays. The mean number of probe sets that displayed a ≧2-fold difference in expression between separately extracted but paired RNA samples was 144, and for single RNA samples analyzed on two separate occasions was 133. Moreover, very few probe sets were found to have a ≧3-fold difference in expression levels between replicate samples. The observed number of probe sets showing a difference in expression values represents less than 2% of the total number of probe sets on the microarray, and thus these data suggest that the AFFYMETRIX® microarray system has a very high degree of reproducibility.

[0090] C. Comparison of Expression Profiles from PB and BM leukemia samples

[0091] Matched BM and PB samples that contained ≧80% leukemic blasts were obtained from 10 patients and the RNA was extracted and assessed by microarray analysis. A very high level of correlation was observed between the expression profiles of BM and PB, with only 189 probe sets having a greater than a 2-fold difference in expression. No genes were found to be consistently over- or under-expressed in one sample type. These data demonstrate that there are minimal differences in the gene expression profiles of leukemic blasts obtained from BM or PB, and that diagnostic gene expression profiling is possible on samples obtained from the PB.

[0092] D. RT-PCR Results

[0093] Real-time TAQMAN® RT-PCR assays (Applied Biosystems, Foster City, Calif.) were performed to independently determine the level of mRNA for five genes that were found by microarray analysis to be predictive of either T-lineage ALL (CD3δ, CD3D antigen delta polypeptide TiT3 complex; MAL, mal T-Cell differentiation protein; and PRKCQ, protein kinase C theta) or E2A-PBX1 expressing ALL (MERTK, c-Mer proto-oncogene tyrosine kinase and KIAA802). The RNA samples analyzed included four samples each of E2A-PBX1 and T-ALL, and two samples each from the remaining subtypes (BCR-ABL, MLL, TEL-AML1, Hyperdiploid >50, Hyperdiploid 47-50, Hypodiploid, Pseudodiploid, and normal). Whenever possible, the forward and reverse primers were designed in different exons so that DNA contamination would not be a concern. In the case of MAL where this was not clear, the RNA was treated for 15 minutes at room temperature with 1.0 unit of DNase I (Invitrogen Corp., Carlsbad, Calif.) using the Invitrogen protocol to remove any contaminating DNA.

[0094] Thirty-three ng of RNA from each sample was reverse transcribed using random hexamers and Multiscribe Reverse Transcriptase (Applied Biosystems, Foster City, Calif.) in a total volume of 10 μl. Real time PCR was performed on a Applied Biosystems PRISM® 7700 Sequence Detection System (Applied Biosystems). All probes were labeled at the 5′ end with FAM (6-carboxy-fluroescein) and at the 3′ end with TAMRA (6-carboxy-tetramethyl-rhodamine).

[0095] The PCR reactions were performed in a total volume of 50 μl containing 10 μl of the reverse transcriptase product, 300 nM each of the forward and reverse primers, 100 nM of probe, 1× master mix and 1 μl of AMPLITAQ GOLD® DNA polymerase (Applied Biosystems). Following a 10 minute incubation at 95° C. to activate the polymerase, samples were denatured at 95° C. for 15 seconds, then annealed and extended at 60° C. for 1 minute, for a total of 40 cycles. The RNA from each sample was also amplified using primers and probes to RNase P (Applied Biosystems) for use in normalization according to the manufacturer's instructions. Negative controls were included in each run. Standard curves were generated for T-cell markers and RNase P using MOLT4 RNA, a T-cell leukemia cell line, and for the E2A-PBX1 markers and RNase P using a leukemia cell line, 697, that contains an E2A-PBX1 fusion.

[0096] The expression level of the predictive genes and RNase P were determined in each of the 24 ALL samples. A ratio was then calculated by taking the expression value for the specific gene and dividing it by the expression level of RNase P in the sample. These ratios were then compared to the values obtained from the AFFYMETRIX® chip data from the same RNA sample. The raw AFFYMETRIX® chip data were scaled as described and then normalized using the 3′GAPDH value for each sample, yielding a normalized ratio. The TAQMAN® results and AFFMETRIX® chip ratios were then log transformed and compared. Since the markers selected for TAQMAN® analysis were predictors for either E2A-PBX1 or T-ALLs, each gene was expected to have four RNA samples with high and 20 samples with low expression. For each gene evaluated, an average expression value for both the TAQMAN® results and AFFYMETRIX® data was calculated for all samples in the up-regulated group, and similarly, for the samples in the down-regulated group.

[0097] E. Comparison of Real-time RT-PCR Data and AFFYMETRIX® Chip Data

[0098] The normalized gene expression ratios for the TAQMAN® data (gene/RNase P) and for the AFFYMETRIX® microarray data (AID for a gene/AID for GAPDH) were log transformed and then the average expression values for each gene was calculated in the four samples in which its expression was expected to be up-regulated and separately in the 20 samples in which its expression was expected to be down-regulated. For example, for genes that were expected to be up-regulated in T-ALL (CD3δ, MAL, and PRKCQ), the log expression ratios in the T-ALL samples were averaged to give the up regulated values and the log expression ratios of each gene in the non-T-ALL cases were averaged to give the down regulated value.

[0099] In both the TAQMAN® and the microchip array analysis, MERTK and KIAA802, were very highly expressed in the diagnostic samples containing E2A-PBX1, and expressed at low levels in all of the other samples. Likewise, PRKCQ, CD3δ, and MAL, showed high levels of expression in T cells by both methodologies in comparison with non T-cells. The normalized ratios from the TAQMAN® assay were plotted against the normalized ratios from the microchip array for both the up-regulated and down-regulated genes. The correlation between TAQMAN® results and the microchip array results was 70%, indicating that the same pattern of gene expression was seen in both analyses. The MERTK was extremely high in two of the E2A-PBX1 patient samples by TAQMAN® analysis. Removal of the MERTK gene from the analysis resulted in a correlation of 91% between the TAQMAN® results and the microchip array results.

[0100] F. Comparison of AFFYMETRIX® Microarray Chip Results and Immunophenotype Results

[0101] Leukemic blasts at the time of diagnosis were analyzed for expression of lineage restricted cell surface antigens using phycoerythrin- or fluorescein isothiocyanate-conjugated monoclonal antibodies against CD2, CD3ε, CD4, CD5, CD7, CD8, CD10, CD19, and CD22 (Becton Dickinson Immunocytometry Systems, San Jose, Calif., USA). Data were obtained using a COULTER® EPICS XL™ (Beckman Coulter, Miami, Fla.), a COULTER® ELITE™ (Beckman Coulter), or a BD FACSCalibur™ flow cytometer (Becton Dickinson, San Jose, Calif.) . The expression patterns for these antigens were then compared to gene expression patterns for the AFFYMETRIX® chip sites specified for CD2 (1 probe set, 40738_at), CD3δ(1 probe set, 38319_at), CD3ε(1 probe set, 36277_at), CD3ζ(1 probe set, 37078_at), CD3γ(1 probe set, 39226_at), CD4 (5 probe sets, 856_at, 1146_at, 35517‘at, 34003_at, and 37942_at), CD5 (1 probe set, 32953_at), CD7 (1 probe set, 771_s_at), CD8α(1 probe set, 40699_at), CD8β(1 probe set, 39239_at), CD10 (1 probe set, 1389_at), CD19 (2 probe sets, 1096_g_at and 1116_at), and CD22 (2 probe sets, 38521_at and 38522_s_at). As a control, the performance of the AFFYMETRIX® microarray probe sets were also assessed using RNA isolated from flow sorted single positive CD4+ and CD8+ thymocytes, and CD10+/CD19+ bone marrow cells. High RNA expression was observed in T-ALL for the T-lineage restricted genes CD2, CD3δ, ε, and ζ, CD8α, and CD7, and in B-lineage ALLs for the B-cell restricted genes CD19, and CD22. A similar high level of correlation was observed between RNA and protein expression for CD10. The observed low expression levels of T-cell restricted genes in B-cell cases, and B-cell restricted genes in T-ALLs, is consistent with the low level of normal contaminating lymphocytes present in the diagnostic marrow samples analyzed.

[0102] G. Patient Data Set

[0103] A total of 389 Pediatric acute leukemia samples were analyzed in this study, from which high quality gene expression data were obtained on 360 (93%). The successfully analyzed samples included: 332 diagnostic bone marrows (BM), 3 diagnostic peripheral blood samples (PB), and 25 relapse ALL samples from BM or PB. 264 (79%) of the diagnostic ALL BM samples and all relapse samples were from patients treated on St. Jude Children's Research Hospital Total Therapy Studies XIIIA or XIIIB and correspond to 64% of the patients treated on these protocols. The details of these protocols are described in Pui et al., “Risk-adapted treatment for acute lymphoblastic leukemia: findings from St. Jude Children's Research Hospital,” Haematology and Blood Transfusions, 1997, pp 629-37, Springer-Verlag, Berlin and in Pui et al. (2000) Leukemia 14:2286-94. Study XIIIA ran from Dec. 20, 1991 to Aug. 23, 1994 and enrolled 165 patients, whereas Study XIIIB ran from Aug. 24, 94 to Jul. 27, 1998 and enrolled 247 patients. No patients were lost to follow-up during treatment. When the databases were frozen for analysis, 100% and 93% of event-free survivors in studies XIIIA and XIIIB, respectively, had been seen within 12 months. The median (minimum, maximum) follow-up of the event-free survivors was 8.09 (6.59, 9.94) and 4.52 (2.37, 7.06) years for XIIIA and XIIIB, respectively. All other samples were obtained from patients treated on St. Jude Total Therapy Studies XI, XII, XIV, XV, or by best clinical management.

[0104] For the identification of gene expression profiles that predict specific genetic subtypes of ALL, 327 diagnostic BM samples were used. The criteria for inclusion in this data set were the availability of a cryopreserved diagnostic BM sample containing ≧75% blasts, and complete data from each of the following diagnostic studies: morphology, immunophenotype, cytogenetics, DNA ploidy, Southern blot for MLL gene rearrangements, and RT-PCR analysis for MLL-AF4, MLL-AF9, E2A-PBX1, TEL-AML1, and BCR-ABL. This final data set includes diagnostic BM samples from XV (38), XIV (4), XIIIA (100), XIIIB (161), or from patients treated on one of our older protocols or by best clinical management (24).

[0105] The data sets used to identify expression profiles predicative of hematologic relapse and the development of therapy-induced AML are described in Table 1.

1TABLE 1Patient DatabaseDiagnostic samples used for subtype classification (n = 327)Label@Protocol#Outcome%BCR-ABL subgroup (n = 15)BCR-ABL-C1T13BCCRBCR-ABL-R1T13AHeme RelapseBCR-ABL-R2T13AHeme RelapseBCR-ABL-R3T13BHeme RelapseBCR-ABL-T13BHeme RelapseHyperdip-R5BCR-ABL-#1T13ACensoredBCR-ABL-#2T13BCensoredBCR-ABL-#3T13BCensoredBCR-ABL-#4T11NABCR-ABL-#5T12NABCR-ABL-#6T12NABCR-ABL-#7T12NABCR-ABL-#8T14NABCR-ABL-#9T15NABCR-ABL-Hyperdip-#10T12NAE2A-PBX1 subgroup (n = 27)E2A-PBX1-C1T13ACCRE2A-PBX1-C2T13ACCRE2A-PBX1-C3T13ACCRE2A-PBX1-C4T13ACCRE2A-PBX1-C5T13ACCRE2A-PBX1-C6T13BCCRE2A-PBX1-C7T13BCCRE2A-PBX1-C8T13BCCRE2A-PBX1-C9T13BCCRE2A-PBX1-C10T13BCCRE2A-PBX1-C11T13BCCRE2A-PBX1-C12T13BCCRE2A-PBX1-R1T13BHeme RelapseE2A-PBX1-2M#1T13B2nd AMLE2A-PBX1-#1OthersNAE2A-PBX1-#2OthersNAE2A-PBX1-#3OthersNAE2A-PBX1-#4OthersNAE2A-PBX1-#5OthersNAE2A-PBX1-#6OthersNAE2A-PBX1-#7T11NAE2A-PBX1-#8T11NAE2A-PBX1-#9T12NAE2A-PBX1-#10T12NAE2A-PBX1-#11T14NAE2A-PBX1-#12T15NAE2A-PBX1-#13T15NAHyperdip >50 subgroup (n = 64)Hyperdip >50-C1T13ACCRHyperdip >50-C2T13ACCRHyperdip >50-C3T13ACCRHyperdip >50-C4T13ACCRHyperdip >50-C5T13ACCRHyperdip >50-C6T13ACCRHyperdip >50-C7T13ACCRHyperdip >50-C8T13ACCRHyperdip >50-C9T13ACCRHyperdip >50-C10T13ACCRHyperdip >50-C11T13ACCRHyperdip >50-C12T13ACCRRelapseHyperdip >50-C13T13ACCRRelapseHyperdip >50-C14T13ACCRRelapseHyperdip >50-C15T13BCCRRelapseHyperdip >50-C16T13BCCRRelapseHyperdip >50-C17T13BCCRHyperdip >50-C18T13BCCRHyperdip >50-C19T13BCCRHyperdip >50-C20T13BCCRHyperdip >50-C21T13BCCRHyperdip >50-C22T13BCCRHyperdip >50-C23T13BCCRHyperdip >50-C24T13BCCRHyperdip >50-C25T13BCCRHyperdip >50-C26T13BCCRHyperdip >50-T13BCCRC27-NHyperdip >50-C28T13BCCRHyperdip >50-C29T13BCCRHyperdip >50-C30T13BCCRHyperdip >50-C31T13BCCRHyperdip >50-C32T13BCCRHyperdip >50-C33T13BCCRHyperdip >50-C34T13BCCRHyperdip >50-C35T13BCCRHyperdip >50-C36T13BCCRHyperdip >50-C37T13BCCRHyperdip >50-C38T13BCCRHyperdip >50-C39T13BCCRHyperdip >50-C40T13BCCRHyperdip >50-C41T13BCCRHyperdip >50-C42T13BCCRHyperdip >50-C43T13BCCRHyperdip >50-R1T13AHemeHyperdip >50-R2T13AHemeHyperdip >50-R3T13AHemeHyperdip >50-R4T13BHemeHyperdip >50-R5T13BHemeHyperdip >50-2M#1T13A2nd AMLHyperdip >50-2M#2T13B2nd AMLHyperdip >50-#1T13ACensoredHyperdip >50-#2T13BCensoredHyperdip >50-#3OthersNAHyperdip >50-#4OthersNAHyperdip >50-#5T12NAHyperdip >50-#6T15NAHyperdip >50-#7T15NAHyperdip >50-#8T15NAHyperdip >50-#9T15NAHyperdip >50-#10T15NAHyperdip >50-#11T15NAHyperdip >50-#12T15NAHyperdip >50-#13T15NAHyperdip >50-#14T15NAHyperdip 47-50 subgroup (n = 23)Hyperdip 47-50-13ACCRC1Hyperdip 47-50-T13ACCRC2Hyperdip 47-50-T13ACCRC3-NHyperdip 47-50-T13ACCRC4Hyperdip 47-50-T13ACCRC5Hyperdip 47-50-T13BCCRC6Hyperdip 47-50-T13BCCRC7Hyperdip 47-50-T13BCCRC8Hyperdip 47-50-T13BCCRC9Hyperdip 47-50-T13BCCRC10Hyperdip 47-50-T13BCCRC11Hyperdip 47-50-T13BCCRC12Hyperdip 47-50-C13T13BCCRHyperdip 47-50-C14-NT13BCCRHyperdip 47-50-C15T13BCCRHyperdip 47-50-C16T13BCCRHyperdip 47-50-C17T13BCCRHyperdip 47-50-C18T13BCCRHyperdip 47-50-C19T13BCCRHyperdip 47-50-2M#1T13A2nd AMLHyperdip 47-50-#1T15NAHyperdip 47-50-#2T15NAHyperdip 47-50-#3T15NAHypodip subgroup (n = 9)Hypodip-C1T13ACCRHypodip-C2T13ACCRHypodip-C3T13BCCRHypodip-C4T13BCCRHypodip-C5T13BCCRHypodip-C6T13BCCRHypodip-2M#1T13A2nd AMLHypodip-#1T15NAHypodip-#2T15NAMLL subgroup (n = 20)MLL-C1T13ACCRMLL-C2T13BCCRMLL-C3T13BCCRMLL-C4T13BCCRMLL-C5T13BCCRMLL-C6T13BCCRMLL-R1T13AHeme RelapseMLL-R2T13AHeme RelapseMLL-R3T13BHeme RelapseMLL-R4T13BHeme RelapseMLL-2M#1T13A2nd AMLMLL-2M#2T13A2nd AMLMLL-#1T13BCensoredMLL-#2T13BCensoredMLL-#3OthersNAMLL-#4OthersNAMLL-#5OthersNAMLL-#6T12NAMLL-#7T14NAMLL-#8T14NANormal subgroup (n = 18)Normal-C1-NT13ACCRNormal-C2-NT13ACCRNormal-C3-NT13ACCRNormal-C4-NT13BCCRNormal-C5T13BCCRNormal-C6T13BCCRNormal-C7-NT13BCCRNormal-C8T13BCCRNormal-C9T13BCCRNormal-C10T13BCCRNormal-C11-NT13BCCRNormal-C12T13BCCRNormal-R1T13AHemeRelapseNormal-R2-NT13BHemeRelapseNormal-R3T13BHemeRelapseNormal-#1T13ACensoredNormal-#2T13BCensoredNormal-#3T13BCensoredPseudodip subgroup (n = 29)Pseudodip-C1T13ACCRPseudodip-C2-NT13ACCRPseudodip-C3T13ACCRPseudodip-C4T13ACCRPseudodip-C5T13ACCRPseudodip-C6T13ACCRPseudodip-C7T13ACCRPseudodip-C8T13ACCRPseudodip-C9T13ACCRPseudodip-C10T13BCCRPseudodip-C11T13BCCRPseudodip-C12T13BCCRPseudodip-C13T13BCCRPseudodip-C14T13BCCRPseudodip-C15T13BCCRPseudodip-C16-NT13BCCRPseudodip-C17T13BCCRPseudodip-C18T13BCCRPseudodip-C19T13BCCRPseudodip-R1-NT13AHemeRelapsePseudodip-#1T13BOtherRelapsePseudodip-#2T13BCensoredPseudodip-#3OthersNAPseudodip-#4OthersNAPseudodip-#5T15NAPseudodip-#6T15NAPseudodip-#7T15NAPseudodip-#8-NT15NAPseudodip-#9T15NAT-ALL subgroup (n = 43)T-ALL-C1T13ACCRT-ALL-C2T13ACCRT-ALL-C3T13ACCRT-ALL-C4T13ACCRT-ALL-C5T13ACCRT-ALL-C6T13ACCRT-ALL-C7T13ACCRT-ALL-C8T13ACCRT-ALL-C9T13BCCRT-ALL-C10T13BCCRT-ALL-C11T13BCCRT-ALL-C12T13BCCRT-ALL-C13T13BCCRT-ALL-C14T13BCCRT-ALL-C15T13BCCRT-ALL-C16T13BCCRT-ALL-C17T13BCCRT-ALL-C18T13BCCRT-ALL-C19T13BCCRT-ALL-C20T13BCCRT-ALL-C21T13BCCRT-ALL-C22T13BCCRT-ALL-C23T13BCCRT-ALL-C24T13BCCRT-ALL-C25T13BCCRT-ALL-C26T13BCCRT-ALL-R1T13AHemeRelapseT-ALL-R2T13BHemeRelapseT-ALL-R3T13BHemeRelapseT-ALL-R4T13BHemeRelapseT-ALL-R5T13BHemeRelapseT-ALL-R6T13BHemeRelapseT-ALL-2M#1T13B2nd AMLT-ALL-#1T13BOtherRelapseT-ALL-#2T13BOtherRelapseT-ALL-#4T13BCensoredT-ALL-#5T13BCensoredT-ALL-#6T15NAT-ALL-#7T15NAT-ALL-#8T15NAT-ALL-#9T15NAT-ALL-#10T15NAT-ALL-#11T15NATEL-AML1 subgroup (n = 79)TEL-AML1-C1T13ACCRTEL-AML1-C2T13ACCRTEL-AML1-C3T13ACCRTEL-AML1-C4T13ACCRTEL-AML1-C5T13ACCRTEL-AML1-C6T13ACCRTEL-AML1-C7T13ACCRTEL-AML1-C8T13ACCRTEL-AML1-C9T13ACCRTEL-AML1-C10T13ACCRTEL-AML1-C11T13ACCRTEL-AML1-C12T13ACCRTEL-AML1-C13T13ACCRTEL-AML1-C14T13ACCRTEL-AML1-C15T13ACCRTEL-AML1-C16T13ACCRTEL-AML1-C17T13ACCRTEL-AML1-C18T13ACCRTEL-AML1-C19T13ACCRTEL-AML1-C20T13ACCRTEL-AML1-C21T13ACCRTEL-AML1-C22T13ACCRTEL-AML1-C23T13ACCRTEL-AML1-C24T13ACCRTEL-AML1-C25T13ACCRTEL-AML1-C26T13ACCRTEL-AML1-C27T13ACCRTEL-AML1-C28T13ACCRTEL-AML1-C29T13BCCRTEL-AML1-C30T13BCCRTEL-AML1-C31T13BCCRTEL-AML1-C32T13BCCRTEL-AML1-C33T13BCCRTEL-AML1-C34T13BCCRTEL-AML1-C35T13BCCRTEL-AML1-C36T13BCCRTEL-AML1-C37T13BCCRTEL-AML1-C38T13BCCRTEL-AML1-C39T13BCCRTEL-AML1-C40T13BCCRTEL-AML1-C41T13BCCRTEL-AML1-C42T13BCCRTEL-AML1-C43T13BCCRTEL-AML1-C44T13BCCRTEL-AML1-C45T13BCCRTEL-AML1-C46T13BCCRTEL-AML1-C47T13BCCRTEL-AML1-C48T13BCCRTEL-AML1-C49T13BCCRTEL-AML1-C50T13BCCRTEL-AML1-C51T13BCCRTEL-AML1-C52T13BCCRTEL-AML1-C53T13BCCRTEL-AML1-C54T13BCCRTEL-AML1-C55T13BCCRTEL-AML1-C56T13BCCRTEL-AML1-C57T13BCCRTEL-AML1-R1T13AHemeRelapseTEL-AML1-R2T13AHemeRelapseTEL-AML1-R3T13BHemeRelapseTEL-AML1-2M#1T13A2nd AMLTEL-AML1-2M#2T13A2nd AMLTEL-AML1-2M#3T13A2nd AMLTEL-AML1-2M#4T13B2nd AMLTEL-AML1-2M#5T13B2nd AMLTEL-AML1-#1T13BOtherRelapseTEL-AML1-#2T13ACensoredTEL-AML1-#3T13ACensoredTEL-AML1-#4T13BCensoredTEL-AML1-#5T15NATEL-AML1-#6T15NATEL-AML1-#7T15NATEL-AML1-#8T15NATEL-AML1-#9T15NATEL-AML1-#10T15NATEL-AML1-#11T15NATEL-AML1-#12T15NATEL-AML1-#13T15NATEL-AML1-#14T15NA@Label key-Subtype Name-C#Dx Sample of patient in CCRSubtype Name-R#Dx Sample of patient who developeda hematologic relapseSubtype Name-#Dx Sample used for subgroup classification onlySubtype Name-2M#Dx Sample of patient who later developed 2nd AMLSubtype Name-NDx Sample in novel group#Protocol-Protocol that patient was treated on%Outcome-CCRContinuous complete remissionHeme RelapseHematologic relapseOther RelapseExtramedullary relapse2nd AMLDiagnostic samples of patients who laterdeveloped 2nd AMLCensoredCensored due to BM transplant,treated off protocol, or died in CRNANot applicable, primarily because the patientwas not treatedon Total 13, and thus is excludedfrom the analysis used toidentify gene expression profilespredictive of outcome

[0106] H. Diagnostic Samples Used for Prediction of Prognosis

[0107] In addition to the 201 CCR and 27 Heme Relapse cases listed in Table 1, five additional relapse cases were also included in the prognostic analysis, giving a total of 233 cases for this analysis. These additional cases were not included in the subgroup prediction data set because they did not meet the established criteria for the reasons listed below.

2LabelProtocolCommentBCR-ABL-R4T13BDid not meet QC criteria because contained70% blastsMLL-R5T13APeripheral Blood Sample (90% blasts)Normal-R4-T13BMolecular studies not performedT-ALL-R7T13APeripheral Blood Sample (90% blasts)T-ALL-R8T13BPeripheral Blood Sample (90% blasts)

[0108] I. Diagnostic Samples Used for Prediction of Secondary AML

[0109] In addition to the 201 CCR and 13 secondary AML cases listed in Table 1, three additional diagnostic marrow samples from patients who developed secondary AML were also included in the prognostic analysis. This gives a total of 217 cases used for this analysis. These additional cases were not included in the diagnostic data set because they did not meet the established criteria for the reasons listed below.

3LabelProtocolCommentHyperdip > 50-2M#3T12Non Total 13 diagnostic sampleHypodip-2M#2T13BNo molecular studies performedHypodip-2M#3T12Non Total 13 diagnostic sample

[0110] Relapsed Samples (n=25) p Twenty-five relapse samples were analyzed, 17 samples which were paired to the diagnostic samples listed above (Subtype Name-2M#), and 8 additional non-paired relapse samples.

[0111] Detailed Analysis

[0112] A. Hierarchical Cluster Analysis of Diagnostic Cases Using All Genes that Passed the Variation Filter

[0113] Two-dimensional hierarchical clustering was performed using Pearson correlation coefficient and an unweighted pair group method using arithmetic averages (GeneMaths, version 1.5). The results of hierarchical clustering of the 327 diagnostic samples using the 10,991 probe sets that passed the variation filter can be viewed at our web site, www.stjuderesearch.org/ALL1.

[0114] B. Methods for Gene Selection

[0115] Discriminating genes for the various leukemia subtypes were selected using a variety of statistical metrics. The individual metrics used and the list of selected probe sets and corresponding genes are given below.

[0116] 1. Chi-Square

[0117] The Chi square method evaluates each gene individually by measuring the Chi square statistics with respect to the classes. The method first discretizes the observed expression values of the gene into several intervals using an entropy-based discretization methodi. The Chi square statistics of a gene is then calculated as X2=ΣΣ(Aij−Eij)2/Eij, summing over intervals i=1..m and classes j =1..k. Aij is the number of samples in the ith interval that are of the jth class. Eij is the expected frequency of Aij and is calculated as Eij=Ri* Ci/N, where Ri is the number of samples in the ith interval, Cj is the number of samples in the jth class, and N is the total number of samples. The genes are then sorted according to their Chi square statistics: the larger the Chi square statistics, the more important the gene. The 40 genes with the highest Chi square statistics in each subtype are listed in Tables 2-8. Generally, using anywhere from the top 20 to 40 genes did not result in significant differences in subtype prediction accuracy. Therefore, only the top 20 genes in subtype prediction were used, unless noted otherwise.

4TABLE 2Genes selected by Chi square: BCR-ABLChiAbove/AffymetrixReferencesquareBelownumberGene NameGeneSymbolnumbervalueMean11637_atmitogen-activated protein kinase-MAPKAPK3U0957862.75Aboveactivated protein kinase 3236650_atcyclin D2CCND2D1363959.79Above340196_atHYA22 proteinHYA22D8815354.79Above41635_atproto-oncogene tyrosine-proteinABLU0756354.77Abovekinase ABL gene533775_s_atcaspase 8 apoptosis-relatedCASP8X9817649.70Abovecysteine protease61636_g_atproto-oncogene tyrosine-proteinABLU0756348.29Abovekinase ABL gene741295_atGTT1 proteinGTT1AL04178042.60Above837600_atextracellular matrix protein 1ECM1U6818642.60Above937012_atcapping protein actin filamentCAPZBU0327138.46Abovemuscle Z-line beta1039225_atalkylglycerone phosphate synthaseAGPSY0944338.46Above111326_atcaspase 10 apoptosis-relatedCASP10U6051937.83Abovecysteine protease1234362_atsolute carrier family 2 facilitatedSLC2A5M5553137.54Aboveglucose transporter member 51333150_atdisrupter of silencing 10SAS10AI12600436.95Above1440051_atTRAM-like proteinKIAA0057D3176236.95Above1539061_atbone marrow stromal cell antigen 2BST2D2813736.95Above1633172_athypothetical protein FLJ10849FLJ10849T7529236.95Above1737399_ataldo-keto reductase family 1AKR1C3D1779336.95Abovemember C3 3-alphahydroxysteroid dehydrogenasetype II18317_atprotease cysteine 1 legumainPRSC1D5569636.95Above1940953_atcalponin 3 acidicCNN3S8056233.94Above20330_s_attubulin, alpha 1, isoform 44TUBA1HG2259-33.32AboveHT23482140504_atparaoxonase 2PON2AF00160131.46Above2238578_attumor necrosis factor receptorTNFRSF7M6392830.47Abovesuperfamily member 72339044_s_atdiacylglycerol kinase delta 130 kDDGKDD7340929.59Below2436634_atBTG family member 2BTG2U7264929.16Below2538119_atglycophorin C Gerbich bloodGYPCX1249629.16Abovegroup2632562_atendoglin Osler-Rendu-WeberENGX7201227.96Abovesyndrome 12733228_g_atinterleukin 10 receptor betaIL10RBAI98423427.70Below2837006_atstep II splicing factor SLU7SLU7AI66065627.15Above2938641_atHomo sapiens mRNA for TSC-22-AJ13311527.15Abovelike protein3038220_atdihydropyrimidine dehydrogenaseDPYDU2093827.15Above311211_s_atCASP2 and RIPK1 domainCRADDU8438826.46Abovecontaining adaptor with deathdomain3239730_atv-abl Abelson murine leukemiaABL1X1641625.90Aboveviral oncogene homolog 13336591_attubulin alpha 1 testis specificTUBA1X0695625.90Above3436035_atanchor attachment protein 1 Gaa1pGPAA1AB00213525.34Aboveyeast homolog35980_atNiemann-Pick disease type C1NPC1AF00202025.29Above36671_atsecreted protein acidic cysteine-SPARCJ0304025.29Aboverich osteonectin3740698_atC-type calcium dependentCLECSF2X9671923.80Abovecarbohydrate-recognition domainlectin superfamily member 2activation-induced3839330_s_atactinin alpha 1ACTN1M9517823.70Above391983_atcyclin D2CCND2X6845223.70Above402001_g_atataxia telangiectasia mutatedATMU2645522.60Above

[0118]

5

TABLE 3

Genes selected by Chi Square for E2A-PBX1

Chi
Above/

Affymetrix

Reference
square
Below

number
Gene Name
GeneSymbol
number
value
Mean

1
41146_at
ADP-ribosyltransferase NAD poly
ADPRT
J03473
187.00
Above

ADP-ribose polymerase

2
1287_at
ADP-ribosyltransferase NAD poly
ADPRT
J03473
187.00
Above

ADP-ribose polymerase

3
32063_at
pre-B-cell leukemia transcription
PBX1
M86546
187.00
Above

factor 1

4
33355_at

Homo sapiens
cDNA FLJ12900
PBX1
AL049381
187.00
Above

fis clone NT2RP2004321 (by

CELERA serach of target

sequence = PBX1)

5
430_at
nucleoside phosphorylase
NP
X00737
187.00
Above

6
40454_at
FAT tumor suppressor Drosophila
FAT
X87241
176.11
Above

homolog

7
753_at
nidogen 2
NID2
D86425
164.28
Above

8
33821_at
Human DNA sequence from clone
HELO1
AL034374
155.00
Above

RP3-483K16 on chromosome

6p12.1-21.1

9
39614_at
KIAA0802 protein
KIAA0802
AB018345
153.46
Above

10
38340_at
huntingtin interacting protein-1-
KIAA0655
AB014555
143.85
Above

related

11
1786_at
c-mer proto-oncogene tyrosine
MERTK
U08023
142.34
Above

kinase

12
39929_at
KIAA0922 protein
KIAA0922
AB023139
139.97
Above

13
39379_at

Homo sapiens
mRNA cDNA

AL049397
139.49
Above

DKFZp586C1019 from clone

DKFZp586C1019

14
717_at
GS3955 protein
GS3955
D87119
135.24
Above

15
362_at
protein kinase C zeta
PRKCZ
Z15108
131.36
Above

16
33513_at
signaling lymphocytic activation
SLAM
U33017
131.36
Above

molecule

17
37225_at
KIAA0172 protein
KIAA0172
D79994
131.36
Above

18
854_at
B lymphoid tyrosine kinase
BLK
S76617
130.95
Above

19
35974_at
lymphoid-restricted membrane
LRMP
U10485
123.33
Above

protein

20
36452_at
synaptopodin
KIAA1029
AB028952
123.33
Above

21
40648_at
c-mer proto-oncogene tyrosine
MERTK
U08023
120.51
Above

kinase

22
38393_at
KIAA0247 gene product
KIAA0247
D87434
120.51
Above

23
38994_at
STAT induced STAT inhibitor-2
STATI2
AF037989
118.58
Below

24
34861_at
golgi autoantigen golgin subfamily
GOLGA3
D63997
116.80
Above

a 3

25
38748_at
adenosine deaminase RNA-
ADARB1
U76421
114.13
Above

specific B1 homolog of rat RED1

26
40113_at
GS3955 protein
GS3955
D87119
114.13
Above

27
36179_at
mitogen-activated protein kinase-
MAPKAPK2
U12779
113.43
Above

activated protein kinase 2

28
37493_at
colony stimulating factor 2
CSF2RB
H04668
113.04
Above

receptor beta low-affinity

granulocyte-macrophage

29
578_at
Human recombination acitivating
RAG2
M94633
111.32
Above

protein (RAG2) gene

30
41017_at
myosin-binding protein H
MYBPH
U27266
109.73
Above

31
37625_at
interferon regulatory factor 4
IRF4
U52682
108.51
Above

32
38679_g_at
small nuclear ribonucleoprotein
SNRPE
AA733050
106.02
Above

polypeptide E

33
1389_at
membrane metallo-endopeptidase
MME
J03779
105.65
Below

neutral endopeptidase

enkephalinase CALLA CD10

34
34783_s_at
BUB3 budding uninhibited by
BUB3
AF047473
103.87
Above

benzimidazoles 3 yeast homolog

35
36959_at
ubiquitin-conjugating enzyme E2
UBE2V1
U49278
103.87
Above

variant 1

36
39864_at
cold inducible RNA-binding
CIRBP
D78134
99.76
Below

protein

37
41862_at
KIAA0056 protein
KIAA0056
D29954
99.76
Above

38
41425_at
Friend leukemia virus integration 1
FLI1
M98833
96.47
Above

39
37177_at
CD58 antigen lymphocyte
CD58
Y00636
93.84
Above

function-associated antigen 3

40
37485_at
fatty-acid-Coenzyme A ligase very
FACVL1
D88308
93.17
Above

long-chain 1

[0119]

6

TABLE 4

Genes selected by Chi square for Hyperdiploid >50

Chi
Above/

Affymetrix

Reference
square
Below

number
Gene Name
GeneSymbol
number
value
Mean

1
36620_at
superoxide dismutase 1 soluble
SOD1
X02317
52.43
Above

amyotrophic lateral sclerosis 1

adult

2
37350_at
Human DNA sequence from clone
PSMD10
AL031177
48.71
Above

889N15 on chromosome Xq22.1-22.3.

3
171_at
von Hippel-Lindau binding protein 1
VBP1
U56833
45.80
Above

4
37677_at
phosphoglycerate kinase 1
PGK1
V00572
45.80
Above

5
41724_at
accessory proteins BAP31/BAP29
DXS1357E
X81109
45.58
Above

6
32207_at
membrane protein palmitoylated 1
MPP1
M64925
44.07
Above

55 kD

7
38738_at
SMT3 suppressor of mif two 3
SMT3H1
X99584
43.57
Above

yeast homolog 1

8
40480_s_at
FYN oncogene related to SRC
FYN
M14333
43.57
Above

FGR YES

9
38518_at
sex comb on midleg Drosophila
SCML2
Y18004
43.20
Above

like 2

10
41132_r_at
heterogeneous nuclear
HNRPH2
U01923
43.15
Above

ribonucleoprotein H2 H

11
31492_at
muscle specific gene
M9
AB019392
43.01
Below

12
38317_at
transcription elongation factor A
TCEAL1
M99701
41.10
Above

SII like 1

13
40998_at
trinucleotide repeat containing 11
TNRC11
AF071309
40.88
Above

THR-associated protein 230 kDa

subunit

14
35688_g_at
mature T-cell proliferation 1
MTCP1
Z24459
40.52
Above

15
40903_at
ATPase H transporting lysosomal
APT6M8-9
AL049929
40.33
Above

vacuolar proton pump membrane

sector associated protein M8-9

16
36489_at
phosphoribosyl pyrophosphate
PRPS1
D00860
40.33
Above

synthetase 1

17
1520_s_at
interleukin 1 beta
IL1B
X04500
40.29
Above

18
35939_s_at
POU domain class 4 transcription
POU4F1
L20433
38.74
Above

factor 1

19
38604_at
neuropeptide Y
NPY
AI198311
38.26
Above

20
31863_at
KIAA0179 protein
KIAA0179
D80001
38.26
Above

21
890_at
ubiquitin-conjugating enzyme
UBE2A
M74524
37.99
Above

E2A RAD6 homolog

22
39402_at
interleukin 1 beta
IL1B
M15330
37.92
Above

23
41490_at
phosphoribosyl pyrophosphate
PRPS2
Y00971
37.72
Above

synthetase 2

24
34753_at
synaptobrevin-like 1
SYBL1
X92396
37.72
Above

25
40891_f_at
DNA segment on chromosome X
DXS9879E
X92896
37.15
Above

unique 9879 expressed sequence

26
306_s_at
high-mobility group nonhistone
HMG14
J02621
37.15
Above

chromosomal protein 14

27
37640_at
hypoxanthine
HPRT1
M31642
37.15
Above

phosphoribosyltransferase 1

Lesch-Nyhan syndrome

28
34829_at
dyskeratosis congenita 1 dyskerin
DKC1
U59151
36.48
Above

29
36169_at
NADH dehydrogenase ubiquinone
NDUFA1
N47307
36.48
Above

1 alpha subcomplex 1 7.5 kD

MWFE

30
38968_at
SH3-domain binding protein 5
SH3BP5
AB005047
35.95
Above

BTK-associated

31
36128_at
transmembrane trafficking protein
TMP21
L40397
35.88
Above

32
37014_at
myxovirus influenza resistance 1
MX1
M33882
35.65
Above

homolog of murine interferon-

inducible protein p78

33
34374_g_at
upstream regulatory element
UREB1
Z97054
35.55
Above

binding protein 1

34
36542_at
solute carrier family 9
SLC9A6
AF030409
35.55
Above

sodium/hydrogen exchanger

isoform 6

35
688_at
proteasome prosome macropain
PSMC1
L02426
35.55
Above

26S subunit ATPase 1

36
955_at
calmodulin type I

HG1862-
35.55
Above

HT1897

37
35816_at
cystatin B stefin B
CSTB
U46692
35.27
Above

38
38459_g_at
Human cytochrome b5 (CYB5)
CYB5
L39945
35.18
Above

gene

39
41288_at
matrix Gla protein
MGP
AL036744
35.18
Above

40
32251_at
hypothetical protein FLJ21174
FLJ21174
AA149307
35.14
Above

[0120]

7

TABLE 5

Genes selected by Chi square for MLL

Chi
Above/

Affymetrix

Reference
square
Below

number
Gene Name
GeneSymbol
number
value
Mean

1
34306_at
muscleblind Drosophila like
MBNL
AB007888
64.07
Above

2
40797_at
a disintegrin and
ADAM10
AF009615
62.85
Above

metalloproteinase domain 10

3
33412_at
LGALS1 Lectin, galactoside-
LGALS1
AI535946
57.97
Above

binding, soluble, 1

4
39338_at
S100 calcium-binding protein
S100A10
AI201310
57.97
Above

A10 annexin II ligand calpactin

I light polypeptide p11

5
2062_at
insulin-like growth factor
IGFBP7
L19182
55.22
Above

binding protein 7

6
32193_at
plexin C1
PLXNC1
AF030339
53.59
Above

7
40518_at
protein tyrosine phosphatase
PTPRC
Y00062
53.40
Above

receptor type C

8
36777_at
DNA segment on chromosome
D12S2489E
AJ001687
51.47
Above

12 unique 2489 expressed

sequence

9
32207_at
membrane protein palmitoylated
MPP1
M64925
50.73
Below

1 55 kD

10
33859_at
sin3-associated polypeptide
SAP18
U96915
50.48
Above

18 kD

11
38391_at
capping protein actin filament
CAPG
M94345
50.26
Above

gelsolin-like

12
40763_at
Meis1 mouse homolog
MEIS1
U85707
50.26
Above

13
1126_s_at
cell surface glycoprotein CD44
CD44
L05424
50.17
Above

gene

14
34721_at
FK506-binding protein 5
FKBP5
U42031
50.17
Above

15
37809_at
homeo box A9
HOXA9
U41813
50.17
Above

16
34861_at
golgi autoantigen golgin
GOLGA3
D63997
47.58
Below

subfamily a 3

17
38194_s_at
immunoglobulin kappa constant
IGKC
M63438
46.18
Below

18
657_at
protocadherin gamma subfamily
PCDHGC3
L11373
46.05
Above

C 3

19
36918_at
guanylate cyclase 1 soluble
GUCY1A3
Y15723
43.90
Above

alpha 3

20
32215_i_at
KIAA0878 protein
KIAA0878
AB020685
43.90
Above

21
38160_at
lymphocyte antigen 75
LY75
AF011333
43.90
Above

22
38413_at
defender against cell death 1
DAD1
D15057
43.90
Above

23
1389_at
membrane metallo-
MME
J03779
43.82
Below

endopeptidase neutral

endopeptidase enkephalinase

CALLA CD10

24
34168_at
deoxynucleotidyltransferase
DNTT
M11722
43.82
Below

terminal

25
2036_s_at
CD44 antigen homing function
CD44
M59040
42.55
Above

and Indian blood group system

26
40522_at
glutamate-ammonia ligase
GLUL
X59834
42.55
Above

glutamine synthase

27
854_at
B lymphoid tyrosine kinase
BLK
S76617
42.34
Above

28
40067_at
E74-like factor 1 ets domain
ELF1
M82882
40.85
Above

transcription factor

29
39756_g_at
X-box binding protein 1
XBP1
Z93930
39.95
Below

30
36940_at
TGFB1-induced anti-apoptotic
TIAF1
D86970
39.82
Below

factor 1

31
36935_at
RAS p21 protein activator
RASA1
M23379
38.77
Above

GTPase activating protein 1

32
32134_at
testin
DKFZP586
AL050162
38.77
Above

B2022

33
39379_at

Homo sapiens
mRNA cDNA

AL049397
38.77
Above

DKFZp586C1019 from clone

DKFZp586C1019

34
40493_at
Human cell surface glycoprotein
CD44
L05424
38.44
Above

CD44

35
769_s_at
annexin A2
ANXA2
D00017
37.61
Above

36
40415_at
acetyl-Coenzyme A
ACAA1
X14813
37.55
Above

acyltransferase 1 peroxisomal 3-

oxoacyl-Coenzyme A thiolase

37
35983_at
hypothetical protein R32184_1
R32184_1
AC004528
37.55
Above

38
40519_at
protein tyrosine phosphatase
PTPRC
Y00638
36.56
Above

receptor type C

39
794_at
protein tyrosine phosphatase
PTPN6
X62055
36.56
Above

non-receptor type 6

40
41234_at
DnaJ Hsp40 homolog subfamily
DNAJB6
AI540318
36.56
Above

B member 6

[0121]

8

TABLE 6

Genes selected by Chi square for Novel risk group

Chi
Above/

Affymetrix

Reference
square
Below

number
Gene Name
GeneSymbol
number
value
Mean

1
37960_at
carbohydrate chondroitin
CHST2
AB014679
175.82
Above

6/keratan sulfotransferase 2

2
31892_at
protein tyrosine phosphatase
PTPRM
X58288
172.85
Above

receptor type M

3
994_at
protein tyrosine phosphatase
PTPRM
X58288
172.85
Above

receptor type M

4
995_g_at
protein tyrosine phosphatase
PTPRM
X58288
172.85
Above

receptor type M

5
41074_at
G protein-coupled receptor 49
GPR49
AF062006
139.36
Above

6
41073_at
G protein-coupled receptor 49
GPR49
AI743745
139.36
Above

7
34676_at
KIAA1099 protein
KIAA1099
AB029022
137.71
Above

8
36139_at
DKFZP586G0522 protein
DKFZP586G0522
AL050289
127.05
Above

9
37542_at
lipoma HMGIC fusion partner-
LHFPL2
D86961
120.79
Above

like 2

10
41159_at
clathrin heavy polypeptide Hc
CLTC
D21260
115.15
Above

11
40081_at
phospholipid transfer protein
PLTP
L26232
108.33
Above

12
32800_at
Human retinoid X receptor
RXR
U66306
107.39
Above

alpha mRNA, 3′ UTR, partial

sequence

13
36906_at
cannabinoid receptor 1 brain
CNR1
U73304
107.39
Above

14
39878_at
protocadherin 9
PCDH9
AI524125
99.20
Above

15
41747_s_at
Human myocyte-specific
MEF2A
U49020
99.20
Above

enhancer factor 2A (MEF2A)

gene, last coding exon, and

complete cds.

16
33410_at
integrin alpha 6
ITGA6
S66213
96.17
Above

17
34947_at
phorbolin-like protein MDS019
MDS019
AA442560
93.59
Above

18
36029_at
chromosome 11 open reading
C11ORF8
U57911
93.59
Above

frame 8

19
41708_at
KIAA1034 protein
KIAA1034
AB028957
92.60
Above

20
1664_at
insulin-like growth factor 2
IGF2
HG3543-
92.60
Above

HT3739

21
32736_at
HSPC022 protein
HSPC022
W68830
91.62
Below

22
41266_at
integrin alpha 6
ITGA6
X53586
86.95
Above

23
36566_at
cystinosis nephropathic
CTNS
AJ222967
82.89
Above

24
1825_at
IQ motif containing GTPase
IQGAP1
L33075
81.20
Below

activating protein 1

25
1731_at
platelet-derived growth factor
PDGFRA
M21574
78.22
Above

receptor alpha polypeptide

26
37023_at
lymphocyte cytosolic protein 1
LCP1
J02923
78.22
Below

L-plastin

27
33037_at
carbohydrate N-
CHST7
AL022165
76.00
Above

acetylglucosamine 6-O

sulfotransferase 7

28
33411_g_at
integrin alpha 6
ITGA6
S66213
75.47
Above

29
538_at
CD34 antigen
CD34
S53911
74.86
Above

30
39108_at
lanosterol synthase 2 3-
LSS
U22526
71.90
Above

oxidosqualene-lanosterol

cyclase

31
38364_at
BCE-1 protein
BCE-1
AF068197
71.90
Above

32
40423_at
KIAA0903 protein
KIAA0903
AB020710
71.29
Above

33
35192_at
glycine dehydrogenase
GLDC
D90239
71.29
Above

decarboxylating glycine

decarboxylase glycine cleavage

system protein P

34
39037_at
myeloid/lymphoid or mixed-
MLLT2
L13773
71.29
Above

lineage leukemia trithorax

Drosophila homolog

translocated to 2

35
38747_at
Human CD34 gene, exon 8.
CD34
M81945
69.45
Above

36
37687_i_at
Fc fragment of IgG low affinity
FCGR2A
M31932
67.75
Above

IIa receptor for CD32

37
1857_at
MAD mothers against
MADH7
AF010193
66.28
Above

decapentaplegic Drosophila

homolog 7

38
38618_at
Human PAC clone RP3-515N1
LIMK2
AC002073
64.03
Above

from 22q11.2-q22

39
31782_at
prostaglandin D2 receptor DP
PTGDR
U31099
61.92
Above

40
32842_at
B-cell CLL/lymphoma 7A
BCL7A
X89984
61.57
Above

[0122]

9

TABLE 7

Genes selected for Chi square for T-ALL

Chi
Above/

Affymetrix

Reference
square
Below

number
Gene Name
GeneSymbol
number
value
Mean

1
38319_at
CD3D antigen delta polypeptide
CD3D
AA919102
215.00
Above

TiT3 complex

2
1096_g_at
CD19 antigen
CD19
M28170
206.48
Below

3
38242_at
B cell linker protein
SLP65
AF068180
198.52
Below

4
32794_g_at
T cell receptor beta locus
TRB
X00437
197.71
Above

5
37988_at
CD79B antigen
CD79B
M89957
197.71
Below

immunoglobulin-associated beta

6
38017_at
CD79A antigen
CD79A
U05259
197.53
Below

immunoglobulin-associated

alpha

7
35016_at
Human Ia-associated invariant
M13560
M13560

Below

gamma-chain gene, exon 8,

clones lambda-y(1,2,3).

8
36277_at
Human membran protein (CD3-
CD3E
M23323
197.53
Above

epsilon) gene, exon 9.

9
38095_i_at
major histocompatibility
HLA-DPB1
M83664
191.09
Below

complex class II DP beta 1

10
39318_at
T-cell leukemia/lymphoma 1A
TCL1A
X82240
189.78
Below

11
38147_at
SH2 domain protein 1A Duncans
SH2D1A
AL023657
189.78
Above

disease lymphoproliferative

syndrome

12
41723_s_at
major histocompatibility
HLA-DRB1
M32578
189.25
Below

complex class II DR beta 1

13
38833_at
Human mRNA for SB classII

X00457
189.03
Below

histocompatibility antigen

alpha-chain

14
33238_at
Human T-lymphocyte specific
lck
U23852
189.03
Above

protein tyrosine kinase p56lck

(lck) abberant mRNA

15
37039_at
major histocompatibility
HLA-DRA
J00194
188.93
Below

complex class II DR alpha

16
38051_at
mal T-cell differentiation protein
MAL
X76220
188.93
Above

17
37344_at
major histocompatibility
HLA-DMA
X62744
187.25
Below

complex class II DM alpha

18
38096_f_at
major histocompatibility
HLA-DPB1
M83664
182.38
Below

complex class II DP beta 1

19
2059_s_at
lymphocyte-specific protein
LCK
M36881
182.38
Above

tyrosine kinase

20
1105_s_at
T cell receptor beta locus
TRB
M12886
180.45
Above

21
32649_at
transcription factor 7 T-cell
TCF7
X59871
177.84
Above

specific HMG-box

22
38949_at
protein kinase C theta
PRKCQ
L01087
172.59
Below

23
39709_at
selenoprotein W 1
SEPW1
U67171
171.96
Above

24
41165_g_at
immunoglobulin heavy constant
IGHM
X67301
171.96
Below

mu

25
36473_at
ubiquitin specific protease 20
USP20
AB023220
167.27
Above

26
266_s_at
CD24 antigen small cell lung
CD24
L33930
165.56
Below

carcinoma cluster 4 antigen

27
40570_at
forkhead box O1A
FOXO1A
AF032885
165.29
Below

rhabdomyosarcoma

28
40775_at
integral membrane protein 2A
ITM2A
AL021786
164.14
Above

29
37420_i_at
Human DNA sequence from

AL022723
164.14
Below

clone RP3-377H14 on

chromosome 6p21.32-22.1.

30
1085_s_at
phospholipase C gamma 2
PLCG2
M37238
161.30
Below

phosphatidylinositol-specific

31
38018_g_at
CD79A antigen
CD79A
U05259
160.51
Below

immunoglobulin-associated

alpha

32
35643_at
nucleobindin 2
NUCB2
X76732
160.07
Above

33
41166_at
immunoglobulin heavy constant
IGHM
X58529
158.50
Below

mu

34
38415_at
protein tyrosine phosphatase
PTP4A2
U14603
155.78
Above

type IVA member 2

35
38893_at
neutrophil cytosolic factor 4
NCF4
AL008637
155.78
Below

40 kD

36
1241_at
protein tyrosine phosphatase
PTP4A2
U14603
155.78
Above

type IVA member 2

37
32793_at
T cell receptor beta locus
TRB
X00437
155.43
Above

38
36571_at
topoisomerase DNA II beta
TOP2B
X68060
152.16
Below

180 kD

39
37399_at
aldo-keto reductase family 1
AKR1C3
D17793
151.93
Above

member C3 3-alpha

hydroxysteroid dehydrogenase

type II

40
41097_at
telomeric repeat binding factor 2
TERF2
AF002999
151.86
Below

[0123]

10

TABLE 8

Genes selected by Chi square for TEL-AML1

Chi
Above/

Affymetrix

Reference
square
Below

number
Gene Name
GeneSymbol
number
value
Mean

1
38652_at
hypothetical protein FLJ20154
FLJ20154
AF070644
137.92
Above

2
36239_at
POU domain class 2 associating
POU2AF1
Z49194
131.43
Above

factor 1

3
41442_at
core-binding factor runt domain
CBFA2T3
AB010419
130.17
Above

alpha subunit 2 translocated to 3

4
37780_at
piccolo presynaptic cytomatrix
PCLO
AB011131
126.79
Above

protein

5
36985_at
isopentenyl-diphosphate delta
IDI1
X17025
125.47
Above

isomerase

6
38578_at
tumor necrosis factor receptor
TNFRSF7
M63928
115.72
Above

superfamily member 7

7
38203_at
potassium intermediate/small
KCNN1
U69883
112.87
Above

conductance calcium-activated

channel subfamily N member 1

8
35614_at
transcription factor-like 5 basic
TCFL5
AB012124
108.45
Above

helix-loop-helix

9
32224_at
KIAA0769 gene product
KIAA0769
AB018312
107.08
Above

10
32730_at

Homo sapiens
mRNA for

AL080059
104.93
Above

KIAA1750 protein partial cds

11
35665_at
phosphoinositide-3-kinase class 3
PIK3C3
Z46973
104.83
Above

12
1077_at
recombination activating gene 1
RAG1
M29474
102.90
Above

13
36524_at
Rho guanine nucleotide
ARHGEF4
AB029035
100.67
Above

exchange factor GEF 4

14
34194_at

Homo sapiens
cDNA FLJ21697

AL049313
98.31
Above

fis clone COL09740

15
36937_s_at
PDZ and LIM domain 1 elfin
PDLIM1
U90878
96.91
Below

16
36008_at
protein tyrosine phosphatase
PTP4A3
AF041434
96.68
Above

type IVA member 3

17
1299_at
telomeric repeat binding factor 2
TERF2
X93512
93.08
Above

18
41814_at
fucosidase alpha-L-1 tissue
FUCA1
M29877
92.77
Above

19
41200_at
CD36 antigen collagen type I
CD36L1
Z22555
90.86
Above

receptor thrombospondin

receptor like 1

20
35238_at
TNF receptor-associated factor 5
TRAF5
AB000509
90.81
Above

21
880_at
FK506-binding protein 1A 12 kD
FKBP1A
M34539
86.69
Above

22
33690_at

Homo sapiens
mRNA cDNA

AL080190
86.69
Above

DKFZp434A202 from clone

DKFZp434A202

23
40272_at
collapsin response mediator
CRMP1
D78012
85.44
Above

protein 1

24
35362_at
myosin X
MYO10
AB018342
83.60
Above

25
41819_at
FYN-binding protein FYB-
FYB
U93049
83.25
Above

120/130

26
40279_at
KIAA0121 gene product
KIAA0121
D50911
81.66
Above

27
1488_at
protein tyrosine phosphatase
PTPRK
L77886
81.66
Above

receptor type K

28
1325_at
MAD mothers against
MADH1
U59423
81.17
Above

decapentaplegic Drosophila

homolog 1

29
37908_at
guanine nucleotide binding
GNG11
U31384
80.37
Above

protein 11

30
769_s_at
annexin A2
ANXA2
D00017
78.68
Below

31
33415_at
non-metastatic cells 2 protein
NME2
X58965
77.04
Below

NM23B expressed in

32
1980_s_at
non-metastatic cells 2 protein
NME2
X58965
76.35
Below

NM23B expressed in

33
32579_at
SWI/SNF related matrix
SMARCA4
D26156
76.35
Above

associated actin dependent

regulator of chromatin

subfamily a member 4

34
39425_at
thioredoxin reductase 1
TXNRD1
X91247
75.97
Above

35
755_at
inositol 1 4 5-triphosphate
ITPR1
D26070
75.56
Above

receptor type 1

36
37343_at
inositol 1 4 5-triphosphate
ITPR3
U01062
75.11
Above

receptor type 3

37
1336_s at
protein kinase C beta 1
PRKCB1
X06318
73.96
Above

38
41097_at
telomeric repeat binding factor 2
TERF2
AF002999
73.84
Above

39
31786_at
Sam68-like phosphotyrosine
T-STAR
AF051321
73.72
Above

protein T-STAR

40
160029_at
protein kinase C beta 1
PRKCB1
X07109
73.66
Above

[0124] 2. Correlation-based Feature Selection (CFS)

[0125] The Correlation-based Feature Selection (CFS) is a method that evaluates subsets of genes rather than individual genes. (Hall and Holmes (2000),“Benchmarking Attribute Selection Techniques for Data Mining,” Working Paper 00/10, Department of Computer Science, University of Waikato, New Zealand). The core of the algorithm is a subset evaluation heuristic that takes into account the usefulness of individual features for predicting the class along with the level of intercorrelation among them with the belief that “good feature subsets contain features highly correlated with the class, yet uncorrelated with each other”. The heuristic assigns a score Merits to a subset S containing k genes, defined as Merits=(k*rcf)/sqrt(k+k*(k−1)*rff), where rcf is the average gene-class correlation and rff is the average gene-gene correlation. Like the Chi square method, CFS first discretizes the gene expressions into intervals and then calculates a matrix of gene-class and gene-gene correlations from the training data for merit calculation. The correlation between two genes or a gene and a class is calculated as rxy=2*[H(X)+H(Y)−H(X,Y)]/[H(X)+H(Y)], where H(X) is the entropy of a gene X. CFS starts from an empty set of genes and uses the best-first search technique with a stopping criterion of 5 consecutive fully expanded non-improving subsets. The subset with the highest merit found during the search is selected. Tables 9-15 list the top gene subsets chosen by CFS for each subtype. For subtype prediction, each gene subset must be used in its entirety, as within each subset, all genes are equally ranked.

11TABLE 9Genes selected by CFS: BCR-ABLAbove/AffymetrixReferenceBelownumberGene NameGeneSymbolnumberMean136650_atcyclin D2CCND2D13639Above240196_atHYA22 proteinHYA22D88153Above31635_atproto-oncogene tyrosine-proteinABLU07563Abovekinase (ABL) gene433775_s_atcaspase 8 apoptosis-related cysteineCASP8X98176Aboveprotease51636_g_atproto-oncogene tyrosine-proteinABLU07563Abovekinase (ABL) gene641295_atGTT1 proteinGTT1AL041780Above71326_atcaspase 10 apoptosis-related cysteineCASP10U60519Aboveprotease833150_atdisrupter of silencing 10SAS10AI126004Above940051_atTRAM-like proteinKIAA0057D31762Above1039061_atbone marrow stromal cell antigen 2BST2D28137Above1133172_athypothetical protein FLJ10849FLJ10849T75292Above1237399_ataldo-keto reductase family 1 memberAKR1C3D17793AboveC3 3-alpha hydroxysteroiddehydrogenase type II13317_atprotease cysteine 1 legumainPRSC1D55696Above14330_s_attubulin, alpha 1, isoform 44TUBA1HG2259-AboveHT23481538578_attumor necrosis factor receptorTNFRSF7M63928Abovesuperfamily member 71639044_s_atdiacylglycerol kinase delta 130 kDDGKDD73409Below1732562_atendoglin Osler-Rendu-WeberENGX72012Abovesyndrome 11838641_atHomo sapiens mRNA for TSC-22-AJ133115Abovelike protein191211_s_atCASP2 and RIPK1 domain containingCRADDU84388Aboveadaptor with death domain2039730_atv-abl Abelson murine leukemia viralABL1X16416Aboveoncogene homolog 12136591_attubulin alpha 1 testis specificTUBA1X06956Above2236035_atanchor attachment protein 1 Gaa1pGPAA1AB002135Aboveyeast homolog23980_atNiemann-Pick disease type C1NPC1AF002020Above2440698_atC-type calcium dependentCLECSF2X96719Abovecarbohydrate-recognition domainlectin superfamily member 2activation-induced2539330_s_atactinin alpha 1ACTN1M95178Above262001_g_atataxia telangiectasia mutated includesATMU26455Abovecomplementation groups A C and D2739319_atlymphocyte cytosolic protein 2 SH2LCP2U20158Abovedomain-containing leukocyte proteinof 76 kD2837685_atClathrin assembly lymphoid-myeloidCLTHU45976Aboveleukemia gene2933813_attumor necrosis factor receptorTNFRSF1BAI813532Abovesuperfamily member 1B3033134_atadenylate cyclase 3ADCY3AB011083Above3136536_atschwannomin interacting protein 1SCHIP-1AF070614Above3236985_atisopentenyl-diphosphate deltaIDI1X17025Belowisomerase3335991_atSm protein FLSM6AA917945Above3433774_atcaspase 8 apoptosis-related cysteineCASP8X98172Aboveprotease3537470_atleukocyte-associated Ig-like receptor 1LAIR1AF013249Above3639245_atHuman 40871 mRNA partialU72507Abovesequence3740076_attumor protein D52-like 2TPD52L2AF004430Below3839370_atMicrotubule-associated proteins 1AMAP1ALC3W28807Belowand 1B light chain 33941594_atJanus kinase 1 a protein tyrosineJAK1M64174Abovekinase4041338_atamino-terminal enhancer of splitAESAI969192Below4132319_attumor necrosis factor ligandTNFSF4AL022310Abovesuperfamily member 4 tax-transcriptionally activatedglycoprotein 1 34 kD4233924_atKIAA1091 proteinKIAA1091AB029014Above4337397_atplatelet/endothelial cell adhesionPECAML34657Abovemolecule-1 (PECAM-1) gene4437190_atWAS protein family member 1WASF1D87459Below4539070_atsinged Drosophila like sea urchinSNLU03057Abovefascin homolog like4638994_atSTAT induced STAT inhibitor-2STATI2AF037989Above4732621_atdown-regulator of transcription 1DR1M97388AboveTBP-binding negative cofactor 24840108_atKIAA0005 gene productKIAA0005D13630Below4935238_atTNF receptor-associated factor 5TRAF5AB000509Above501558_g_atp21/Cdc42/Rac1-activated kinase 1PAK1U24152Aboveyeast Ste20-related511373_attranscription factor 3 E2ATCF3M31523Belowimmunoglobulin enhancer bindingfactors E12/E475235731_atintegrin alpha 4 antigen CD49D alphaITGA4X16983Above4 subunit of VLA-4 receptor5338659_atsuppressor of clear C. elegansSHOC2AB020669Belowhomolog of

[0126]

12

TABLE 10

Gene selected by CFS for E2A-PBX1

Above/

Affymetrix

Gene
Reference
Below

number
Gene Name
Symbol
number
Mean

1
33355_at

Homo sapiens

PBX1
AL049381
Above

cDNA FLJ12900

fis clone NT2RP

2004321

(by CELERA

search of target

sequence = PBX1)

[0127]

13

TABLE 11

Genes selected by CFS for: Hyperdiploid >50

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
36620_at
superoxide dismutase 1 soluble
SOD1
X02317
Above

amyotrophic lateral sclerosis 1 adult

2
37350_at
clone 889N15 on chromosome
PSMD10
AL031177
Above

Xq22.1-22.3. Contains part of the

gene for a novel protein similar to X.

laevis
Cortical Thymocyte Marker

CTX

3
41724_at
accessory proteins BAP31/BAP29
DXS1357E
X81109
Above

4
38738_at
SMT3 suppressor of mif two 3 yeast
SMT3H1
X99584
Above

homolog 1

5
40480_s_at
FYN oncogene related to SRC FGR
FYN
M14333
Above

YES

6
38518_at
sex comb on midleg Drosophila like 2
SCML2
Y18004
Above

7
31492_at
muscle specific gene
M9
AB019392
Below

8
35688_g_at
mature T-cell proliferation 1
MTCP1
Z24459
Above

9
35939_s_at
POU domain class 4 transcription
POU4F1
L20433
Above

factor 1

10
36128_at
transmembrane trafficking protein
TMP21
L40397
Above

11
37014_at
myxovirus influenza resistance 1
MX1
M33882
Above

homolog of murine interferon-

inducible protein p78

12
34374_g_at
upstream regulatory element binding
UREB1
Z97054
Above

protein 1

13
688_at
proteasome prosome macropain 26S
PSMC1
L02426
Above

subunit ATPase 1

14
39878_at
protocadherin 9
PCDH9
AI524125
Below

15
38771_at
histone deacetylase 1
HDAC1
D50405
Below

16
865_at
ribosomal protein S6 kinase 90 kD
RPS6KA3
U08316
Above

polypeptide 3

17
41143_at
calmodulin (CALM1) gene
CALM1
U12022
Above

18
39867_at
Tu translation elongation factor
TUFM
S75463
Below

mitochondrial

19
41470_at
prominin mouse like 1
PROML1
AF027208
Above

20
41503_at
KIAA0854 protein
KIAA0854
AB020661
Below

21
2039_s_at
FYN oncogene related to SRC FGR
FYN
M14333
Above

YES

22
36845_at
KIAA0136 protein
KIAA0136
D50926
Above

23
36940_at
TGFB1-induced anti-apoptotic factor 1
TIAF1
D86970
Above

24
32236_at
ubiquitin-conjugating enzyme E2G 2
UBE2G2
AF032456
Above

homologous to yeast UBC7

25
36885_at
spleen tyrosine kinase
SYK
L28824
Below

26
40200_at
heat shock transcription factor 1
HSF1
M64673
Below

27
40842_at
U1 snRNP-specific protein A gene
SNRPA
M60784
Below

28
40514_at
hypothetical 43.2 kD protein
LOC51614
AF091085
Below

29
41222_at
signal transducer and activator of
STAT6
AF067575
Below

transcription 6 (STAT6) gene

30
1294_at
ubiquitin-activating enzyme E1-like
UBE1L
L13852
Below

31
34315_at
AFG3 ATPase family gene 3 yeast
AFG3L2
Y18314
Above

like 2

32
39806_at
DKFZP547E2110 protein
DKFZP547E2110
AL050261
Above

33
40875_s_at
small nuclear ribonucleoprotein 70 kD
SNRP70
X06815
Below

polypeptide RNP antigen

34
38458_at
cytochrome b5 (CYB5) gene
CYB5
L39945
Above

35
1817_at
prefoldin 5
PFDN5
D89667
Below

36
34709_r_at
stromal antigen 2
STAG2
Z75331
Above

37
33447_at
myosin light polypeptide regulatory
MLCB
X54304
Above

non-sarcomeric 20 kD

38
1077_at
recombination activating gene 1
RAG1
M29474
Below

39
1915_s_at
v-fos FBJ murine osteosarcoma viral
FOS
V01512
Above

oncogene homolog

40
38854_at
KIAA0635 gene product
KIAA0635
AB014535
Above

41
37732_at
RING1 and YY1 binding protein
RYBP
AL049940
Above

42
35940_at
POU domain class 4 transcription
POU4F1
X64624
Above

factor 1

43
34733_at
splicing factor 3a subunit 1 120 kD
SF3A1
X85237
Below

44
245_at
selectin L lymphocyte adhesion
SELL
M25280
Below

molecule 1

45
40146_at
RAP1B member of RAS oncogene
RAP1B
AL080212
Below

family

46
40104_at
serine/threonine kinase 25 Ste20 yeast
STK25
D63780
Below

homolog

47
430_at
nucleoside phosphorylase
NP
X00737
Above

48
36899_at
special AT-rich sequence binding
SATB1
M97287
Below

protein 1 binds to nuclear

matrix/scaffold-associating DNA s

49
35727_at
hypothetical protein FLJ20517
FLJ20517
AI249721
Below

50
38649_at
KIAA0970 protein
KIAA0970
AB023187
Below

51
36107_at
ATP synthase H transporting
ATP5J
AA845575
Above

mitochondrial F0 complex subunit F6

52
38789_at
transketolase Wernicke-Korsakoff
TKT
L12711
Below

syndrome

53
39301_at
calpain 3 p94
CAPN3
X85030
Below

54
41278_at
BAF53
BAF53A
AF041474
Below

55
41162_at
protein phosphatase 1G formerly 2C
PPM1G
Y13936
Below

magnesium-dependent gamma

isoform

56
37819_at
hypothetical protein
LOC54104
AF007130
Below

57
38717_at
DKFZP586A0522 protein
DKFZP586A0522
AL050159
Below

58
40019_at
ecotropic viral integration site 2B
EVI2B
M60830
Above

59
39489_g_at
protocadherin 9
PCDH9
W27720
Below

60
857_at
protein phosphatase 1A formerly 2C
PPM1A
S87759
Above

magnesium-dependent alpha isoform

61
32804_at
RNA binding motif protein 5
RBM5
AF091263
Below

62
37676_at
phosphodiesterase 8A
PDE8A
AF056490
Below

63
1519_at
v-ets avian erythroblastosis virus E26
ETS2
J04102
Above

oncogene homolog 2

64
37680_at
A kinase PRKA anchor protein gravin
AKAP12
U81607
Below

12

65
548_s_at
spleen tyrosine kinase
SYK
S80267
Below

66
39797_at
KIAA0349 protein
KIAA0349
AB002347
Above

67
32789_at
nuclear cap binding protein subunit 2
NCBP2
AA149428
Below

20 kD

68
38091_at
lectin galactoside-binding soluble 9
LGALS9
Z49107
Below

galectin 9

69
41223_at
cytochrome c oxidase subunit Va
COX5A
M22760
Below

70
933_f_at
zinc finger protein 91 HPF7 HTF10
ZNF91
L11672
Below

71
37012_at
capping protein actin filament muscle
CAPZB
U03271
Below

Z-line beta

72
35214_at
UDP-glucose dehydrogenase
UGDH
AF061016
Above

73
32434_at
myristoylated alanine-rich protein
MACS
D10522
Above

kinase C substrate MARCKS 80K-L

74
38345_at
centrosomal protein 1
CEP1
AF083322
Below

75
40404_s_at
CDC16 cell division cycle 16 S.
CDC16
U18291
Below

cerevisiae
homolog

76
39096_at
SON DNA binding protein
SON
AB028942
Above

77
33429_at
DKFZP586M1523 protein
DKFZP586M1523
AL050225
Above

78
40641_at
TBP-associated factor 172
TAF-172
AF038362
Above

79
41381_at
KIAA0308 protein
KIAA0308
AB002306
Below

80
35135_at

Homo sapiens
Similar to CG15084

X13956
Below

gene product clone MGC 10471

mRNA complete cds

81
39421_at
runt-related transcription factor 1
RUNX1
D43969
Below

acute myeloid leukemia 1 aml1

oncogene

82
195_s_at
caspase 4 apoptosis-related cysteine
CASP4
U28014
Below

protease

83
36898_r_at
primase polypeptide 2A 58 kD
PRIM2A
X74331
Above

84
38792_at
spermine synthase
SMS
AD001528
Above

85
32643_at
glucan 1 4-alpha-branching enzyme 1
GBE1
L07956
Below

glycogen branching enzyme Andersen

disease glycogen storage disease type

IV

86
38808_at
cell membrane glycoprotein 110000M
GP110
D64154
Below

r surface antigen

87
36062_at
Leupaxin
LPXN
AF062075
Below

88
300_f_at
transcription factor BTF3 homolog

HG4518-
Below

(GB: M90355)

HT4921

89
1979_s_at
nucleolar protein 1 120 kD
NOL1
X55504
Below

90
32230_at
eukaryotic translation initiation factor
EIF3S2
U39067
Below

3 subunit 2 beta 36 kD

91
39893_at
guanine nucleotide binding protein G
GNG7
AB010414
Below

protein gamma 7

92
34651_at
catechol-O-methyltransferase
COMT
M58525
Above

93
1052_s_at
CCAAT/enhancer binding protein
CEBPD
M83667
Below

C/EBP delta

94
36272_r_at
peripheral myelin protein 2
PMP2
X62167
Below

95
2044_s_at
retinoblastoma 1 including
RB1
M15400
Below

osteosarcoma

96
32135_at
sterol regulatory element binding
SREBF1
U00968
Below

transcription factor 1

[0128]

14

TABLE 12

Genes selected by CFS for MLL

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
34306_at
muscleblind Drosophila like
MBNL
AB007888
Above

2
40797_at
a disintegrin and metalloproteinase
ADAM10
AF009615
Above

domain 10

3
33412_at
LGALS1 Lectin, galactoside-binding,
LGALS1
AI535946
Above

soluble, 1 (galectin 1)

4
39338_at
S100 calcium-binding protein A10
S100A10
AI201310
Above

annexin II ligand calpactin I light

polypeptide p11

5
2062_at
insulin-like growth factor binding
IGFBP7
L19182
Above

protein 7

6
32193_at
plexin C1
PLXNC1
AF030339
Above

7
40518_at
protein tyrosine phosphatase receptor
PTPRC
Y00062
Above

type C

8
36777_at
DNA segment on chromosome 12
D12S2489E
AJ001687
Above

unique 2489 expressed sequence

9
38391_at
capping protein actin filament
CAPG
M94345
Above

gelsolin-like

10
40763_at
Meis1 mouse homolog
MEIS1
U85707
Above

11
34721_at
FK506-binding protein 5
FKBP5
U42031
Above

12
37809_at
homeo box A9
HOXA9
U41813
Above

13
32215_i_at
KIAA0878 protein
KIAA0878
AB020685
Above

14
38160_at
lymphocyte antigen 75
LY75
AF011333
Above

15
1389_at
membrane metallo-endopeptidase
MME
J03779
Below

neutral endopeptidase enkephalinase

CALLA CD10

16
34168_at
deoxynucleotidyltransferase terminal
DNTT
M11722
Below

17
40522_at
glutamate-ammonia ligase glutamine
GLUL
X59834
Above

synthase

18
854_at
B lymphoid tyrosine kinase
BLK
S76617
Above

19
40067_at
E74-like factor 1 ets domain
ELF1
M82882
Above

transcription factor

20
39756_g_at
X-box binding protein 1
XBP1
Z93930
Below

21
32134_at
Testing
DKFZP586B2022
AL050162
Above

22
39379_at

Homo sapiens
mRNA cDNA

AL049397
Above

DKFZp586C1019 from clone

DKFZp586C1019

23
40415_at
acetyl-Coenzyme A acyltransferase 1
ACAA1
X14813
Above

peroxisomal 3-oxoacyl-Coenzyme A

thiolase

24
40519_at
protein tyrosine phosphatase receptor
PTPRC
Y00638
Above

type C

25
33847_s_at
cyclin-dependent kinase inhibitor 1B
CDKN1B
U10906
Above

p27 Kip1

26
32696_at
pre-B-cell leukemia transcription
PBX3
X59841
Above

factor 3

27
40417_at
KIAA0098 protein

D43950
Above

28
1644_at
eukaryotic translation initiation factor
EIF3S2
U36764
Above

3 subunit 2 beta 36 kD

29
948_s_at
peptidylprolyl isomerase D
PPID
D63861
Above

cyclophilin D

30
34337_s_at
putative DNA binding protein
M96
AJ010014
Below

31
41747 s_at
myocyte-specific enhancer factor 2A
MEF2A
U49020
Above

(MEF2A) gene

32
39516_at
hypothetical protein
HSPC004
AI827793
Above

33
31820_at
hematopoietic cell-specific Lyn
HCLS1
X16663
Above

substrate 1

34
33305_at
serine or cysteine proteinase inhibitor
SERPINB1
M93056
Above

clade B ovalbumin member 1

35
40520_g_at
protein tyrosine phosphatase receptor
PTPRC
Y00638
Above

type C

36
41222_at
signal transducer and activator of
STAT6
AF067575
Above

transcription 6 (STAT6) gene

37
1718_at
actin related protein 2/3 complex
ARPC2
U50523
Above

subunit 2 34 kD

38
38342_at
KIAA0239 protein
KIAA0239
D87076
Below

39
38805_at
TG-interacting factor TALE family
TGIF
X89750
Below

homeobox

40
32089_at
sperm associated antigen 6
SPAG6
AF079363
Above

41
1950_s_at
Smad 3, exon 1

AB004922
Above

42
39410_at
development and differentiation
DDEF2
AB007860
Above

enhancing factor 2

43
37280_at
MAD mothers against
MADH1
U59912
Below

decapentaplegic Drosophila homolog 1

44
32607_at
brain acid-soluble protein 1
BASP1
AF039656
Above

45
39389_at
CD9 antigen p24
CD9
M38690
Below

46
40913_at
ATPase Ca transporting plasma
ATP2B4
W28589
Below

membrane 4

47
1039_s_at
hypoxia-inducible factor 1 alpha
HIF1A
U22431
Below

subunit basic helix-loop-helix

transcription factor

48
35939_s_at
POU domain class 4 transcription
POU4F1
L20433
Below

factor 1

49
963_at
ligase IV DNA ATP-dependent
LIG4
X83441
Below

50
39628_at
RAB9 member RAS oncogene family
RAB9
U44103
Below

51
38242_at
B cell linker protein
SLP65
AF068180
Below

52
37692_at
diazepam binding inhibitor GABA
DBI
AI557240
Above

receptor modulator acyl-Coenzyme A

binding protein

53
32166_at
KIAA1027 protein
KIAA1027
AB028950
Above

54
34800_at
DKFZP586O1624 protein
DKFZP586O1624
AL039458
Below

55
34386_at
methyl-CpG binding domain protein 4
MBD4
AF072250
Below

56
40296_at
hypothetical protein
753P9
AL023653
Below

57
40456_at
up-regulated by BCG-CWS
LOC64116
AL049963
Above

58
33943_at
ferritin heavy polypeptide 1
FTH1
L20941
Below

59
39049_at
G18.1a and G18.1b proteins (G18.1a

AJ243937
Below

and G18.1b genes, located in the class

III region of the major

histocompatibility complex)

60
38075_at
synaptophysin-like protein
SYPL
X68194
Above

61
932_i_at
zinc finger protein 91 HPF7 HTF10
ZNF91
L11672
Below

62
1825_at
IQ motif containing GTPase
IQGAP1
L33075
Above

activating protein 1

63
34210_at
CDW52 antigen CAMPATH-1
CDW52
N90866
Below

antigen

64
39778_at
mannosyl alpha-1 3- glycoprotein
MGAT1
M55621
Below

beta-1 2-N-

acetylglucosaminyltransferase

65
34699_at
CD2-associated protein
CD2AP
AL050105
Below

66
40066_at
ubiquitin-activating enzyme E1C
UBE1C
AF046024
Above

homologous to yeast UBA3

67
41177_at
hypothetical protein FLJ12443
FLJ12443
AW024285
Above

68
32736_at
HSPC022 protein
HSPC022
W68830
Above

69
1928_s_at
mad protein homolog Smad2 gene
Smad2
U78733
Below

70
1081_at
ornithine decarboxylase 1
ODC1
M33764
Above

71
37345_at
Calumenin
CALU
AF013759
Above

72
34099_f_at
nucleosome assembly protein 1-like 1
NAP1L1
W26056
Above

73
933_f_at
zinc finger protein 91 HPF7 HTF10
ZNF91
L11672
Below

74
32214_at
thioredoxin-like 32 kD
TXNL
AF003938
Below

75
33501_r_at
SNC73 protein SNC73 mRNA

S71043
Below

complete cds

76
950_at
translocation protein 1
TLOC1
D87127
Below

77
41161_at
death-associated protein 6
DAXX
AB015051
Below

78
41381_at
KIAA0308 protein
KIAA0308
AB002306
Below

79
38705_at
ubiquitin-conjugating enzyme E2D 2
UBE2D2
AI310002
Above

homologous to yeast UBC4/5

80
38617_at
LIM domain kinase 2
LIMK2
D45906
Below

81
34305_at
poly rC binding protein 1
PCBP1
Z29505
Above

82
40436_g_at
solute carrier family 25 mitochondrial
SLC25A6
J03592
Above

carrier adenine nucleotide translocator

member 6

83
1827_s_at
c-myc-P64 mRNA, initiating from

M13929
Above

promoter P0

84
38479_at
acidic protein rich in leucines
SSP29
Y07969
Below

85
33207_at
DnaJ Hsp40 homolog subfamily C
DNAJC3
AI095508
Below

member 3

86
39039_s_at
CGI-76 protein
LOC51632
AI557497
Below

87
32157_at
protein phosphatase 1 catalytic
PPP1CA
S57501
Above

subunit alpha isoform

88
905_at
guanylate kinase 1
GUK1
L76200
Below

89
35794_at
KIAA0942 protein
KIAA0942
AB023159
Below

90
1007_s_at
discoidin domain receptor family
DDR1
U48705
Below

member 1

91
39424_at
tumor necrosis factor receptor
TNFRSF14
U70321
Below

superfamily member 14 herpesvirus

entry mediator

92
36634_at
BTG family member 2
BTG2
U72649
Below

93
38760_f_at
butyrophilin subfamily 3 member A2
BTN3A2
U90546
Below

[0129]

15

TABLE 13

Genes selected by CFS for Novel Class

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
37960_at
carbohydrate chondroitin 6/keratan
CHST2
AB014679
Above

sulfotransferase 2

2
31892_at
protein tyrosine phosphatase receptor
PTPRM
X58288
Above

type M

3
994_at
protein tyrosine phosphatase receptor
PTPRM
X58288
Above

type M

4
995_g_at
protein tyrosine phosphatase receptor
PTPRM
X58288
Above

type M

5
41074_at
G protein-coupled receptor 49
GPR49
AF062006
Above

6
41073_at
G protein-coupled receptor 49
GPR49
AI743745
Above

7
34676_at
KIAA1099 protein
KIAA1099
AB029022
Above

8
36139_at
DKFZP586G0522 protein
DKFZP586G0522
AL050289
Above

9
37542_at
lipoma HMGIC fusion partner-like 2
LHFPL2
D86961
Above

10
41159_at
clathrin heavy polypeptide Hc
CLTC
D21260
Above

11
32800_at
retinoid X receptor alpha mRNA

U66306
Above

12
1664_at
insulin-like growth factor 2
IGF2
HG3543-
Above

HT3739

13
36566_at
cystinosis nephropathic
CTNS
AJ222967
Above

[0130]

16

TABLE 14

Gene selected by CFS for T-ALL

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
38319_at
CD3D antigen
CD3D
AA919102
Above

delta

polypeptide

TiT3 complex

[0131]

17

TABLE 15

Genes selected by CFS for TEL-AML1L

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
38652_at
hypothetical protein FLJ20154
FLJ20154
AF070644
Above

2
36239_at
POU domain class 2 associating
POU2AF1
Z49194
Above

factor 1

3
41442_at
core-binding factor runt domain alpha
CBFA2T3
AB010419
Above

subunit 2 translocated to 3

4
37780_at
piccolo presynaptic cytomatrix
PCLO
AB011131
Above

protein

5
36985_at
isopentenyl-diphosphate delta
IDI1
X17025
Above

isomerase

6
38578_at
tumor necrosis factor receptor
TNFRSF7
M63928
Above

superfamily member 7

7
35614_at
transcription factor-like 5 basic helix-
TCFL5
AB012124
Above

loop-helix

8
32224_at
KIAA0769 gene product
KIAA0769
AB018312
Above

9
32730_at
KIAA1750 protein

AL080059
Above

10
36937_s_at
PDZ and LIM domain 1 elfin
PDLIM1
U90878
Below

11
36008_at
protein tyrosine phosphatase type IVA
PTP4A3
AF041434
Above

member 3

12
41200_at
CD36 antigen collagen type I receptor
CD36L1
Z22555
Above

thrombospondin receptor like 1

13
33690_at
DKFZp434A202 from clone

AL080190
Above

DKFZp434A202

14
755_at
inositor 1 4 5-triphosphate receptor
ITPR1
D26070
Above

type 1

15
41097_at
telomeric repeat binding factor 2
TERF2
AF002999
Above

16
160029_at
protein kinase C beta 1
PRKCB1
X07109
Above

17
34481_at
vav proto-oncogene
Vav
AF030227
Above

18
41498_at
KIAA0911 protein
KIAA0911
AB020718
Above

19
37280_at
MAD mothers against
MADH1
U59912
Above

decapentaplegic Drosphila homolog

1

20
1647_at
IQ motif containing GTPase
IQGAP2
U51903
Below

activating protein 2

21
37724_at
v-myc avian myelocytomatosis viral
MYC
V00568
Below

oncogene homolog

22
37981_at
drebrin 1
DBN1
U00802
Above

23
37326_at
proteolipid protein 2 colonic
PLP2
U93305
Below

epithelium-enriched

24
37344_at
major histocompatibility complex
HLA-DMA
X62744
Above

class II DM alpha

25
38666_at
pleckstrin homology Sec7 and
PSCD1
M85169
Below

coiled/coil domains 1 cytohesin 1

26
39039_s_at
CGI-76 protein
LOC51632
AI557497
Below

27
34819_at
CD164 antigen sialomucin
CD164
D14043
Below

28
40729_s_at
nuclear factor of kappa light
NFKBIL1
Y14768
Above

polypeptide gene enhancer in B-cells

inhibitor-like 1

29
34224_at
fatty acid desaturase 3
FADS3
AC004770
Above

30
39827_at
hypothetical protein
FLJ20500
AA522530
Below

31
32157_at
protein phosphatase 1 catalytic
PPP1CA
S57501
Below

subunit alpha isoform

32
34183_at
DKFZP434C171 protein
DKFZP434C17
AL080169
Below

1

33
39329_at
actinin alpha 1
ACTN1
X15804
Below

34
38124_at
midkine neurite growth-promoting
MDK
X55110
Above

factor 2

35
33304_at
interferon stimulated gene 20 kD
ISG20
U88964
Above

36
41295_at
GTT1 protein
GTT1
AL041780
Below

37
40745_at
adaptor-related protein complex 1
AP1B1
L13939
Above

beta 1 subunit

38
38906_at
spectrin alpha erythrocytic 1
SPTA1
M61877
Above

elliptocytosis 2

39
263_g_at
S-adenosylmethionine decarboxylase
AMD1
M21154
Below

1

40
41609_at
major histocompatibility complex
HLA-DMB
U15085
Above

class II DM beta

41
39045_at
hypothetical protein FLJ21432
FLJ21432
W26655
Below

42
39421_at
runt-related transcription factor 1
RUNX1
D43969
Above

acute myeloid leukemia 1 aml1

oncogene

43
34210_at
CDW52 antigen CAMPATH-1
CDW52
N90866
Above

antigen

44
37276_at
IQ motif containing GTPase
IQGAP2
U51903
Below

activating protein 2

45
38763_at
L-iditol-2 dehydrogenase gene

L29254
Below

46
40960_at
UDP-Gal betaGlcNAc beta 1 4-
B4GALT1
D29805
Below

galactosyltransferase polypeptide 1

47
1127_at
ribosomal protein S6 kinase 90 kD
RPS6KA1
L07597
Below

polypeptide 1

48
37359_at
KIAA0102 gene product
KIAA0102
D14658
Below

49
38968_at
SH3-domain binding protein 5 BTK-
SH3BP5
AB005047
Below

associated

50
39135_at
KIAA0767 protein
KIAA0767
AB018310
Below

51
36128_at
transmembrane trafficking protein
TMP21
L40397
Below

52
1158_s_at
calmodulin 3 phosphorylase kinase
CALM3
J04046
Above

delta

53
34782_at
jumonji mouse homolog
JMJ
AL021938
Below

54
37893_at
protein tyrosine phosphatase non-
PTPN2
AI828880
Below

receptor type 2

55
39758_f_at
Lysosomal-associated membrane
LAMP1
J04182
Below

protein 1

56
35151_at
tumor suppressor deleted in oral
DOC-1R
AF089814
Below

cancer-related 1

57
38096_f_at
major histocompatibility complex
HLA-DPB1
M83664
Above

class II DP beta 1

58
40467_at
succinate dehydrogenase complex
SDHD
AB006202
Below

subunit D integral membrane protein

59
39712_at
S100 calcium-binding protein A13
S100A13
AI541308
Below

60
41812_s_at
KIAA0906 protein
KIAA0906
AB020713
Below

61
34336_at
lysyl-tRNA synthetase
KARS
D32053
Below

62
38336_at
KIAA1013 protein
KIAA1013
AB023230
Below

63
32253_at
arginine-glutamic acid dipeptide RE
RERE
AB007927
Below

repeats

64
35731_at
integrin alpha 4 antigen CD49D alpha
ITGA4
X16983
Below

4 subunit of VLA-4 receptor

65
40698_at
C-type calcium dependent
CLECSF2
X96719
Below

carbohydrate-recognition domain

lectin superfamily member 2

activation-induced

66
840_at
zinc finger protein 220
ZNF220
U47742
Above

67
41171_at
proteasome prosome macropain
PSME2
D45248
Above

activator subunit 2 PA28 beta

68
34877_at
Janus kinase 1 a protein tyrosine
JAK1
AL039831
Above

kinase

69
37190_at
WAS protein family member 1
WASF1
D87459
Below

70
31690_at
Glutamate dehydrogenase-2
GLUD2
U08997
Below

71
40961_at
SWI/SNF related matrix associated
SMARCA2
X72889
Below

actin dependent regulator of

chromatin subfamily a member 2

72
38149_at
KIAA0053 gene product
KIAA0053
D29642
Above

73
2061_at
integrin alpha 4 antigen CD49D alpha
ITGA4
L12002
Below

4 subunit of VLA-4 receptor

74
2012_s_at
protein kinase DNA-activated
PRKDC
U34994
Below

catalytic polypeptide

75
36878_f_at
major histocompatibility complex
HLA-DQB1
M60028
Above

class II DQ beta 1

76
34821_at
DKFZP586D0623 protein
DKFZP586D06
AL050197
Below

23

77
36980_at
proline-rich protein with nuclear
B4-2
U03105
Below

targeting signal

78
853_at
nuclear factor erythroid-derived 2 like
NFE2L2
S74017
Below

2

79
39320_at
caspase 1 apoptosis-related cysteine
CASP1
U13697
Below

protease interleukin 1 beta convertase

80
32572_at
ubiquitin specific protease 9 X
USP9X
X98296
Below

chromosome Drosophila fat facets

related

81
387_at
cyclin-dependent kinase 9 CDC2-
CDK9
X80230
Below

related kinase

82
35300_at
glutamyl-prolyl-tRNA synthetase
EPRS
X54326
Below

83
36155_at
KIAA0275 gene product
KIAA0275
D87465
Below

84
37625_at
Interfuron regulatory factor 4
IRF4
U52682
Below

85
35763_at
KIAA0540 protein
KIAA0540
AB011112
Below

86
39077_at
DR1-associated protein 1 negative
DRAP1
U41843
Below

cofactor 2 alpha

87
40132_g_at
Follistatin-like 1
FSTL1
D89937
Below

88
32615_at
aspartyl-tRNA synthetase
DARS
J05032
Below

89
38357_at

Homo sapiens
mRNA cDNA

AL049321
Above

DKFZp564D156 from clone

DKFZp564D156

90
34817_s_at
ataxin 2 related protein
A2LP
U70671
Above

91
40856_at
serine or cysteine proteinase inhibitor
SERPINF1
U29953
Below

clade F alpha-2 antiplasmin pigment

epithelium derived factor member 1

92
39784_at
eukaryotic translation initiation factor
EIF2S1
U26032
Below

2 subunit 1 alpha 35 kD

93
37600_at
extracellular matrix protein 1
ECM1
U68186
Below

94
40839_at
ubiquitin-like 3
UBL3
AL080177
Below

95
34832_s_at
KIAA0763 gene product
KIAA0763
AB018306
Below

96
33244_at
chimerin chimaerin 2
CHN2
U07223
Below

97
31516_f_at
basic transcription factor 3 like 1
BTF3L1
M90354
Below

98
35266_at
bladder cancer associated protein
BLCAP
AL049288
Above

99
253_g_at
(clone GPCR W) G protein-linked

L42324
Below

receptor gene (GPCR) gene

100
35227_at
retinoblastoma-binding protein 8
RBBP8
U72066
Below

101
41073_at
G protein-coupled receptor 49
GPR49
AI743745
Below

102
38084_at
chromobox homolog 3 Drosophila
CBX3
AI797801
Below

HP1 gamma

103
39025_at
6.2 kd protein
LOC54543
AI557912
Below

104
32085_at
KIAA0981 protein
KIAA0981
AB023198
Above

105
38902_r_at
Activating transcription factor 2
ATF2
X15875
Below

[0132] 3. T-statistics

[0133] T-statistics is a classical feature selection approach. The t-statistics of a gene is defined as T=|μ1−μ2|/sqrt(σ12/n1+σ22/n2), where μi is the mean expression of that gene in the ith class, σi2 is the variance of that gene in the ith class and ni is the size of the ith class. This formula assigns higher value to a gene that has larger mean difference between two classes and has smaller variance within both classes. For BCR-ABL, hyperdiploid >50, MLL, Novel, and TEL-AML1 the top ranked 40 genes are listed in Tables 16, 18, 19, 20, and 22, whereas for E2A-PBX1 and T-ALL only the top 30 and 31 genes are shown. Additional genes that may be used in expression profiles to assign subjects to a leukemia risk group are shown in Tables 54-60. The genes in Tables 54-60 were selected on the basis of having a T-statistic value greater than the T-statistic vlaue for the gene when examined as a disciminator in 999 of 1000 permutations of the data set (p<0.001; this statistical test is described elsewhere herein). Of these genes, only those having a T-statistic absolute values equal to or greater than 8 (representing a nominal p value of ˜<0.0001) are shown in Tables 54-50.

[0134] Generally, using the top 20-40 genes did not result in significant changes to subtype prediction accuracy. Accordingly, the top 20 genes were used for subtype prediction, unless noted otherwise.

18TABLE 16Genes Selected by T statistics for BCR-ABLAbove/AffymetrixGeneReferenceT-statBelownumberGene NameSymbolnumbervalueMean132319_attumor necrosis factor ligandTNFSF4AL02231012.0346Abovesuperfamily member 4 tax-transcriptionally activatedglycoprotein 1 34 kD236194_atlow density lipoprotein-relatedLRPAP1M63959−11.3077Belowprotein-associated protein 1 alpha-2-macroglobulin receptor-associated protein 131211_s_atCASP2 and RIPK1 domainCRADDU8438810.6627Abovecontaining adaptor with deathdomain437397_atHomo sapiens platelet/endothelialPECAML3465710.2460Abovecell adhesion molecule-1(PECAM-1) gene, exon 16 andcomplete cds.5330_s_attubulin, alpha 1, isoform 44TUBA1HG2259-10.0540AboveHT2348633774_atcaspase 8 apoptosis-relatedCASP8X981729.9147Abovecysteine protease7202_atheat shock transcription factor 2HSF2M65217−9.7639Below81558_g_atp21/Cdc42/Rac1-activated kinasePAK1U241529.6562Above1 yeast Ste20-related939691_atSH3-containing protein SH3GLB1SH3GLB1AB0079609.5307Above102045_s_athemopoietic cell kinaseHCKM16592−9.3898Below1136591_attubulin alpha 1 testis specificTUBA1X069569.3382Above121386_atprotein tyrosine phosphatase non-PTPN9M83738−9.2414Belowreceptor type 91335991_atSm protein FLSM6AA9179459.0298Above1441273_atFK506 binding protein 12-FRAP1AL0469408.9732Aboverapamycin associated protein 11535970_g_atM-phase phosphoprotein 9MPHOSPH9N231378.6474Above1638636_atimmunoglobulin superfamilyISLRAB0031848.4291Abovecontaining leucine-rich repeat1736683_atmatrix Gla proteinMGPAI953789−8.3872Below1839070_atsinged Drosophila like sea urchinSNLU030578.2583Abovefascin homolog like1940798_s_ata disintegrin and metalloproteinaseADAM10Z485798.2283Abovedomain 102041649_atFOXJ2 forkhead factorLOC55810AF0381778.2275Above2138966_atglycoprotein synaptic 2GPSN2AF0389588.2080Above2234759_atHuman hbc647 mRNA sequenceU684948.1863Above231434_atphosphatase and tensin homologPTENU924368.1671Abovemutated in multiple advancedcancers 12440167_s_atCS box-containing WD proteinLOC55884AF0381878.1655Above2540264_g_atzinc finger protein-like 1ZFPL1AF0018918.1384Above2636129_atKIAA0397 gene productKIAA0397AB0078578.0041Above27551_atE1A binding protein p300EP300U01877−7.7578Below2838345_atcentrosomal protein 1CEP1AF083322−7.7431Below2941137_atmyosin phosphatase target subunit 2MYPT2AB007972−7.7301Below3039068_atprotein phosphatase 2 regulatoryPPP2R5DL76702−7.6161Belowsubunit B B56 delta isoform3138160_atlymphocyte antigen 75LY75AF0113337.5830Above3234314_atribonucleotide reductase M1RRM1X595437.5778Abovepolypeptide3339519_atKIAA0692 proteinKIAA0692AB0145927.4662Above3432788_atRAN binding protein 2RANBP2D420637.4114Above3534882_atnucleolar protein KKE/D repeatNOP56Y120657.3622Above362064_g_atexcision repair cross-ERCC5L200467.3597Abovecomplementing rodent repairdeficiency complementation group 53741836_atprotein with polyglutamine repeatERPROT213-21U948367.3350Abovecalcium ca2 homeostasisendoplasmic reticulum protein381563_s_attumor necrosis factor receptorTNFRSF1AM582867.3039Abovesuperfamily member 1A3937047_atNiemann-Pick disease type C1NPC1AF0020207.2357Above4032724_atphytanoyl-CoA hydroxylasePHYHAF023462−7.2252BelowRefsum disease

[0135]

19

TABLE 17

Genes Selected by T statistics for E2A-PBX1

Above/

Affymetrix

Gene
Reference
T-stat
Below

number
Gene Name
Symbol
number
value
Mean

1
32063_at
pre-B-cell leukemia transcription
PBX1
M86546
126.7442
Above

factor 1

2
33355_at

Homo sapiens
cDNA FLJ12900
PBX1
AL049381
36.6116
Above

fis clone NT2RP2004321 (by

CELERA search of target

sequence = PBX1)

3
40454_at
FAT tumor suppressor Drosophila
FAT
X87241
30.7577
Above

homolog

4
717_at
GS3955 protein
GS3955
D87119
23.7813
Above

5
39070_at
singed Drosophila like sea urchin
SNL
U03057
−22.8956
Below

fascin homolog like

6
33641_g_at
nuclear factor of kappa light
NFKBIL1
Y14768
−20.4637
Below

polypeptide gene enhancer in B-

cells inhibitor-like 1

7
36536_at
schwannomin interacting protein 1
SCHIP-1
AF070614
−20.1554
Below

8
854_at
B lymphoid tyrosine kinase
BLK
S76617
19.6467
Above

9
37625_at
interferon regulatory factor 4
IRF4
U52682
18.8419
Above

10
39614_at
KIAA0802 protein
KIAA0802
AB018345
17.8214
Above

11
37099_at
arachidonate 5-lipoxygenase-
ALOX5AP
AI806222
−17.7944
Below

activating protein

12
38994_at
STAT induced STAT inhibitor-2
STATI2
AF037989
−17.6553
Below

13
37641_at
Human gene for hepatitis C-

D28915
−17.3074
Below

associated microtubular aggregate

protein p44, exon 9 and complete

cds.

14
40113_at
GS3955 protein
GS3955
D87119
16.7288
Above

15
2031_s_at
cyclin-dependent kinase inhibitor
CDKN1A
U03106
−14.9826
Below

1A p21 Cip1

16
330_s_at
tubulin, alpha 1, isoform 44
TUBA1
HG2259-
−14.8016
Below

HT2348

17
38340_at
huntingtin interacting protein-1-
KIAA0655
AB014555
14.7180
Above

related

18
38510_at

Homo sapiens
mRNA cDNA

AL049435
−14.4522
Below

DKFZp586B0220

19
268_at

Homo sapiens
platelet/endothelial
PECAM
L34657
−13.7540
Below

cell adhesion molecule-1

(PECAM-1) gene, exon 16 and

complete cds.

20
2062_at
insulin-like growth factor binding
IGFBP7
L19182
13.6403
Above

protein 7

21
37893_at
protein tyrosine phosphatase non-
PTPN2
AI828880
13.5099
Above

receptor type 2

22
38580_at
guanine nucleotide binding protein
GNAQ
U43083
−12.8525
Below

G protein q polypeptide

23
40049_at
death-associated protein kinase 1
DAPK1
X76104
−12.3837
Below

24
38393_at
KIAA0247 gene product
KIAA0247
D87434
12.3436
Above

25
39379_at

Homo sapiens
mRNA cDNA

AL049397
12.2102
Above

DKFZp586C1019

26
430_at
nucleoside phosphorylase
NP
X00737
12.1307
Above

27
37975_at
cytochrome b-245 beta
CYBB
X04011
−12.0743
Below

polypeptide chronic

granulomatous disease

28
34862_at
CGI-49 protein
LOC51097
AA005018
12.0264
Above

29
39756_g_at
X-box binding protein 1
XBP1
Z93930
−11.9796
Below

30
307_at
arachidonate 5-lipoxygenase
ALOX5
J03600
−11.9492
Below

31
37304_at
chromobox homolog 1 Drosophila
CBX1
U35451
11.9422
Above

HP1 beta

32
1287_at
ADP-ribosyltransferase NAD poly
ADPRT
J03473
11.9051
Above

ADP-ribose polymerase

33
1520_s_at
interleukin 1 beta
IL1B
X04500
11.7327
Above

34
596_s_at
colony stimulating factor 3
CSF3R
M59820
−11.6814
Below

receptor granulocyte

35
37493_at
colony stimulating factor 2
CSF2RB
H04668
11.6620
Above

receptor beta low-affinity

granulocyte-macrophage

36
36452_at
synaptopodin
KIAA1029
AB028952
11.4021
Above

37
1081_at
ornithine decarboxylase 1
ODC1
M33764
11.2865
Above

38
1563_s_at
tumor necrosis factor receptor
TNFRSF1A
M58286
−11.1361
Below

superfamily member 1A

39
39069_at
AE-binding protein 1
AEBP1
AF053944
11.0984
Above

40
36203_at
ornithine decarboxylase 1
ODC1
X16277
10.9475
Above

[0136]

20

TABLE 18

Genes Selected by T statistics for Hyperdiploid >50

Above/

Affymetrix

Gene
Reference
T-stat
Below

number
Gene Name
Symbol
number
value
Mean

1
36620_at
superoxide dismutase 1 soluble
SOD1
X02317
9.1574
Above

amyotrophic lateral sclerosis 1

adult

2
39878_at
protocadherin 9
PCDH9
AI524125
−6.9008
Below

3
37543_at
Rac/Cdc42 guanine exchange
ARHGEF6
D25304
6.8366
Above

factor GEF 6

4
41470_at
prominin mouse like 1
PROML1
AF027208
6.7290
Above

5
31492_at
muscle specific gene
M9
AB019392
−6.6885
Below

6
38968_at
SH3-domain binding protein 5
SH3BP5
AB005047
6.4051
Above

BTK-associated

7
1915_s_at
v-fos FBJ murine osteosarcoma
FOS
V01512
6.4008
Above

viral oncogene homolog

8
37677_at
phosphoglycerate kinase 1
PGK1
V00572
6.2865
Above

9
39867_at
Tu translation elongation factor
TUFM
S75463
−6.2299
Below

mitochondrial

10
36795_at
prosaposin variant Gaucher
PSAP
J03077
6.1812
Above

disease and variant metachromatic

leukodystrophy

11
40875_s_at
small nuclear ribonucleoprotein
SNRP70
X06815
−6.0877
Below

70 kD polypeptide RNP antigen

12
306_s_at
high-mobility group nonhistone
HMG14
J02621
6.0804
Above

chromosomal protein 14

13
41724_at
accessory proteins BAP31/BAP29
DXS1357E
X81109
6.0244
Above

14
39168_at
Ac-like transposable element
ALTE
AB018328
5.9336
Above

15
955_at
calmodulin type I
CALM1
HG1862-
5.8650
Above

HT1897

16
38604_at
neuropeptide Y
NPY
AI198311
5.8313
Above

17
39147_g_at
alpha thalassemia/mental
ATRX
U72936
5.8181
Above

retardation syndrome X-linked

RAD54 S. cerevisiae homolog

18
39069_at
AE-binding protein 1
AEBP1
AF053944
−5.6901
Below

19
37014_at
myxovirus influenza resistance 1
MX1
M33882
5.6688
Above

homolog of murine interferon-

inducible protein p78

20
1520_s_at
interleukin 1 beta
IL1B
X04500
5.6605
Above

21
1488_at
protein tyrosine phosphatase
PTPRK
L77886
−5.5877
Below

receptor type K

22
32553_at
MYC-associated zinc finger
MAZ
M94046
−5.5000
Below

protein purine-binding

transcription factor

23
36169_at
NADH dehydrogenase ubiquinone
NDUFA1
N47307
5.4376
Above

1 alpha subcomplex 1 7.5 kD

MWFE

24
1817_at
prefoldin 5
PFDN5
D89667
−5.4110
Below

25
578_at
Human recombination acitivating
RAG2
M94633
−5.4026
Below

protein (RAG2) gene, last exon

26
1556_at
RNA binding motif protein 5
RBM5
U23946
−5.3032
Below

27
40998_at
trinucleotide repeat containing 11
TNRC11
AF071309
5.2349
Above

THR-associated protein 230 kDa

subunit

28
37294_at
B-cell translocation gene 1 anti-
BTG1
X61123
−5.1877
Below

proliferative

29
1447_at
proteasome prosome macropain
PSMB1
D00761
5.1699
Above

subunit beta type 1

30
35940_at
POU domain class 4 transcription
POU4F1
X64624
5.1200
Above

factor 1

31
33307_at
kraken-like
BK126B4.1
AL022316
−5.0984
Below

32
1081_at
ornithine decarboxylase 1
ODC1
M33764
−5.0822
Below

33
34336_at
lysyl-tRNA synthetase
KARS
D32053
−5.0692
Below

34
41143_at
Human calmodulin (CALM1)
CALM1
U12022
5.0543
Above

gene, exons 2, 3, 4, 5 and

6, and complete cds

35
32251_at
hypothetical protein FLJ21174
FLJ21174
AA149307
5.0373
Above

36
35298_at
eukaryotic translation initiation
EIF3S7
U54558
−4.9499
Below

factor 3 subunit 7 zeta 66/67 kD

37
38649_at
KIAA0970 protein
KIAA0970
AB023187
−4.9228
Below

38
36629_at
glucocorticoid-induced leucine
GILZ
AI635895
4.8061
Above

zipper

39
39721_at
ephrin-B1
EFNB1
U09303
4.7968
Above

40
2094_s_at
v-fos FBJ murine osteosarcoma
FOS
K00650
4.7446
Above

viral oncogene homolog

[0137]

21

TABLE 19

Genes Selected by T statistics for MLL

Above/

Affymetrix

Gene
Reference
T-stat
Below

number
Gene Name
Symbol
number
value
Mean

1
307_at
arachidonate 5-lipoxygenase
ALOX5
J03600
−16.8244
Below

2
37280_at
MAD mothers against
MADH1
U59912
−15.4460
Below

decapentaplegic Drosophila

homolog 1

3
1520_s_at
interleukin 1 beta
IL1B
X04500
−13.6764
Below

4
36908_at
Human macrophage mannose
MRC1
M93221
−11.8629
Below

receptor (MRC1) gene, exon 30.

5
33412_at
LGALS1 Lectin, galactoside-
LGALS1
AI535946
11.0223
Above

binding, soluble, 1 (galectin 1)

6
2062_at
insulin-like growth factor binding
IGFBP7
L19182
10.4318
Above

protein 7

7
35940_at
POU domain class 4 transcription
POU4F1
X64624
−10.1815
Below

factor 1

8
39721_at
ephrin-B1
EFNB1
U09303
−9.6158
Below

9
39402_at
interleukin 1 beta
IL1B
M15330
−9.5998
Below

10
1737_s_at
insulin-like growth factor-binding
IGFBP4
M62403
−9.4119
Below

protein 4

11
37413_at
dipeptidase 1 renal
DPEP1
J05257
−9.4101
Below

12
40519_at
protein tyrosine phosphatase
PTPRC
Y00638
9.3163
Above

receptor type C

13
1971_g_at
fragile histidine triad gene
FHIT
U46922
−9.2257
Below

14
1983_at
cyclin D2
CCND2
X68452
−9.2213
Below

15
38869_at
KIAA1069 protein
KIAA1069
AB028992
−9.1951
Below

16
40520_g_at
protein tyrosine phosphatase
PTPRC
Y00638
9.1099
Above

receptor type C

17
1718_at
actin related protein 2/3 complex
ARPC2
U50523
9.0435
Above

subunit 2 34 kD

18
34237_at
HBS1 S. cerevisiae like
HBS1L
AB028961
−8.8208
Below

19
1726_at
DNA polymerase, epsilon,

HG919-
−8.4664
Below

catalytic subunit

HT919

20
36643_at
discoidin domain receptor family
DDR1
L20817
−8.4627
Below

member 1

21
1325_at
MAD mothers against
MADH1
U59423
−8.3762
Below

decapentaplegic Drosophila

homolog 1

22
39379_at

Homo sapiens
mRNA cDNA

AL049397
8.2974
Above

DKFZp586C1019

23
36536_at
schwannomin interacting protein 1
SCHIP-1
AF070614
−8.1177
Below

24
564_at
guanine nucleotide binding protein
GNA11
M69013
−8.1107
Below

G protein alpha 11 Gq class

25
39705_at
KIAA0700 protein
KIAA0700
AB014600
−7.9334
Below

26
36105_at
Human nonspecific crossreacting
NCA
M18728
−7.6911
Below

antigen mRNA, complete cds.

27
174_s_at
intersectin 2
ITSN2
U61167
7.5752
Above

28
39114_at
decidual protein induced by
DEPP
AB022718
−7.4767
Below

progesterone

29
40436_g_at
solute carrier family 25
SLC25A6
J03592
7.3952
Above

mitochondrial carrier adenine

nucleotide translocator member 6

30
794_at
protein tyrosine phosphatase non-
PTPN6
X62055
7.2192
Above

receptor type 6

31
38032_at
KIAA0736 gene product
K1AA0736
AB018279
−7.0718
Below

32
40518_at
protein tyrosine phosphatase
PTPRC
Y00062
6.9829
Above

receptor type C

33
41762_at
TIA1 cytotoxic granule-associated
TIAL1
D64015
−6.9118
Below

RNA-binding protein-like 1

34
1389_at
membrane metallo-endopeptidase
MME
J03779
−6.7734
Below

neutral endopeptidase

enkephalinase CALLA CD10

35
39967_at
leucine zipper down-regulated in
LDOC1
AB019527
−6.7415
Below

cancer 1

36
188_at
ephrin-B1
EFNB1
U09303
−6.5964
Below

37
160033_s_at
X-ray repair complementing
XRCC1
NM_006297
−6.5936
Below

defective repair in Chinese

hamster cells 1

38
40913_at
ATPase Ca transporting plasma
ATP2B4
W28589
−6.5774
Below

membrane 4

39
37398_at
platelet/endothelial cell adhesion
PECAM1
AA100961
−6.5675
Below

molecule CD31 antigen

40
1488_at
protein tyrosine phosphatase
PTPRK
L77886
−6.5584
Below

receptor type K

[0138]

22

TABLE 20

Genes Selected by T statistics for Novel Risk Group

Above/

Affymetrix

Gene
Reference
T-stat
Below

number
Gene Name
Symbol
number
value
Mean

1
41734_at
KIAA0870 protein
KIAA0870
AB020677
−40.5168
Below

2
31892_at
protein tyrosine phosphatase
PTPRM
X58288
33.4654
Above

receptor type M

3
995_g_at
protein tyrosine phosphatase
PTPRM
X58288
24.7557
Above

receptor type M

4
34676_at
KIAA1099 protein
KIAA1099
AB029022
14.0491
Above

5
37908_at
guanine nucleotide binding protein
GNG11
U31384
11.4548
Above

11

6
37960_at
carbohydrate chondroitin 6/keratan
CHST2
AB014679
10.9971
Above

sulfotransferase 2

7
33410_at
integrin alpha 6
ITGA6
S66213
10.0370
Above

8
40585_at
adenylate cyclase 7
ADCY7
D25538
−9.5897
Below

9
33284_at
myeloperoxidase
MPO
M19507
−9.4724
Below

10
41159_at
clathrin heavy polypeptide Hc
CLTC
D21260
9.4489
Above

11
36591_at
tubulin alpha 1 testis specific
TUBA1
X06956
−9.1387
Below

12
37712_g_at
MADS box transcription enhancer
MEF2C
S57212
−9.1225
Below

factor 2 polypeptide C myocyte

enhancer factor 2C

13
38576_at
H2B histone family member B
H2BFB
AJ223353
−9.0869
Below

14
38408_at
transmembrane 4 superfamily
TM4SF2
L10373
−8.7026
Below

member 2

15
33907_at
eukaryotic translation initiation
EIF4G3
AF012072
−8.3540
Below

factor 4 gamma 3

16
41273_at
FK506 binding protein 12-
FRAP1
AL046940
−8.3212
Below

rapamycin associated protein 1

17
402_s_at
intercellular adhesion molecule 3
ICAM3
X69819
−7.9741
Below

18
35112_at
regulator of G-protein signalling 9
RGS9
AF071476
7.8348
Above

19
34850_at
ubiquitin-conjugating enzyme E2E
UBE2E3
AB017644
7.8197
Above

3 homologous to yeast UBC4/5

20
37030_at
KIAA0887 protein
KIAA0887
AB020694
−7.6343
Below

21
36322_at
fucosyltransferase 7 alpha 13
FUT7
AB012668
−7.6240
Below

fucosyltransferase

22
39509_at

Homo sapiens
cDNA FLJ22071

AI692348
−7.6232
Below

23
40091_at
B-cell CLL/lymphoma 6 zinc
BCL6
U00115
−7.6171
Below

finger protein 51

24
37280_at
MAD mothers against
MADH1
U59912
7.5991
Above

decapentaplegic Drosophila

homolog 1

25
1325_at
MAD mothers against
MADH1
U59423
7.5824
Above

decapentaplegic Drosophila

homolog 1

26
831_at
DEAD/H Asp-Glu-Ala-Asp/His
DDX10
U28042
7.4276
Above

box polypeptide 10 RNA helicase

27
37600_at
extracellular matrix protein 1
ECM1
U68186
−7.2991
Below

28
41266_at
integrin alpha 6
ITGA6
X53586
7.2985
Above

29
36958_at
zyxin
ZYX
X95735
−7.2889
Below

30
36564_at
Human DNA sequence from clone

W27419
−7.2848
Below

RP5-1174N9 on chromosome

1p134.1-35.3

31
32174_at
solute carrier family 9
SLC9A3R1
AF015926
−7.2749
Below

sodium/hydrogen exchanger

isoform 3 regulatory factor 1

32
619_s_at
membrane-spanning 4-domains
MS4A2
M27394
−7.2325
Below

subfamily A member 2 Fc

fragment of IgE high affinity I

receptor for beta polypeptide

33
40749_at
membrane-spanning 4-domains
MS4A2
X07203
−7.2063
Below

subfamily A member 2 Fc

fragment of IgE high affinity I

receptor for beta polypeptide

34
31894_at
centromere protein C 1
CENPC1
M95724
6.9679
Above

35
32319_at
tumor necrosis factor ligand
TNFSF4
AL022310
6.8225
Above

superfamily member 4 tax-

transcriptionally activated

glycoprotein 1 34 kD

36
38259_at
syntaxin binding protein 2
STXBP2
AB002559
−6.6992
Below

37
35629_at
hypothetical protein
DJ1042K10.2
AL022238
−6.6968
Below

38
38700_at
cysteine and glycine-rich protein 1
CSRP1
M33146
−6.6962
Below

39
37397_at

Homo sapiens
platelet/endothelial
PECAM
L34657
−6.6934
Below

cell adhesion molecule-1

(PECAM-1) gene, exon 16 and

complete cds.

40
41127_at
solute carrier family 1
SLC1A4
L14595
−6.6892
Below

glutamate/neutral amino acid

transporter member 4

[0139]

23

TABLE 21

Genes Selected by T statistics for T-ALL

Above/

Affymetrix

Gene
Reference
T-stat
Below

number
Gene Name
Symbol
number
value
Mean

1
38242_at
B cell linker protein
SLP65
AF068180
−115.8362
Below

2
38319_at
CD3D antigen delta polypeptide
CD3D
AA919102
27.6995
Above

TiT3 complex

3
37988_at
CD79B antigen immunoglobulin-
CD79B
M89957
−23.7294
Below

associated beta

4
38147_at
SH2 domain protein 1A Duncan s
SH2D1A
AL023657
22.4501
Above

disease lymphoproliferative

syndrome

5
38522_s_at
CD22 antigen
CD22
X52785
−21.2795
Below

6
35350_at
B cell RAG associated protein
BRAG
AB011170
−19.1460
Below

7
36277_at
Human membran protein (CD3-
CD3E
M23323
19.0859
Above

epsilon) gene, exon 9.

8
38604_at
neuropeptide Y
NPY
AI198311
−18.8194
Below

9
33705_at
phosphodiesterase 4B cAMP-
PDE4B
L20971
−18.6383
Below

specific dunce Drosophila

homolog phosphodiesterase E4

10
36878_f_at
major histocompatibility complex
HLA-DQB1
M60028
−18.5620
Below

class II DQ beta 1

11
36638_at
connective tissue growth factor
CTGF
X78947
−18.2772
Below

12
32794_g_at
T cell receptor beta locus
TRB
X00437
17.9081
Above

13
32174_at
solute carrier family 9
SLC9A3R1
AF015926
17.4427
Above

sodium/hydrogen exchanger

isoform 3 regulatory factor 1

14
160041_at
protein tyrosine phosphatase non-
PTPN18
X79568
−17.3412
Below

receptor type 18 brain-derived

15
38521_at
CD22 antigen
CD22
X59350
−17.0388
Below

16
38018_g_at
CD79A antigen immunoglobulin-
CD79A
U05259
−16.7948
Below

associated alpha

17
36571_at
topoisomerase DNA II beta 180 kD
TOP2B
X68060
−16.7508
Below

18
1096_g_at
CD19 antigen
CD19
M28170
−16.4583
Below

19
39318_at
T-cell leukemia/lymphoma 1A
TCL1A
X82240
−16.2017
Below

20
41710_at
hypothetical protein
LOC54103
AL079277
−15.9099
Below

21
599_at
H2.0 Drosophila like homeo box 1
HLX1
M60721
−15.5425
Below

22
266_s_at
CD24 antigen small cell lung
CD24
L33930
−15.0123
Below

carcinoma cluster 4 antigen

23
36502_at
PFTAIRE protein kinase 1
PFTK1
AB020641
−14.9972
Below

24
39114_at
decidual protein induced by
DEPP
AB022718
−14.9886
Below

progesterone

25
37539_at
RalGDS-like gene KIAA0959
KIAA0959
AB023176
−14.6872
Below

protein

26
40775_at
integral membrane protein 2A
ITM2A
AL021786
14.5666
Above

27
34033_s_at
leukocyte immunoglobulin-like
LILRA2
AF025531
−14.3809
Below

receptor subfamily A with TM

domain member 2

28
2031_s_at
cyclin-dependent kinase inhibitor
CDKN1A
U03106
−14.1071
Below

1A p21 Cip1

29
38051_at
mal T-cell differentiation protein
MAL
X76220
14.0743
Above

30
35794_at
KIAA0942 protein
KIAA0942
AB023159
−13.9659
Below

31
41156_g_at
catenin cadherin-associated
CTNNA1
U03100
−13.8135
Below

protein alpha 1 102 kD

32
32979_at
GRB2-associated binding protein 1
GAB1
U43885
−13.5842
Below

33
32562_at
endoglin Osler-Rendu-Weber
ENG
X72012
−13.4209
Below

syndrome 1

34
36536_at
schwannomin interacting protein 1
SCHIP-1
AF070614
−13.4172
Below

35
36108_at
major histocompatibility complex
HLA-DQB1
M16276
−13.3518
Below

class II DQ beta 1

36
41734_at
KIAA0870 protein
KIAA0870
AB020677
−13.2672
Below

37
41153_f_at

Homo sapiens
alphaE-catenin
CTNNA1
AF102803
−12.7927
Below

(CTNNA1) gene, exon 18 and

complete cds.

38
37710_at
MADS box transcription enhancer
MEF2C
L08895
−12.7716
Below

factor 2 polypeptide C myocyte

enhancer factor 2C

39
39893_at
guanine nucleotide binding protein
GNG7
AB010414
−12.7696
Below

G protein gamma 7

40
37908_at
guanine nucleotide binding protein
GNG11
U31384
−12.7353
Below

11

[0140]

24

TABLE 22

Genes Selected by T statistics for TEL-AML1

Above/

Affymetrix

Gene
Reference
T-stat
Below

number
Gene Name
Symbol
number
value
Mean

1
38578_at
tumor necrosis factor receptor
TNFRSF7
M63928
15.2209
Above

superfamily member 7

2
38203_at
potassium intermediate/small
KCNN1
U69883
15.0804
Above

conductance calcium-activated

channel subfamily N member 1

3
36524_at
Rho guanine nucleotide exchange
ARHGEF4
AB029035
14.9774
Above

factor GEF 4

4
37780_at
piccolo presynaptic cytomatrix
PCLO
ABO11131
14.1405
Above

protein

5
35614_at
transcription factor-like 5 basic
TCFL5
AB012124
12.9369
Above

helix-loop-helix

6
160029_at
protein kinase C beta 1
PRKCB1
X07109
12.5429
Above

7
1980_s_at
non-metastatic cells 2 protein
NME2
X58965
−12.5035
Below

NM23B expressed in

8
1488_at
protein tyrosine phosphatase
PTPRK
L77886
12.3871
Above

receptor type K

9
34194_at

Homo sapiens
cDNA FLJ21697

AL049313
12.1089
Above

10
37908_at
guanine nucleotide binding protein
GNG11
U31384
11.4322
Above

11

11
40272_at
collapsin response mediator
CRMP1
D78012
11.0625
Above

protein 1

12
41097_at
telomeric repeat binding factor 2
TERF2
AF002999
11.0133
Above

13
33690_at

Homo sapiens
mRNA cDNA

AL080190
10.8763
Above

DKFZp434A202

14
32730_at

Homo sapiens
mRNA for

AL080059
10.7439
Above

KIAA1750

15
1325_at
MAD mothers against
MADH1
U59423
10.5332
Above

decapentaplegic Drosophila

homolog 1

16
41819_at
FYN-binding protein FYB-
FYB
U93049
10.3692
Above

120/130

17
1299_at
telomeric repeat binding factor 2
TERF2
X93512
10.2921
Above

18
35665_at
phosphoinositide-3-kinase class 3
PIK3C3
Z46973
10.0568
Above

19
36537_at
Rho-specific guanine nucleotide
P114-RHO-
AB011093
9.8824
Above

exchange factor p114
GEF

20
37280_at
MAD mothers against
MADH1
U59912
9.8662
Above

decapentaplegic Drosophila

homolog 1

21
1936_s_at
proto-oncogene c-myc, alt.

HG3523-
−9.6621
Below

transcript 3, ORF 114

HT4899

22
1077_at
recombination activating gene 1
RAG1
M29474
9.4563
Above

23
38763_at
Human (clone D21-1) L-iditol-2

L29254
−9.2719
Below

dehydrogenase gene, exon 9 and

complete cds.

24
41295_at
GTT1 protein
GTT1
AL041780
−9.1813
Below

25
36008_at
protein tyrosine phosphatase type
PTP4A3
AF041434
9.1682
Above

IVA member 3

26
38570_at
major histocompatibility complex
HLA-DOB
X03066
9.0394
Above

class II DO beta

27
32163_f_at
EST

AA216639
9.0392
Above

28
40570_at
forkhead box O1A
FOXO1A
AF032885
8.9931
Above

rhabdomyosarcoma

29
32724_at
phytanoyl-CoA hydroxylase
PHYH
AF023462
8.9571
Above

Refsum disease

30
932_i_at
zinc finger protein 91 HPF7
ZNF91
L11672
8.8075
Above

HTF10

31
37343_at
inositol 1 4 5-triphosphate receptor
ITPR3
U01062
8.7321
Above

type 3

32
33447_at
myosin light polypeptide
MLCB
X54304
−8.6848
Below

regulatory non-sarcomeric 20 kD

33
35362_at
myosin X
MYO10
AB018342
8.6700
Above

34
38906_at
spectrin alpha erythrocytic 1
SPTA1
M61877
8.5010
Above

elliptocytosis 2

35
324_f_at
basic transcription factor 3
BTF3
HG1515-
−8.4705
Below

HT1515

36
39329_at
actinin alpha 1
ACTN1
X15804
−8.3219
Below

37
577_at
midkine neurite growth-promoting
MDK
M94250
8.2693
Above

factor 2

38
40729_s_at
nuclear factor of kappa light
NFKBIL1
Y14768
8.2000
Above

polypeptide gene enhancer in B-

cells inhibitor-like 1

39
41442_at
core-binding factor runt domain
CBFA2T3
AB010419
8.0604
Above

alpha subunit 2 translocated to 3

40
36275_at

Homo sapiens
mRNA from

AB002438
7.8550
Above

chromosome 5q21-22 clone

FBR89

[0141] 4. Wilkins'

[0142] This method of selecting genes uses the weighted sum of three components to estimate the discriminative value of each gene. The higher the score, the better the gene is at discriminating between the two classes. The input to the scoring method is preprocessed and normalized data. The idea of the metric is that a gene is a good discriminator if: (1) it is expressed in one class and not in the other, or if the gene is expressed in both classes, but significantly more so in one than the other, or (2) the gene is present in most samples, and the data are pure, in the sense that there is a threshold expression value for the gene where the gene generally has expression levels larger than the threshold in one class, and smaller than the threshold in the other class. The components of the metric were quantified as follows. For a gene, assume PR1 is the ratio of “present” samples to all samples in class 1, where present means that the gene's expression value was not preprocessed to a constant (1). Assume PR2 is defined similarly for class 2. The first component of the metric, M1, is estimated as the absolute difference between PR1 and PR2. This value is between 0 (when the gene is equally present in both classes) and 1 (when the gene is expressed in one class and not in the other). The second component of the metric, M2, measures the extent to which the gene is present overall, and is defined as the average of PR1 and PR2. The final component, M3, estimates the “purity”, or existence of a threshold value. The gene expression values for the present samples are sorted into ascending order and a vector of their class labels is built, for example {+, +, +, −, −, −, +, −, −, +, −}. The next step is to find the best place to partition the samples so that the expression values for one class (maybe +) are less than the partition point, and the values from the other class are larger. Let LC1 and LC2 be the number of class 1 and class 2 samples on the left side of the partition, respectively. Assume RC1 and RC2 are defined similarly for the right side of the partition. Then the purity is estimated as: max {LC1-LC2+RC2−RC1, LC2−LC1+RC1−RC2}/ number of total present samples. Each possible partition is checked. In the example above, the partition {+, +, +, ∥−, −, −, +, −, −, +, −} is the best partition, with a purity value of M3=7/11=0.64. The score for the gene is the weighted sum of 0.5*M1+0.25*M2+0.25*M3. The top 50 genes for each subgroup selected by this metric are listed in Tables 23-29. For class prediction all 50 genes were used, unless otherwise stated.

25TABLE 23Genes Selected by Wilkins' for BCR-ABLAbove/AffymetrixGeneReferenceTrain setBelownumberGene NameSymbolnumberscoreMean132319_attumor necrosis factor ligandTNFSF4AL0223100.6354Abovesuperfamily member 4 tax-transcriptionally activatedglycoprotein 1 34 kD237479_atCD72 antigenCD72M549920.6352Below31211_s_atCASP2 and RIPK1 domainCRADDU843880.6265Abovecontaining adaptor with deathdomain437397_atplatelet/endothelial cell adhesionPECAML346570.6161Abovemolecule-1 (PECAM-1) gene533162_atinsulin receptorINSRX021600.6118Below639691_atSH3-containing protein SH3GLB1SH3GLB1AB0079600.6089Above71558_g_atp21/Cdc42/Rac1-activated kinase 1PAK1U241520.6087Aboveyeast Ste20-related834759_atHuman hbc647 mRNA sequenceU684940.6061Above933774_atcaspase 8 apoptosis-related cysteineCASP8X981720.6040Aboveprotease101326_atcaspase 10 apoptosis-relatedCASP10U605190.6021Abovecysteine protease1138312_atDKFZp564O222 from cloneAL0500020.6010AboveDKFZp564O2221235970_g_atM-phase phosphoprotein 9MPHOSPH9N231370.5989Above1341273_atFK506 binding protein 12-FRAP1AL0469400.5989Aboverapamycin associated protein 11440798_s_ata disintegrin and metalloproteinaseADAM10Z485790.5980Abovedomain 101540953_atcalponin 3 acidicCNN3S805620.5972Above161434_atphosphatase and tensin homologPTENU924360.5963Belowmutated in multiple advancedcancers 11738966_atglycoprotein synaptic 2GPSN2AF0389580.5953Above1835991_atSm protein FLSM6AA9179450.5938Above19330_s_attubulin, alpha 1, isoform 44TUBA1HG2259-0.5938AboveHT23482038032_atKIAA0736 gene productKIAA0736AB0182790.5934Above211983_atcyclin D2CCND2X684520.5927Above2236194_atlow density lipoprotein-relatedLRPAP1M639590.5914Belowprotein-associated protein 1 alpha-2-macroglobulin receptor-associated protein 12334460_atperipheral benzodiazepine receptor-PRAX-1AB0145120.5911Aboveassociated protein 1242001_g_atataxia telangiectasia mutatedATMU264550.5910Aboveincludes complementation groups AC and D2531443_atAML1AML1S763460.5896Above2633410_atintegrin alpha 6ITGA6S662130.5896Above2737472_atmannosidase beta A lysosomalMANBAU603370.5887Below2836099_atsplicing factor arginine/serine-richSFRS1M690400.5877Below1 splicing factor 2 alternate splicingfactor2938636_atimmunoglobulin superfamilyISLRAB0031840.5858Abovecontaining leucine-rich repeat3034314_atribonucleotide reductase M1RRM1X595430.5858Belowpolypeptide3136129_atKIAA0397 gene productKIAA0397AB0078570.5858Above3240264_g_atzinc finger protein-like 1ZFPL1AF0018910.5858Above3337399_ataldo-keto reductase family 1AKR1C3D177930.5852Abovemember C3 3-alpha hydroxysteroiddehydrogenase type II3438160_atlymphocyte antigen 75LY75AF0113330.5832Above3541649_atFOXJ2 forkhead factorLOC55810AF0381770.5832Above3636591_attubulin alpha 1 testis specificTUBA1X069560.5832Above3740167_s_atCS box-containing WD proteinLOC55884AF0381870.5832Above382064_g_atexcision repair cross-ERCC5L200460.5832Abovecomplementing rodent repairdeficiency complementation group3939729_atHuman natural killer cell enhancingNKEFBL191850.5829Belowfactor (NKEFB) mRNA, completecds.4038270_atpoly ADP-ribose glycohydrolasePARGAF0050430.5828Below4140613_atuncharacterized hypothalamusHT012AL0317750.5819Belowprotein HT0124239070_atsinged Drosophila like sea urchinSNLU030570.5813Abovefascin homolog like4340782_atshort-chainSDR1AF0617410.5813Abovedehydrogenase/reductase 14434256_atsialyltransferase 9 CMP-NeuAcSIAT9AB0183560.5797Abovelactosylceramide alpha-2 3-sialyltransferase GM3 synthase4541836_atprotein with polyglutamine repeatERPROT213-U948360.5777Abovecalcium ca2 homeostasis21endoplasmic reticulum protein4635681_r_atzinc finger homeobox 1BZFHX1BAB0111410.5759Below4737190_atWAS protein family member 1WASF1D874590.5759Below4832788_atRAN binding protein 92RANBP2D420630.5756Above49828_atprostaglandin E receptor 2 subtypePTGER2U194870.5740AboveEP2 53 kD5038220_atdihydropyrimidine dehydrogenaseDPYDU209380.5737Above

[0143]

26

TABLE 24

Genes Selected by Wilkins' for E2A-PBX1

Above/

Affymetrix

Gene
Reference
Train set
Below

number
Gene Name
Symbol
number
score
Mean

1
32063_at
pre-B-cell leukemia transcription
PBX1
M86546
0.8750
Above

factor 1

2
38994_at
STAT induced STAT inhibitor-2
STATI2
AF037989
0.8252
Below

3
33355_at

Homo sapiens
cDNA FLJ12900 fis
PBX1
AL049381
0.8040
Above

clone NT2RP2004321 (by

CELERA serach of target sequence =

PBX1)

4
40454_at
FAT tumor suppressor Drosophila
FAT
X87241
0.7899
Above

homolog

5
753_at
nidogen 2
NID2
D86425
0.7368
Above

6
717_at
GS3955 protein
GS3955
D87119
0.7306
Above

7
1786_at
c-mer proto-oncogene tyrosine
MERTK
U08023
0.7300
Above

kinase

8
39070_at
singed Drosophila like sea urchin
SNL
U03057
0.7271
Below

fascin homolog like

9
1065_at
fms-related tyrosine kinase 3
FLT3
U02687
0.7160
Below

10
36650_at
cyclin D2
CCND2
D13639
0.7151
Below

11
33513_at
signaling lymphocytic activation
SLAM
U33017
0.7096
Above

molecule

12
33748_at
minor histocompatibility antigen
KIAA0223
D86976
0.7084
Below

HA-1

13
37225_at
KIAA0172 protein
KIAA0172
D79994
0.7033
Above

14
38717_at
DKFZP586A0522 protein
DKFZP586A
AL050159
0.7003
Below

0522

15
854_at
B lymphoid tyrosine kinase
BLK
S76617
0.6982
Above

16
33641_g_at
nuclear factor of kappa light
NFKBIL1
Y14768
0.6975
Below

polypeptide gene enhancer in B-

cells inhibitor-like 1

17
40468_at
KIAA0554 protein
KIAA0554
AB011126
0.6971
Below

18
41266_at
integrin alpha 6
ITGA6
X53586
0.6965
Below

19
36536_at
schwannomin interacting protein 1
SCHIP-1
AF070614
0.6938
Below

20
362_at
protein kinase C zeta
PRKCZ
Z15108
0.6904
Above

21
755_at
inositol 1 4 5-triphosphate receptor
ITPR1
D26070
0.6877
Below

type 1

22
307_at
arachidonate 5-lipoxygenase
ALOX5
J03600
0.6875
Below

23
39614_at
KIAA0802 protein
KIAA0802
AB018345
0.6863
Above

24
1563_s_at
tumor necrosis factor receptor
TNFRSF1A
M58286
0.6837
Below

superfamily member 1A

25
38748_at
adenosine deaminase RNA-specific
ADARB1
U76421
0.6763
Above

B1 homolog of rat RED1

26
41409_at
basement membrane-induced gene
ICB-1
AF044896
0.6757
Below

27
34892_at
tumor necrosis factor receptor
TNFRSF10B
AF016266
0.6726
Below

superfamily member 10b

28
40648_at
c-mer proto-oncogene tyrosine
MERTK
U08023
0.6710
Above

kinase

29
38408_at
transmembrane 4 superfamily
TM4SF2
L10373
0.6667
Below

member 2

30
34583_at
fms-related tyrosine kinase 3
FLT3
U02687
0.6665
Below

31
36900_at
stromal interaction molecule 1
STIM1
U52426
0.6650
Below

32
37625_at
interferon regulatory factor 4
IRF4
U52682
0.6636
Above

33
38340_at
huntingtin interacting protein-1-
KIAA0655
AB014555
0.6609
Above

related

34
1830_s_at
transforming growth factor beta 1
TGFB1
M38449
0.6608
Below

35
37099_at
arachidonate 5-lipoxygenase-
ALOX5AP
AI806222
0.6605
Below

activating protein

36
38254_at
KIAA0882 protein
KIAA0882
AB020689
0.6539
Below

37
37641_at
Human gene for hepatitis C-

D28915
0.6531
Below

associated microtubular aggregate

protein p44, exon 9 and complete

cds.

38
33865_at
adenovirus 5 E1A binding protein
BS69
AA127624
0.6515
Below

39
40729_s_at
nuclear factor of kappa light
NFKBIL1
Y14768
0.6502
Below

polypeptide gene enhancer in B-

cells inhibitor-like 1

40
40113_at
GS3955 protein
GS3955
D87119
0.6476
Above

41
32979_at
GRB2-associated binding protein 1
GAB1
U43885
0.6457
Below

42
36591_at
tubulin alpha 1 testis specific
TUBA1
X06956
0.6427
Below

43
38739_at
v-ets avian erythroblastosis virus
ETS2
AF017257
0.6424
Below

E26 oncogene homolog 2

44
37485_at
fatty-acid-Coenzyme A ligase very
FACVL1
D88308
0.6363
Above

long-chain 1

45
538_at
CD34 antigen
CD34
S53911
0.6326
Below

46
37893_at
protein tyrosine phosphatase non-
PTPN2
AI828880
0.6318
Above

receptor type 2

47
41017_at
myosin-binding protein H
MYBPH
U27266
0.6297
Above

48
37967_at
lymphocyte antigen 117
LY117
AF000424
0.6260
Below

49
37281_at
KIAA0233 gene product
KIAA0233
D87071
0.6250
Below

50
35675_at
vinexin beta SH3-containing
SCAM-1
AF037261
0.6229
Below

adaptor molecule-1

[0144]

27

TABLE 25

Genes selected for Wilkins for Hyperdiploid >50

Above/

Affymetrix

Gene
Reference
Train set
Below

number
Gene Name
Symbol
number
score
Mean

1
39878_at
protocadherin 9
PCDH9
AI524125
0.5838
Below

2
41470_at
Prominin mouse like 1
PROML1
AF027208
0.5616
Above

3
39069_at
AE-binding protein 1
AEBP1
AF053944
0.5423
Below

4
1520_s_at
interleukin 1 beta
IL1B
X04500
0.5399
Above

5
578_at
Human recombination acitivating
RAG2
M94633
0.5208
Below

protein (RAG2) gene, last exon

6
32251_at
hypothetical protein FLJ21174
FLJ21174
AA149307
0.5164
Above

7
40480_s_at
FYN oncogene related to SRC FGR
FYN
M14333
0.5090
Above

YES

8
38604_at
neuropeptide Y
NPY
AI198311
0.5083
Above

9
40903_at
ATPase H transporting lysosomal
APT6M8-9
AL049929
0.5080
Above

vacuolar proton pump membrane

sector associated protein M8-9

10
38968_at
SH3-domain binding protein 5
SH3BP5
AB005047
0.5057
Above

BTK-associated

11
37272_at
inositol 1 4 5-trisphosphate 3-
ITPKB
X57206
0.5025
Below

kinase B

12
35688_g_at
mature T-cell proliferation 1
MTCP1
Z24459
0.5018
Above

13
1488_at
protein tyrosine phosphatase
PTPRK
L77886
0.4977
Below

receptor type K

14
36885_at
spleen tyrosine kinase
SYK
L28824
0.4964
Below

15
1630_s_at
tyrosine kinase syk
syk
HG3730-
0.4913
Below

HT4000

16
38317_at
transcription elongation factor A
TCEAL1
M99701
0.4901
Above

SII like 1

17
38649_at
KIAA0970 protein
KIAA0970
AB023187
0.4898
Below

18
39721_at
ephrin-B1
EFNB1
U09303
0.4895
Above

19
33307_at
kraken-like
BK126B4.1
AL022316
0.4880
Below

20
38518_at
sex comb on midleg Drosophila like 2
SCML2
Y18004
0.4879
Above

21
39402_at
interleukin 1 beta
IL1B
M15330
0.4750
Above

22
36489_at
phosphoribosyl pyrophosphate
PRPS1
D00860
0.4718
Above

synthetase 1

23
37747_at
Human annexin V (ANX5) gene,
(ANX5
U05770
0.4717
Above

exon 13.

24
40200_at
heat shock transcription factor 1
HSF1
M64673
0.4689
Below

25
35940_at
POU domain class 4 transcription
POU4F1
X64624
0.4685
Above

factor 1

26
35727_at
hypothetical protein FLJ20517
FLJ20517
AI249721
0.4675
Below

27
1357_at
ubiquitin specific protease 4 proto-
USP4
U20657
0.4670
Below

oncogene

28
36592_at
prohibitin
PHB
S85655
0.4668
Above

29
37014_at
myxovirus influenza resistance 1
MX1
M33882
0.4635
Above

homolog of murine interferon-

inducible protein p78

30
40891_f_at
DNA segment on chromosome X
DXS9879E
X92896
0.4608
Above

unique 9879 expressed sequence

31
40846_g_at
interleukin enhancer binding factor
ILF3
U10324
0.4605
Below

3 90 Kd

32
41132_r_at
heterogeneous nuclear
HNRPH2
U01923
0.4605
Above

ribonucleoprotein H2 H

33
37280_at
MAD mothers against
MADH1
U59912
0.4595
Below

decapentaplegic Drosophila

homolog 1

34
35939_s_at
POU domain class 4 transcription
POU4F1
L20433
0.4594
Above

factor 1

35
890_at
ubiquitin-conjugating enzyme E2A
UBE2A
M74524
0.4570
Above

RAD6 homolog

36
38738_at
SMT3 suppressor of mif two 3
SMT3H1
X99584
0.4568
Above

yeast homolog 1

37
38458_at
Human cytochrome b5 (CYB5)
CYB5
L39945
0.4552
Above

gene, exon 6 and complete cds.

38
38869_at
KIAA1069 protein
KIAA1069
AB028992
0.4549
Above

39
915_at
interferon-induced protein with
IFIT1
M24594
0.4544
Above

tetratricopeptide repeats 1

40
38408_at
transmembrane 4 superfamily
TM4SF2
L10373
0.4535
Above

member 2

41
39301_at
calpain 3 p94
CAPN3
X85030
0.4533
Below

42
41425_at
Friend leukemia virus integration 1
FLI1
M98833
0.4519
Below

43
2094_s_at
v-fos FBJ murine osteosarcoma
FOS
K00650
0.4514
Above

viral oncogene homolog

44
36605_at
transcription factor 4
TCF4
M74719
0.4497
Above

45
37709_at
DNA segment numerous copies
DXF68S1E
M86934
0.4493
Above

expressed probes GS1 gene

46
36128_at
transmembrane trafficking protein
TMP21
L40397
0.4488
Above

47
171_at
von Hippel-Lindau binding protein 1
VBP1
U56833
0.4473
Above

48
41490_at
phosphoribosyl pyrophosphate
PRPS2
Y00971
0.4466
Above

synthetase 2

49
36536_at
schwannomin interacting protein 1
SCHIP-1
AF070614
0.4448
Above

50
35843_at

Homo sapiens
mRNA cDNA

L40402
0.4443
Above

DKFZp434D0935

[0145]

28

TABLE 26

Genes Selected by Wilkins' for MLL

Above/

Affymetrix

Gene
Reference
Train set
Below

number
Gene Name
Symbol
number
score
Mean

1
39402_at
interleukin 1 beta
IL1B
M15330
0.7355
Below

2
307_at
arachidonate 5-lipoxygenase
ALOX5
J03600
0.7221
Below

3
1389_at
membrane metallo-endopeptidase
MME
J03779
0.7178
Below

neutral endopeptidase

enkephalinase CALLA CD10

4
37280_at
MAD mothers against
MADH1
U59912
0.7021
Below

decapentaplegic Drosophila

homolog 1

5
36650_at
cyclin D2
CCND2
D13639
0.6759
Below

6
37043_at
inhibitor of DNA binding 3
ID3
AL021154
0.6743
Below

dominant negative helix-loop-helix

protein

7
1520_s_at
interleukin 1 beta
IL1B
X04500
0.6689
Below

8
40913_at
ATPase Ca transporting plasma
ATP2B4
W28589
0.6684
Below

membrane 4

9
36536_at
schwannomin interacting protein 1
SCHIP-1
AF070614
0.6554
Below

10
37398_at
platelet/endothelial cell adhesion
PECAM1
AA100961
0.6548
Below

molecule CD31 antigen

11
39114_at
decidual protein induced by
DEPP
AB022718
0.6478
Below

progesterone

12
37967_at
lymphocyte antigen 117
LY117
AF000424
0.6432
Below

13
1325_at
MAD mothers against
MADH1
U59423
0.6421
Below

decapentaplegic Drosophila

homolog 1

14
38336_at
KIAA1013 protein
KIAA1013
AB023230
0.6395
Below

15
577_at
midkine neurite growth-promoting
MDK
M94250
0.6363
Below

factor 2

16
38671_at
KIAA0620 protein
KIAA0620
AB014520
0.6353
Below

17
33412_at
LGALS1 Lectin, galactoside-
LGALS1
AI535946
0.6351
Above

binding, soluble, 1

18
40451_at
hypothetical protein FLJ21434
FLJ21434
AL080203
0.6350
Below

19
36908_at
Human macrophage mannose
MRC1
M93221
0.6290
Below

receptor (MRC1) gene, exon 30.

20
963_at
ligase IV DNA ATP-dependent
LIG4
X83441
0.6282
Below

21
41346_at
like-glycosyltransferase
LARGE
AJ007583
0.6214
Below

22
32207_at
membrane protein palmitoylated 1
MPP1
M64925
0.6155
Below

55 kD

23
2062_at
insulin-like growth factor binding
IGFBP7
L19182
0.6145
Above

protein 7

24
38408_at
transmembrane 4 superfamily
TM4SF2
L10373
0.6137
Below

member 2

25
854_at
B lymphoid tyrosine kinase
BLK
S76617
0.6075
Above

26
32193_at
plexin C1
PLXNC1
AF030339
0.6065
Above

27
35939_s_at
POU domain class 4 transcription
POU4F1
L20433
0.6046
Below

factor 1

28
33705_at
phosphodiesterase 4B cAMP-
PDE4B
L20971
0.5991
Below

specific dunce Drosophila homolog

phosphodiesterase E4

29
34168_at
deoxynucleotidyltransferase
DNTT
M11722
0.5979
Below

terminal

30
36383_at
v-ets avian erythroblastosis virus
ERG
M17254
0.5976
Below

E26 oncogene related

31
38968_at
SH3-domain binding protein 5
SH3BP5
AB005047
0.5976
Below

BTK-associated

32
39263_at
2 5 oligoadenylate synthetase 2
OAS2
M87434
0.5967
Below

33
39329_at
actinin alpha 1
ACTN1
X15804
0.5953
Below

34
34699_at
CD2-associated protein
CD2AP
AL050105
0.5945
Below

35
1267_at
protein kinase C eta
PRKCH
M55284
0.5941
Below

36
35172_at
tyrosylprotein sulfotransferase 2
TPST2
AF049891
0.5937
Below

37
38124_at
midkine neurite growth-promoting
MDK
X55110
0.5936
Below

factor 2

38
33813_at
tumor necrosis factor receptor
TNFRSF1B
AI813532
0.5934
Below

superfamily member 1B

39
34176_at
hypothetical protein from clone 643
LOC57228
AF091087
0.5930
Below

40
39424_at
tumor necrosis factor receptor
TNFRSF14
U70321
0.5930
Below

superfamily member 14 herpesvirus

entry mediator

41
40729_s_at
nuclear factor of kappa light
NFKBIL1
Y14768
0.5905
Below

polypeptide gene enhancer in B-

cells inhibitor-like 1

42
32607_at
brain acid-soluble protein 1
BASP1
AF039656
0.5905
Above

43
38342_at
KIAA0239 protein
KIAA0239
D87076
0.5896
Below

44
32533_s_at
vesicle-associated membrane
VAMP5
AF054825
0.5880
Below

protein 5 myobrevin

45
39330_s_at
actinin alpha 1
ACTN1
M95178
0.5867
Below

46
40519_at
protein tyrosine phosphatase
PTPRC
Y00638
0.5848
Above

receptor type C

47
39338_at
S100 calcium-binding protein A10
S100A10
AI201310
0.5844
Above

annexin II ligand calpactin I light

polypeptide p11

48
35940_at
POU domain class 4 transcription
POU4F1
X64624
0.5824
Below

factor 1

49
39712_at
S100 calcium-binding protein A13
S100A13
AI541308
0.5818
Below

50
39379_at

Homo sapiens
mRNA cDNA

AL049397
0.5811
Above

DKFZp586C1019 from clone

DKFZp586C1019

[0146]

29

TABLE 27

Genes Selected by Wilkins' for Novel Risk Group

Above/

Affymetrix

Gene
Reference
Train set
Below

number
Gene Name
Symbol
number
score
Mean

1
31892_at
protein tyrosine phosphatase
PTPRM
X58288
0.8668
Above

receptor type M

2
41734_at
KIAA0870 protein
KIAA0870
AB020677
0.8614
Below

3
995_g_at
protein tyrosine phosphatase
PTPRM
X58288
0.8505
Above

receptor type M

4
994_at
protein tyrosine phosphatase
PTPRM
X58288
0.7694
Above

receptor type M

5
37967_at
lymphocyte antigen 117
LY117
AF000424
0.7399
Below

6
34676_at
KIAA1099 protein
KIAA1099
AB029022
0.7298
Above

7
41159_at
Clathrin heavy polypeptide Hc
CLTC
D21260
0.7283
Above

8
39728_at
interferon gamma-inducible protein
IFI30
J03909
0.7138
Below

30

9
37542_at
lipoma HMGIC fusion partner-like 2
LHFPL2
D86961
0.7069
Above

10
35350_at
B cell RAG associated protein
BRAG
AB011170
0.7049
Below

11
41438_at
KIAA1451 protein
KIAA1451
AL049923
0.6999
Below

12
34370_at
Archain 1
ARCN1
X81198
0.6999
Below

13
36029_at
chromosome 11 open reading frame 8
C11ORF8
U57911
0.6964
Above

14
37960_at
carbohydrate chondroitin 6/keratan
CHST2
AB014679
0.6947
Above

sulfotransferase 2

15
35869_at
MD-1 RP105-associated
MD-1
AB020499
0.6908
Below

16
36601_at
Vinculin
VCL
M33308
0.6908
Below

17
40775_at
Integral membrane protein 2A
ITM2A
AL021786
0.6879
Above

18
37281_at
KIAA0233 gene product
KIAA0233
D87071
0.6837
Below

19
957_at
Arrestin, beta 2
ARRB2
HG2059-
0.6744
Below

HT2114

20
33284_at
myeloperoxidase
MPO
M19507
0.6712
Below

21
40585_at
adenylate cyclase 7
ADCY7
D25538
0.6712
Below

22
37908_at
guanine nucleotide binding protein
GNG11
U31384
0.6656
Above

11

23
40167_s_at
CS box-containing WD protein
LOC55884
AF038187
0.6581
Below

24
38576_at
H2B histone family member B
H2BFB
AJ223353
0.6576
Below

25
36591_at
tubulin alpha 1 testis specific
TUBA1
X06956
0.6576
Below

26
37712_g_at
MADS box transcription enhancer
MEF2C
S57212
0.6576
Below

factor 2 polypeptide C myocyte

enhancer factor 2C

27
33924_at
KIAA1091 protein
KIAA1091
AB029014
0.6484
Below

28
32724_at
phytanoyl-CoA hydroxylase
PHYH
AF023462
0.6466
Above

Refsum disease

29
33358_at
EST (retina)

W29087
0.6457
Above

30
33740_at
chromosome 1 open reading frame 2
C1ORF2
AF023268
0.6441
Below

31
36588_at
KIAA0810 protein
KIAA0810
AB018353
0.6441
Below

32
38802_at
progesterone binding protein
HPR6.6
Y12711
0.6441
Below

33
38408_at
transmembrane 4 superfamily
TM4SF2
L10373
0.6440
Below

member 2

34
32227_at
proteoglycan 1 secretory granule
PRG1
X17042
0.6409
Below

35
34840_at

Homo sapiens
cDNA FLJ22642 fis

AI700633
0.6409
Below

clone HSI06970

36
1131_at
mitogen-activated protein kinase
MAP2K2
L11285
0.6409
Below

kinase 2

37
33410_at
integrin alpha 6
ITGA6
S66213
0.6391
Above

38
38006_at
CD48 antigen B-cell membrane
CD48
M37766
0.6342
Below

protein

39
33907_at
eukaryotic translation initiation
EIF4G3
AF012072
0.6304
Below

factor 4 gamma 3

40
41273_at
FK506 binding protein 12-
FRAP1
AL046940
0.6304
Below

rapamycin associated protein 1

41
39781_at
insulin-like growth factor-binding
IGFBP4
U20982
0.6301
Below

protein 4

42
39893_at
guanine nucleotide binding protein
GNG7
AB010414
0.6301
Below

G protein gamma 7

43
37326_at
proteolipid protein 2 colonic
PLP2
U93305
0.6267
Below

epithelium-enriched

44
36687_at
cytochrome c oxidase subunit VIIb
COX7B
N50520
0.6266
Below

45
40423_at
KIAA0903 protein
KIAA0903
AB020710
0.6254
Above

46
32542_at
four and a half LIM domains 1
FHL1
AF063002
0.6236
Below

47
33232_at
cysteine-rich protein 1 intestinal
CRIP1
AI017574
0.6211
Below

48
37280_at
MAD mothers against
MADH1
U59912
0.6208
Above

decapentaplegic Drosophila

homolog 1

49
1325_at
MAD mothers against
MADH1
U59423
0.6208
Above

decapentaplegic Drosophila

homolog 1

50
40729_s_at
nuclear factor of kappa light
NFKBIL1
Y14768
0.6199
Below

polypeptide gene enhancer in B-

cells inhibitor-like 1

[0147]

30

TABLE 28

Genes selected by Wilkins' for T-ALL

Above/

Affymetrix

Gene
Reference
Train set
Below

number
Gene Name
Symbol
number
score
Mean

1
38242_at
B cell linker protein
SLP65
AF068180
0.8683
Below

2
37988_at
CD79B antigen immunoglobulin-
CD79B
M89957
0.8422
Below

associated beta

3
1096_g_at
CD19 antigen
CD19
M28170
0.8181
Below

4
39318_at
T-cell leukemia/lymphoma 1A
TCL1A
X82240
0.8128
Below

5
38018_g_at
CD79A antigen immunoglobulin-
CD79A
U05259
0.8127
Below

associated alpha

6
36878_f_at
major histocompatibility complex
HLA-DQB1
M60028
0.8053
Below

class II DQ beta 1

7
38147_at
SH2 domain protein 1A Duncan s
SH2D1A
AL023657
0.8016
Above

disease lymphoproliferative

syndrome

8
35350_at
B cell RAG associated protein
BRAG
AB011170
0.7914
Below

9
38051_at
mal T-cell differentiation protein
MAL
X76220
0.7900
Above

10
266_s_at
CD24 antigen small cell lung
CD24
L33930
0.7867
Below

carcinoma cluster 4 antigen

11
38521_at
CD22 antigen
CD22
X59350
0.7856
Below

12
37344_at
major histocompatibility complex
HLA-DMA
X62744
0.7835
Below

class II DM alpha

13
34033_s_at
leukocyte immunoglobulin-like
LILRA2
AF025531
0.7761
Below

receptor subfamily A with TM

domain member 2

14
36638_at
connective tissue growth factor
CTGF
X78947
0.7755
Below

15
38213_at
galactosidase alpha
GLA
U78027
0.7701
Below

16
41734_at
KIAA0870 protein
KIAA0870
AB020677
0.7693
Below

17
37711_at
MADS box transcription enhancer
MEF2C
S57212
0.7560
Below

factor 2 polypeptide C myocyte

enhancer factor 2C

18
36239_at
POU domain class 2 associating
POU2AF1
Z49194
0.7440
Below

factor 1

19
38319_at
CD3D antigen delta polypeptide
CD3D
AA919102
0.7426
Above

TiT3 complex

20
38894_g_at
neutrophil cytosolic factor 4 40 kD
NCF4
AL008637
0.7422
Below

21
33705_at
phosphodiesterase 4B cAMP-
PDE4B
L20971
0.7414
Below

specific dunce Drosophila homolog

phosphodiesterase E4

22
38017_at
CD79A antigen immunoglobulin-
CD79A
U05259
0.7360
Below

associated alpha

23
41156_g_at
catenin cadherin-associated protein
CTNNA1
U03100
0.7315
Below

alpha 1 102 kD

24
38994_at
STAT induced STAT inhibitor-2
STATI2
AF037989
0.7292
Below

25
37710_at
MADS box transcription enhancer
MEF2C
L08895
0.7283
Below

factor 2 polypeptide C myocyte

enhancer factor 2C

26
41155_at
catenin cadherin-associated protein
CTNNA1
U03100
0.7278
Below

alpha 1 102 kD

27
40570_at
forkhead box O1A
FOXO1A
AF032885
0.7258
Below

rhabdomyosarcoma

28
34224_at
fatty acid desaturase 3
FADS3
AC004770
0.7254
Below

29
38604_at
neuropeptide Y
NPY
AI198311
0.7212
Below

30
36773_f_at
major histocompatibility complex
HLA-DQB1
M81141
0.7197
Below

class II DQ beta 1

31
32562_at
endoglin Osler-Rendu-Weber
ENG
X72012
0.7180
Below

syndrome 1

32
36502_at
PFTAIRE protein kinase 1
PFTK1
AB020641
0.7179
Below

33
37180_at
phospholipase C gamma 2
PLCG2
X14034
0.7114
Below

phosphatidylinositol-specific

34
38893_at
neutrophil cytosolic factor 4 40 kD
NCF4
AL008637
0.7100
Below

35
387_at
cyclin-dependent kinase 9 CDC2-
CDK9
X80230
0.7024
Below

related kinase

36
32035_at
Human MHC class II HLA-

M16942
0.6992
Below

DRw53-associated glycoprotein

beta-chain mRNA complete cds

37
41153_f_at

Homo sapiens
alphaE-catenin
CTNNA1
AF102803
0.6976
Below

(CTNNA1) gene

38
40780_at
C-terminal binding protein 2
CTBP2
AF016507
0.6976
Below

39
40775_at
integral membrane protein 2A
ITM2A
AL021786
0.6952
Above

40
39402_at
interleukin 1 beta
IL1B
M15330
0.6945
Below

41
38522_s_at
CD22 antigen
CD22
X52785
0.6945
Below

42
41166_at
immunoglobulin heavy constant mu
IGHM
X58529
0.6941
Below

43
36937_s_at
PDZ and LIM domain 1 elfin
PDLIM1
U90878
0.6937
Below

44
38833_at
Human mRNA for SB classII

X00457
0.6925
Below

histocompatibility antigen alpha-

chain

45
2047_s_at
junction plakoglobin
JUP
M23410
0.6920
Below

46
36277_at
Human membran protein (CD3-
CD3E
M23323
0.6899
Above

epsilon) gene, exon 9.

47
40688_at
linker for activation of T cells
LAT
AJ223280
0.6898
Above

48
39389_at
CD9 antigen p24
CD9
M38690
0.6879
Below

49
33162_at
Insulin receptor
INSR
X02160
0.6879
Below

50
31891_at
chitinase 3-like 2
CHI3L2
U58515
0.6872
Above

[0148]

31

TABLE 29

Genes Selected by Wilkins' for TEL-AML1

Above/

Affymetrix

Gene
Reference
Train set
Below

number
Gene Name
Symbol
number
score
Mean

1
37780_at
Piccolo presynaptic cytomatrix
PCLO
AB011131
0.7121
Above

protein

2
38203_at
potassium intermediate/small
KCNN1
U69883
0.7086
Above

conductance calcium-activated

channel subfamily N member 1

3
36524_at
Rho guanine nucleotide exchange
ARHGEF4
AB029035
0.6782
Above

factor GEF 4

4
38578_at
tumor necrosis factor receptor
TNFRSF7
M63928
0.6718
Above

superfamily member 7

5
32730_at

Homo sapiens
mRNA for KIAA1750

AL080059
0.6616
Above

protein partial cds

6
34194_at

Homo sapiens
cDNA FLJ21697 fis

AL049313
0.6518
Above

clone COL09740

7
40272_at
collapsin response mediator protein 1
CRMP1
D78012
0.6160
Above

8
41819_at
FYN-binding protein FYB-120/130
FYB
U93049
0.6058
Above

9
1488_at
protein tyrosine phosphatase receptor
PTPRK
L77886
0.6056
Above

type K

10
35665_at
phosphoinositide-3-kinase class 3
PIK3C3
Z46973
0.6022
Above

11
35614_at
transcription factor-like 5 basic helix-
TCFL5
AB012124
0.5983
Above

loop-helix

12
36008_at
protein tyrosine phosphatase type IVA
PTP4A3
AF041434
0.5976
Above

member 3

13
35362_at
Myosin X
MYO10
AB018342
0.5964
Above

14
37908_at
guanine nucleotide binding protein 11
GNG11
U31384
0.5888
Above

15
39329_at
Actinin alpha 1
ACTN1
X15804
0.5840
Below

16
1936_s_at
proto-oncogene c-myc, alt. transcript

HG3523-
0.5761
Below

3, ORF 114

HT4899

17
33690_at

Homo sapiens
mRNA cDNA
DKFZp434A202
AL080190
0.5725
Above

DKFZp434A202

18
39389_at
CD9 antigen p24
CD9
M38690
0.5684
Below

19
37343_at
inositol 1 4 5-triphosphate receptor
ITPR3
U01062
0.5642
Above

type 3

20
1299_at
telomeric repeat binding factor 2
TERF2
X93512
0.5585
Above

21
38652_at
hypothetical protein FLJ20154
FLJ20154
AF070644
0.5563
Above

22
38763_at
(clone D21-1) L-iditol-2

L29254
0.5535
Below

dehydrogenase gene

23
37724_at
v-myc avian myelocytomatosis viral
MYC
V00568
0.5506
Below

oncogene homolog

24
36937_s_at
PDZ and LIM domain 1 elfin
PDLIM1
U90878
0.5506
Below

25
1325_at
MAD mothers against
MADH1
U59423
0.5482
Above

decapentaplegic Drosophila homolog 1

26
41549_s_at
adaptor-related protein complex 1
AP1S2
AF091077
0.5474
Below

sigma 2 subunit

27
39827_at
hypothetical protein
FLJ20500
AA522530
0.5471
Below

28
32724_at
phytanoyl-CoA hydroxylase Refsum
PHYH
AF023462
0.5459
Above

disease

29
31786_at
Sam68-like phosphotyrosine protein
T-STAR
AF051321
0.5403
Above

T-STAR

30
38570_at
major histocompatibility complex
HLA-DOB
X03066
0.5384
Above

class II DO beta

31
39330_s_at
actinin alpha 1
ACTN1
M95178
0.5375
Below

32
36493_at
lymphocyte-specific protein 1
LSP1
M33552
0.5356
Below

33
574_s_at
caspase 1 apoptosis-related cysteine
CASP1
M87507
0.5336
Below

protease interleukin 1 beta convertase

34
32224_at
KIAA0769 gene product
KIAA0769
AB018312
0.5326
Above

35
1077_at
recombination activating gene 1
RAG1
M29474
0.5302
Above

36
37280_at
MAD mothers against
MADH1
U59912
0.5283
Above

decapentaplegic Drosophila homolog 1

37
41200_at
CD36 antigen collagen type I receptor
CD36L1
Z22555
0.5261
Above

thrombospondin receptor like 1

38
36009_at
hypothetical protein
CL683
AF091092
0.5259
Below

39
36933_at
N-myc downstream regulated
NDRG1
D87953
0.5254
Below

40
1126_s_at
Human cell surface glycoprotein
CD44
L05424
0.5232
Below

CD44 (CD44) gene, 3′ end of long

tailed isoform.

41
39824_at
ESTs

AI391564
0.5231
Above

42
38078_at
filamin B beta actin-binding protein-
FLNB
AF042166
0.5208
Below

278

43
38127_at
syndecan 1
SDC1
Z48199
0.5199
Above

44
32941_at
interferon consensus sequence
ICSBP1
M91196
0.5195
Below

binding protein 1

45
37276_at
IQ motif containing GTPase
IQGAP2
U51903
0.5191
Below

activating protein 2

46
34768_at
DKFZP564E1962 protein
DKFZP564
AL080080
0.5184
Below

E1962

47
39781_at
insulin-like growth factor-binding
IGFBP4
U20982
0.5173
Below

protein 4

48
37918_at
integrin beta 2 antigen CD18 p95
ITGB2
M15395
0.5162
Below

lymphocyte function-associated

antigen 1 macrophage antigen 1 mac-

1 beta subunit

49
41490_at
phosphoribosyl pyrophosphate
PRPS2
Y00971
0.5155
Below

synthetase 2

50
41814_at
fucosidase alpha-L-1 tissue
FUCA1
M29877
0.5101
Above

[0149] 5. SOM/DAV

[0150] The 10,991 probe sets that passed the variation filter were used for subsequent selection of discriminating genes using the self-organizing map (SOM) and discriminant analysis with variance (DAV) programs in the GeneMaths software package (version 1.5, Applied Maths, Belgium). The subgroups for which genes were selected included T-lineage ALL, TEL-AML1, E2A-PBX1, MLL rearrangement, BCR-ABL, hyperdiploid ALL (chromosomal number >50) and the novel subgroup described in the text of the paper. The target number of total genes chosen by each algorithm was 500.

[0151] The SOM analysis was performed using 30×18 node format to enable an optimal number of genes per node (˜20 genes per node). Nodes that contained genes whose expression varied more than 2-fold from the mean in more than 70% of the samples in a particular subgroup were chosen. A total of 451 genes were chosen using the SOM algorithm and 443 genes using the DAV algorithm. The combined gene sets contained 755 unique genes, of which 185 were present in both subsets. 2-D hierarchical clustering of the genes and samples were performed using Pearson's correlation coefficient as the metric and unweighted pair group method using arithmetic averages (UPGMA). Approximately 10% of the genes that were found to have correlation coefficients less than 0.7 in each branch of the dendrogram were removed and the process was repeated reiteratively until the correlation coefficient for all genes within a branch was >0.7, or until the removal of additional gene resulted in a deterioration of the class distinction as indicated by inappropriate clustering of cases. Through this approach a subset of 215 genes were selected that optimally separated the 7 subgroups. These genes are listed in Tables 30-36. The selection of genes by this approach does not provide for a ranking. For class prediction between 20 and 30 genes were used for each genetic subgroup, unless otherwise stated.

32TABLE 30Genes selected by DAV-SOM for BCR-ABLAbove/AffymetrixReferenceBelownumberGene NameGeneSymbolnumberMean139250_atnephroblastoma overexpressed geneNOVX96584Above237600_atextracellular matrix protein 1ECM1U68186Above338312_atDKFZp564O222 from cloneAL050002AboveDKFZp564O222438342_atKIAA0239 proteinKIAA0239D87076Above539712_atS100 calcium-binding protein A13S100A13AI541308Above639730_atv-ab1 Abelson murine leukemia viralABL1X16416Aboveoncogene homolog 1739781_atInsulin-like growth factor-binding protein 4IGFBP4U20982Above840051_atTRAM-like proteinKIAA0057D31762Above940504_atparaoxonase 2PON2AF001601Above1033362_atCdc42 effector protein 3CEP3AF094521Above1133404_atadenylyl cyclase-associated protein 2CAP2U02390Above1234362_atsolute carrier family 2 facilitated glucoseSLC2A5M55531Abovetransporter member 51336591_atTubulin alpha 1 testis specificTUBA1X06956Above1438077_atcollagen type VI alpha 3COL6A3X52022Above1540196_atHYA22 proteinHYA22D88153Above161911_s_atGrowth arrest and DNA-damage-GADD45AM60974Aboveinducible alpha171702_atinterleukin 2 receptor alphaIL2RAX01057Above181635_atHuman proto-oncogene tyrosine-proteinABLU07563Abovekinase (ABL) gene, exon 1a and exons 2-10,complete cds.191636_g_atHuman proto-oncogene tyrosine-proteinABLU07563Abovekinase (ABL) gene, exon 1a and exons 2-10,complete cds.201326_atCaspase 10 apoptosis-related cysteineCASP10U60519Aboveprotease21330_s_atTubulin, alpha 1, isoform 44TUBA1HG2259-AboveHT2348

[0152]

33

TABLE 31

Genes selected by DAV-SOM for E2A-PBX1

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
33513_at
signaling lymphocytic activation molecule
SLAM
U33017
Above

2
37479_at
CD72 antigen
CD72
M54992
Above

3
37485_at
fatty-acid-Coenzyme A ligase very long-
FACVL1
D88308
Above

chain 1

4
39614_at
KIAA0802 protein
KIAA0802
AB018345
Above

5
39929_at
KIAA0922 protein
KIAA0922
AB023139
Above

6
40648_at
c-mer proto-oncogene tyrosine kinase
MERTK
U08023
Above

7
41017_at
Myosin-binding protein H
MYBPH
U27266
Above

8
41425_at
Friend leukemia virus integration 1
FLI1
M98833
Above

9
41862_at
KIAA0056 protein
KIAA0056
D29954
Above

10
32063_at
pre-B-cell leukemia transcription factor 1
PBX1
M86546
Above

11
37225_at
KIAA0172 protein
KIAA0172
D79994
Above

12
38285_at
mu-crystallin gene

AF039397
Above

13
38286_at
KIAA1071 protein
KIAA1071
AB028994
Above

14
38340_at
huntingtin interacting protein-1-related
KIAA0655
AB014555
Above

15
39379_at
cDNA DKFZp586C1019 from clone

AL049397
Above

DKFZp586C1019

16
39402_at
interleukin 1 beta
IL1B
M15330
Above

17
40454_at
FAT tumor suppressor Drosophila homolog
FAT
X87241
Above

18
41139_at
melanoma antigen family D 1
MAGED1
W26633
Above

19
41146_at
ADP-ribosyltransferase NAD poly ADP-
ADPRT
J03473
Above

ribose polymerase

20
33355_at

Homo sapiens
cDNA FLJ12900 fis clone

AL049381
Above

NT2RP2004321

21
34783_s_at
BUB3 budding uninhibited by
BUB3
AF047473
Above

benzimidazoles 3 yeast homolog

22
36179_at
mitogen-activated protein kinase-activated
MAPKAPK2
U12779
Above

protein kinase 2

23
36589_at
aldo-keto reductase family 1 member B1
AKR1B1
X15414
Above

aldose reductase

24
38393_at
KIAA0247 gene product
KIAA0247
D87434
Above

25
38438_at
Nuclear factor of kappa light polypeptide
NFKB1
M58603
Above

gene enhancer in B-cells 1 p105

26
1786_at
c-mer proto-oncogene tyrosine kinase
MERTK
U08023
Above

27
1520_s_at
interleukin 1 beta
IL1B
X04500
Above

28
1287_at
ADP-ribosyltransferase NAD poly ADP-
ADPRT
J03473
Above

ribose polymerase

29
854_at
B lymphoid tyrosine kinase
BLK
S76617
Above

30
753_at
Nidogen 2
NID2
D86425
Above

31
430_at
nucleoside phosphorylase
NP
X00737
Above

32
362_at
Protein kinase C zeta
PRKCZ
Z15108
Above

[0153]

34

TABLE 32

Genes selected by DAV/SOM for Hyperdiploid >50

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
36795_at
prosaposin variant Gaucher disease and
PSAP
J03077
Above

variant metachromatic leukodystrophy

2
38242_at
B cell linker protein
SLP65
AF068180
Above

3
38518_at
sex comb on midleg Drosophila like 2
SCML2
Y18004
Above

4
39628_at
RAB9 member RAS oncogene family
RAB9
U44103
Above

5
31863_at
KIAA0179 protein
KIAA0179
D80001
Above

6
33228_g_at
interleukin 10 receptor beta
IL10RB
AI984234
Above

7
33753_at
KIAA0666 protein
KIAA0666
AB014566
Above

8
37543_at
Rac/Cdc42 guanine exchange factor GEF 6
ARHGEF6
D25304
Above

9
38968_at
SH3-domain binding protein 5 BTK-
SH3BP5
AB005047
Above

associated

10
39039_s_at
CGI-76 protein
LOC51632
AI557497
Above

11
39329_at
Actinin alpha 1
ACTN1
X15804
Above

12
39389_at
CD9 antigen p24
CD9
M38690
Above

13
32207_at
membrane protein palmitoylated 1 55 kD
MPP1
M64925
Above

14
32236_at
ubiquitin-conjugating enzyme E2G 2
UBE2G2
AF032456
Above

homologous to yeast UBC7

15
32251_at
hypothetical protein FLJ21174
FLJ21174
AA149307
Above

16
35764_at
chromosome X open reading frame 5
OFD1
Y15164
Above

17
36620_at
superoxide dismutase 1 soluble
SOD1
X02317
Above

amyotrophic lateral sclerosis 1 adult

18
36937_s_at
PDZ and LIM domain 1 elfin
PDLIM1
U90878
Above

19
37326_at
proteolipid protein 2 colonic epithelium-
PLP2
U93305
Above

enriched

20
37350_at
clone 889N15 on chromosome Xq22.1-22.3.
PSMD10
AL031177
Above

Contains part of the gene for a novel

protein similar to X. laevis Cortical

Thymocyte Marker CTX

21
38738_at
SMT3 suppressor of mif two 3 yeast
SMT3H1
X99584
Above

homolog 1

22
39168_at
Ac-like transposable element
ALTE
AB018328
Above

23
40903_at
ATPase H transporting lysosomal vacuolar
APT6M8-9
AL049929
Above

proton pump membrane sector associated

protein M8-9

24
32572_at
ubiquitin specific protease 9 X chromosome
USP9X
X98296
Above

Drosophila fat facets related

25
1065_at
fms-related tyrosine kinase 3
FLT3
U02687
Above

26
306_s_at
high-mobility group nonhistone
HMG14
J02621
Above

chromosomal protein 14

[0154]

35

TABLE 33

Genes selected by DAV/SOM for MLL

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
31492_at
Muscle specific gene
M9
AB019392
Above

2
36777_at
DNA segment on chromosome 12 unique
D12S2489E
AJ001687
Above

2489 expressed sequence

3
39301_at
Calpain 3 p94
CAPN3
X85030
Below

4
41448_at
Homeo box A4
HOXA4
AC004080
Above

5
39424_at
tumor necrosis factor receptor superfamily
TNFRSF14
U70321
Below

member 14 herpesvirus entry mediator

6
40076_at
Tumor protein D52-like 2
TPD52L2
AF004430
Above

7
40493_at
Human cell surface glycoprotein CD44
CD44
L05424
Above

(CD44) gene, 3′ end of long tailed isoform.

8
40506_s_at

Homo sapiens
polyadenylate binding

U75686
Above

protein mRNA, complete cds.

9
40514_at
hypothetical 43.2 Kd protein
LOC51614
AF091085
Above

10
40763_at
Meis1 mouse homolog
MEIS1
U85707
Above

11
40797_at
a disintegrin and metalloproteinase domain
ADAM10
AF009615
Above

10

12
40798_s_at
a disintegrin and metalloproteinase domain
ADAM10
Z48579
Above

10

13
41747_s_at
myocyte-specific enhancer factor 2A
MEF2A
U49020
Above

(MEF2A) gene

14
32193_at
Plexin C1
PLXNC1
AF030339
Above

15
32215_i_at
KIAA0878 protein
KIAA0878
AB020685
Above

16
33412_at
LGALS1 Lectin, galactoside-binding,
LGALS1
AI535946
Above

soluble, 1 (galectin 1)

17
34306_at
muscleblind Drosophila like
MBNL
AB007888
Above

18
34785_at
KIAA1025 protein
KIAA1025
AB028948
Above

19
35298_at
eukaryotic translation initiation factor 3
EIF3S7
U54558
Above

subunit 7 zeta 66/67 kD

20
36690_at
Nuclear receptor subfamily 3 group C
NR3C1
M10901
Above

member 1

21
37675_at
solute carrier family 25 mitochondrial
SLC25A3
X60036
Above

carrier phosphate carrier member 3

22
38391_at
capping protein actin filament gelsolin-like
CAPG
M94345
Above

23
38413_at
defender against cell death 1
DAD1
D15057
Above

24
39110_at
eukaryotic translation initiation factor 4B
EIF4B
X55733
Above

25
39867_at
Tu translation elongation factor
TUFM
S75463
Above

mitochondrial

26
2062_at
Insulin-like growth factor binding protein 7
IGFBP7
L19182
Above

27
2036_s_at
CD44 antigen homing function and Indian
CD44
M59040
Above

blood group system

28
1914_at
Cyclin A1
CCNA1
U66838
Above

29
1327_s_at
mitogen-activated protein kinase kinase
MAP3K5
U67156
Above

kinase 5

30
1126_s_at
Human cell surface glycoprotein CD44
CD44
L05424
Above

(CD44) gene, 3′ end of long tailed isoform.

31
1102_s_at
Nuclear receptor subfamily 3 group C
NR3C1
M10901
Above

member 1

32
873_at
homeo box A5
HOXA5
M26679
Above

33
706_at
Glucocorticoid receptor, beta

HG4582-
Above

HT4987

34
657_at
protocadherin gamma subfamily C 3
PCDHGC3
L11373
Above

[0155]

36

TABLE 34

Genes selected by DAV/SOM for Novel Class

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
33137_at
latent transforming growth factor beta
LTBP4
Y13622
Above

binding protein 4

2
38081_at
leukotriene A4 hydrolase
LTA4H
J03459
Above

3
38661_at
seb4D
HSRNASEB
X75314
Above

4
39878_at
protocadherin 9
PCDH9
AI524125
Above

5
35260_at
KIAA0867 protein
MONDOA
AB020674
Above

6
1373_at
transcription factor 3 E2A immunoglobulin
TCF3
M31523
Above

enhancer binding factors E12/E47

7
35177_at
KIAA0725 protein
KIAA0725
AB018268
Above

8
38618_at
Human PAC clone RP3-515N1 from
LIMK2
AC002073
Above

22q11.2-q22

9
34947_at
phorbolin-like protein MDS019
MDS019
AA442560
Above

10
40692_at
transducin-like enhancer of split 4 homolog
TLE4
M99439
Above

of Drosophila E sp1

11
38364_at
BCE-1 protein
BCE-1
AF068197
Above

12
37960_at
carbohydrate chondroitin 6/keratan
CHST2
AB014679
Above

sulfotransferase 2

13
994_at
Protein tyrosine phosphatase receptor type M
PTPRM
X58288
Above

14
31892_at
Protein tyrosine phosphatase receptor type M
PTPRM
X58288
Above

15
995_g_at
Protein tyrosine phosphatase receptor type M
PTPRM
X58288
Above

16
41073_at
G protein-coupled receptor 49
GPR49
AI743745
Above

17
41708_at
KIAA1034 protein
KIAA1034
AB028957
Above

18
34376_at
protein kinase cAMP-dependent catalytic
PKIG
AB019517
Below

inhibitor gamma

19
37978_at
quinolinate phosphoribosyltransferase
QPRT
D78177
Below

nicotinate-nucleotide pyrophosphorylase

carboxylating

20
38717_at
DKFZP586A0522 protein
DKFZP586A0522
AL050159
Below

21
33999_f_at
Human L2-9 transcript of unrearranged

X58398
Above

immunoglobulin V H 5 pseudogene

22
36181_at
LIM and SH3 protein 1
LASP1
X82456
Below

23
41202_s_at
conserved gene amplified in osteosarcoma
OS4
AF000152
Above

24
41138_at
Antigen identified by monoclonal
MIC2
M16279
Below

antibodies 12E7 F21 and O13

25
40771_at
Moesin
MSN
Z98946
Above

26
39070_at
singed Drosophila like sea urchin fascin
SNL
U03057
Below

homolog like

27
32562_at
endoglin Osler-Rendu-Weber syndrome 1
ENG
X72012
Below

28
36536_at
schwannomin interacting protein 1
SCHIP-1
AF070614
Below

29
36650_at
cyclin D2
CCND2
D13639
Below

30
39756_g_at
X-box binding protein 1
XBP1
Z93930
Above

31
34168_at
deoxynucleotidyltransferase terminal
DNTT
M11722
Above

32
1389_at
membrane metallo-endopeptidase neutral
MME
J03779
Below

endopeptidase enkephalinase CALLA

CD10

33
41213_at
peroxiredoxin 1
PRDX1
X67951
Above

34
36571_at
Topoisomerase DNA II beta 180 kD
TOP2B
X68060
Above

35
253_g_at
clone GPCR W G protein-linked receptor

L42324
Below

gene (GPCR) gene, 5′ end of cds.

36
252_at
clone GPCR W G protein-linked receptor

L42324
Above

gene (GPCR) gene, 5′ end of cds.

37
2087_s_at
cadherin 11 type 2 OB-cadherin osteoblast
CDH11
D21254
Above

38
36976_at
cadherin 11 type 2 OB-cadherin osteoblast
CDH11
D21255
Above

[0156]

37

TABLE 35

Genes selected by DAV/SOM for T-ALL

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
35016_at
Human Ia-associated invariant gamma-

M13560
Below

chain gene, exon 8, clones lambda-y(1, 2, 3).

2
36277_at
membrane protein (CD3-epsilon) gene
CD3E
M23323
Above

3
38147_at
SH2 domain protein 1A Duncan s disease
SH2D1A
AL023657
Above

lymphoproliferative syndrome

4
38949_at
protein kinase C theta
PRKCQ
L01087
Above

5
32649_at
transcription factor 7 T-cell specific HMG-
TCF7
X59871
Above

box

6
33238_at
Human T-lymphocyte specific protein
LCK
U23852
Above

tyrosine kinase p56lck (LCK) aberrant

mRNA, complete cds.

7
35643_at
nucleobindin 2
NUCB2
X76732
Above

8
36473_at
ubiquitin specific protease 20
USP20
AB023220
Above

9
38319_at
CD3D antigen delta polypeptide TiT3
CD3D
AA919102
Above

complex

10
39709_at
selenoprotein W 1
SEPW1
U67171
Above

11
40775_at
integral membrane protein 2A
ITM2A
AL021786
Above

12
32794_g_at
T cell receptor beta locus
TRB
X00437
Above

13
37039_at
major histocompatibility complex class II
HLA-DRA
J00194
Below

DR alpha

14
38051_at
mal T-cell differentiation protein
MAL
X76220
Above

15
38095_i_at
major histocompatibility complex class II
HLA-DPB1
M83664
Below

DP beta 1

16
38096_f_at
major histocompatibility complex class II
HLA-DPB1
M83664
Below

DP beta 1

17
38415_at
protein tyrosine phosphatase type IVA
PTP4A2
U14603
Above

member 2

18
38833_at
Human mRNA for SB classII

X00457
Below

histocompatibility antigen alpha-chain

19
2059_s_at
lymphocyte-specific protein tyrosine kinase
LCK
M36881
Above

20
1241_at
protein tyrosine phosphatase type IVA
PTP4A2
U14603
Above

member 2

21
1105_s_at
T cell receptor beta locus
TRB
M12886
Above

[0157]

38

TABLE 36

Genes selected by DAV/SOM for TEL-AML1

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
31508_at
upregulated by 1, 25-dihydroxyvitamin D-3
VDUP1
S73591
Above

2
33690_at
cDNA DKFZp434A202 from clone

AL080190
Above

DKFZp434A202

3
34481_at
vav proto-oncogene, exon 27, and complete
VAV
AF030227
Above

cds.

4
36239_at
POU domain class 2 associating factor 1
POU2AF1
Z49194
Above

5
37470_at
Leukocyte-associated Ig-like receptor 1
LAIR1
AF013249
Above

6
38203_at
Potassium intermediate/small conductance
KCNN1
U69883
Above

calcium-activated channel subfamily N

member 1

7
38570_at
major histocompatibility complex class II
HLA-DOB
X03066
Above

DO beta

8
38578_at
tumor necrosis factor receptor superfamily
TNFRSF7
M63928
Above

member 7

9
38906_at
spectrin alpha erythrocytic 1 elliptocytosis 2
SPTA 1
M61877
Above

10
40729_s_at
nuclear factor of kappa light polypeptide
NFKBIL1
Y14768
Above

gene enhancer in B-cells inhibitor-like 1

11
40745_at
adaptor-related protein complex 1 beta 1
AP1B1
L13939
Above

subunit

12
41097_at
telomeric repeat binding factor 2
TERF2
AF002999
Above

13
41381_at
KIAA0308 protein
KIAA0308
AB002306
Above

14
41442_at
core-binding factor runt domain alpha
CBFA2T3
AB010419
Above

subunit 2 translocated to 3

15
31898_at
KIAA0212 gene product
KIAA0212
D86967
Above

16
32660_at
KIAA0342 gene product
KIAA0342
AB002340
Above

17
34194_at
cDNA FLJ21697 fis clone COL09740

AL049313
Above

18
35614_at
transcription factor-like 5 basic helix-loop-
TCFL5
AB012124
Above

helix

19
35665_at
Phosphoinositide-3-kinase class 3
PIK3C3
Z46973
Above

20
36008_at
protein tyrosine phosphatase type IVA
PTP4A3
AF041434
Above

member 3

21
36524_at
Rho guanine nucleotide exchange factor
ARHGEF4
AB029035
Above

GEF 4

22
36537_at
Rho-specific guanine nucleotide exchange
P114-RHO-
AB011093
Above

factor p114
GEF

23
37280_at
MAD mothers against decapentaplegic
MADH1
U59912
Above

Drosophila homolog 1

24
38652_at
hypothetical protein FLJ20154
FLJ20154
AF070644
Above

25
41200_at
CD36 antigen collagen type I receptor
CD36L1
Z22555
Above

thrombospondin receptor like 1

26
32224_at
KIAA0769 gene product
KIAA0769
AB018312
Above

27
36985_at
isopentenyl-diphosphate delta isomerase
IDI1
X17025
Above

28
38124_at
midkine neurite growth-promoting factor 2
MDK
X55110
Above

29
39824_at
ESTs

AI391564
Above

30
40570_at
forkhead box O1A rhabdomyosarcoma
FOXO1A
AF032885
Above

31
41498_at
KIAA0911 protein
KIAA0911
AB020718
Above

32
41814_at
fucosidase alpha-L- 1 tissue
FUCA1
M29877
Above

33
32579_at
SWI/SNF related matrix associated actin
SMARCA4
D26156
Above

dependent regulator of chromatin subfamily

a member 4

34
33162_at
insulin receptor
INSR
X02160
Above

35
1779_s_at
pim-1 oncogene
PIM1
M16750
Above

36
1488_at
protein tyrosine phosphatase receptor type K
PTPRK
L77886
Above

37
1325_at
MAD mothers against decapentaplegic
MADH1
U59423
Above

Drosophila homolog 1

38
1336_s_at
protein kinase C beta 1
PRKCB1
X06318
Above

39
1299_at
Telomeric repeat binding factor 2
TERF2
X93512
Above

40
1217_g_at
protein kinase C beta 1
PRKCB1
X07109
Above

41
1077_at
recombination activating gene 1
RAG1
M29474
Above

42
932_i_at
zinc finger protein 91 HPF7 HTF10
ZNF91
L11672
Above

43
880_at
FK506-binding protein 1A 12 kD
FKBP1A
M34539
Above

44
755_at
inositol 1 4 5-triphosphate receptor type 1
ITPR1
D26070
Above

45
577_at
midkine neurite growth-promoting factor 2
MDK
M94250
Above

46
160029_at
protein kinase C beta 1
PRKCB1
X07109
Above

[0158] C. Comparison of Genes Selected by the Different Metrics

[0159] There is a high degree of overlap between the genes chosen by the various metrics, however the top ranked genes for each metric differ. Despite this, the top genes selected by the various metrics are all able to accurately identify the leukemia risk groups as detailed below. As a result, a limited number of genes can be used to accurately identify the genetic subtypes and one can use non-overlapping lists and still achieve high prediction accuracy. Thus, there are many genes that are distinct discriminators of these seven risk groups, and one need only to use a small subset of these in a supervised learning algorithm to accurately identify a case as belonging to the genetic subtype.

[0160] D. Decision Tree for the Diagnosis of Genetic Subtypes

[0161] Classification was approached using a decision tree format, in which the first decision was T-ALL versus B-lineage (non-T-ALL). Within the B-lineage subset, cases were then sequentially classified into the known risk groups characterized by the presence of E2A-PBX1, TEL-AML1, BCR-ABL, MLL chimeric genes, and lastly hyperdiploid>50 chromosomes. Cases not assigned to one of these classes were left unassigned. Classification was performed using the supervised learning algorithms described below.

[0162] E. Description of Supervised Learning Algorithms

[0163] An analysis of the profiles was performed using alinear classifier, C4.5, and a variety of different non-linear classifiers. The non-linear classifiers consistently outperformed the linear classifier. Therefore, only the description and data from non-linear classifiers are included below.

[0164] 1. Support Vector Machine (SVM)

[0165] Support vector machine (SVM) selects a small number of critical boundary instances from each class and builds a linear discriminant function that separates them as widely as possible (Witten and Frank, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementation, Morgan Kaufmann, 1999, herein incorporated by reference). In the case where no linear separation is possible, the technique of “kernel” is used to automatically inject the training instances into a higher dimensional space and a separator is learned in that space. The Weka version of SVM developed at the University of Waikato of New Zealand (www.cs.waikato.ac.nz/ml/weka), which implements Platt's sequence minimal optimization algorithm for training a support vector classifier using polynomial kernels was used (Platt, “Fast Training of Support Vector Machines Using Sequential Minimal Optimization,” Advances in Kernel Methods—Support Vector Learning, Schlkpof et al., eds., MIT Press, 1998, herein incorporated by reference).

[0166] 2. Prediction by Collective Likelihood of Emerging Patterns (PCL)

[0167] Emerging patterns (EPs) are a notion used in data mining to discover sharp differences between two classes of data (Dong and Li, “Efficient Mining of Emerging Patterns: Discovering Trends and Differences,” Proc. 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 43-52 (1999), herein incorporated by reference). An EP is a pattern—the expression level of several genes in our case—whose frequency increases significantly from one class of samples to another class. In particular, the most general patterns that have infinite growth in the sense that their frequency in one class is 0% and in another class is greater than 0% and none of their proper subpatterns are EPs were identified. These EPs can then be combined into reliable rules for subtype prediction. Three earlier methods for classification based on EPs are JEP(Li et al. (2001) Knowledge and Information System 3:131-45, herein incorporated by reference), DeEPs (Li et al., “DeEPs: Instance-based Classification by Emerging Patterns,” Proc. 4th European Conference on Principles and Practice of Knowledge Discovery in Databases, pp. 191-200, 2000, herein incorporated by reference), and CAEP (Dong et al., “CAEP: Classification by Aggregation Emerging Patterns,” Proc. 2nd International Conference on Discovery Science, pages 30-42, 1999, herein incorporated by reference).

[0168] In this analysis an original variation in the spirit of JEP but with a different manner of aggregating EPs was used. Given two training data sets Dp and Dn and a testing sample T, the first phase was to discover EPs from Dp and Dn. Denote the EPs of Dp, in descending order of frequency, as TopEPp1, . . . , TopEPpi, and those of Dn as TopEPn1, . . . , TopEPnj. Suppose T contains the following EPs of Dp: TopEPpil, . . . , TopEPpix, where i1<i2<. . . <ix<=i; and the following EPs of Dn: TopEPnjl, . . . , TopEPnjy, where j1<j2<. . . <jy<=j. In the next step, two scores were calculated for T: scorep=Σ[frequency(TopEPpjm)/frequency(TopEPpm)] and scoren=Σ[frequency(TopEPnjm)/frequency(TopEPnm)], summing over m=1 . . . k, where k<<i and k<<j. In this case, k is chosen to be 25. Finally, a prediction is made on T as follows: If scorep>scoren, then T is predicted to be in class Dp; otherwise, it is predicted as class Dn.

[0169] The spirit of this variation is to measure how far the top k EPs contained in T are away from the top k EPs of a class. For example, if k=1, then scorep indicates whether the number-one EP contained in T is far from the most frequent EP of Dp. If the score is the maximum value 1, then the “distance” is very close, namely the most common property of Dp is also present in this testing sample. With smaller scores, the distance becomes further and the likelihood of T belonging to Dp becomes weaker. Using more than one top-ranked EPs in this way leads to very reliable predictions. This variation of EP-based classification method was termed “prediction by collective likelihood of EPs” or PCL for short.

[0170] 3. k-Nearest Neighbor (k-NN)

[0171] k-NN is a typical instance-based learner where the class of a new instance is decided by the majority class of its k closest neighbors (Cover and Hart (1967) IEEE Transactions on Information Theory 13:21-27, herein incorporated by reference). This method was used with the Euclidean distance metric. Conceptually, this is one of the most straightforward methods and is often used as a baseline for comparison purposes. The data were normalized using the z-score method, then the “best” few genes were chosen using one of the statistical gene selection methods. For these experiments, the “top n” genes, where n=1-50, were used. The expression values of the top genes from each diagnostic sample were treated as a vector in n-dimensional space. To classify a new sample, the same top n genes were chosen, and the Euclidean distance was computed between this new vector and each vector in the training data. The prediction was made by a majority vote of the k nearest samples, where k=1 or k=3. In this experiment, k was set to 1.

[0172] 4. Artificial Neural Network (ANN)

[0173] The artificial neural network (ANN) learning models built are all feed-forward, fully connected, and non-recurrent. The input layer of each ANN contains 50 units, which correspond to the 50 input values (the “top 50” scoring genes). Each ANN has one hidden layer with 4 units, and an output layer that contains two units, which represent the two class labels. In a preprocessing step all input data was normalized using the z-score method. The apparent error was estimated using 3-fold cross-validation. That is, for each training procedure, the training samples were randomly shuffled and divided into three groups of approximately equal size. A model was built with two of the groups and the third group was set aside for validation. This step was repeated three times, each time with a different group for validation. This shuffling-training process was repeated ten times, resulting in 30 ANN models. Each test sample was fed into each of the 30 ANN models, and the output was the average of the 30 outputs. The class predicted was the one that was represented by the output unit with the larger average output value.

[0174] F. Table of Results Using the Different Algorithms to Predict the Genetic Subgroups

[0175] A summary of the true prediction accuracy on the blinded test set of 112 cases are presented in Tables 37-39. Sensitivity was calculated as the number of positive samples predicted/the number of true positives. Specificity was calculated as the number of negative samples predicted/the number of true negatives.

39TABLE 37True Prediction Accuracy Resultson Test Set using SVM and ANN algorithmsSVMANNChi SqCFST-statsSOM/DAVWilkins'T-ALLTrue100100100100100AccuracySensitivity100100100100100Specificity100100100100100E2A-True100100100100100PBX1AccuracySensitivity100100100100100Specificity100100100100100TEL-True99999897100AML1AccuracySensitivity100100100100100Specificity98989797100BCR-True9597949797ABLAccuracySensitivity5067338383Specificity1001001009898MLLTrue1009810097100AccuracySensitivity10010010086100Specificity10098100100100H>50True9696969594AccuracySensitivity10010010095100Specificity9393939389

[0176]

40

TABLE 38

True Prediction Accuracy Results on Test Set using k-NN

k-NN

Chi Sq
CFS
T-stats
Wilkins'

T-ALL
True Accuracy
100
100
100
100

Sensitivity
100
100
100
100

Specificity
100
100
100
100

E2A-PBX1
True Accuracy
100
100
100
100

Sensitivity
100
100
100
100

Specificity
100
100
100
100

TEL-AML1
True Accuracy
98
98
99
100

Sensitivity
100
96
96
100

Specificity
97
98
100
100

BCR-ABL
True Accuracy
94
97
95
93

Sensitivity
33
67
50
67

Specificity
100
100
100
96

MLL
True Accuracy
100
98
95
100

Sensitivity
100
83
100
100

Specificity
100
100
94
100

H>50
True Accuracy
98
96
94
98

Sensitivity
100
100
95
100

Specificity
96
93
93
96

[0177]

41

TABLE 39

True Prediction Accuracy Results on Test Set using PCL

PCL

Chi Sq
CFS

T-ALL
True Accuracy
100
100

Sensitivity
100
100

Specificity
100
100

E2A-PBX1
True Accuracy
ND
100

Sensitivity
ND
100

Specificity
ND
100

TEL-AML1
True Accuracy
99
ND

Sensitivity
96
ND

Specificity
100
ND

BCR-ABL
True Accuracy
97
ND

Sensitivity
67
ND

Specificity
100
ND

MLL
True Accuracy
100
ND

Sensitivity
100
ND

Specificity
100
ND

H > 50
True Accuracy
98
ND

Sensitivity
100
ND

Specificity
96
ND

[0178] The assignment of a leukemic sample to a specific biologic subgroup is more accurately reflected by its gene expression profile than by the presence or absence of a specific genetic lesion. For example, four patients that had expression profiles classified as TEL-AML1, despite lacking a TEL-AML1 chimeric message by the reverse transcriptase polymerase chain reaction (RT-PCR) were found to have an alteration in TEL, suggesting a common underlying biology. Thus, from a technical viewpoint, gene expression profiling provides a viable alternative to standard diagnostic approaches.

[0179] G. Absence of Correlation of Expression Data for Genetic Subtypes with Stage of B-Cell Differentiation

[0180] The expression profiles of the different risk groups of B-cell leukemias do notcorrespond to markers of different stages of B-cell differentiation,. The first issue is defining the stage of B-cell differentiation. The defined stages of BM derived B-cells relevant to pediatric ALL are outlined below in Table 40, along with their frequency in pediatric ALL (Campana and Behm (2000) J. Immunologic Methods, 243:59-75). Three stages of differentiation are defined by a limited number of markers. In Table 41 below, the distribution of the leukemia cases into these B-cell differentiation stages is shown. As can be seen, none of the genetic subtypes is specifically associated with one of these three stages of differentiation. Thus, this simple analysis clearly shows that the majority of the chromosomal translocation subgroups in pediatric ALL do not correspond to a specific stage of B-cell differentiation. This is a well-known fact in the field of pediatric ALL and differs from the relationship typically seen between chromosomal translocations and other genetic lesions, and the stage of differentiation seen in B-cell lymphomas.

42TABLE 40Immunophenotyping of acute lymphoblastic leukemiasaLeukocyte antigen expression(% of cases positive)FrequencySubtypeCD19CD22cIgμsIgμsIg κ or λ(%)Early Pre-B100>9500060-65Pre-B1001001000020-25Transitional10010010010001-3Abbreviations: cIg μ, cytoplasmic immunoglobulin μ chain; sIg μ, surface immunoglobulin μ chain; sIg κor λ, surface immunoglobulin κ or λ chains aD. Campana and F. G. Behm, “Immunophenotyping of leukemia”, Journal of Immunological Methods 243: 59-75, 2000.

[0181]

43

TABLE 41

Distribution of genetic subtypes by immunophenotypea

TRANSITIONAL

EARLY PRE-B
PRE-B
PRE B

E2A
0
17
6

TEL
55
23
0

BCR
11
3
0

MLL
12
6
1

Hyperdip > 50
49
9
5

Novel
8
4
1

Total
172
77
24

a
For this analysis, samples with other immunophenotypes (NOS or mature B-cell) were not included

[0182] The next goal was to determine whether a set of genes that could accurately identify subjectss by their stage of differentiation, regardless of leukemai risk group. To accomplish this, cases were assigned into one of three classes, early pre-B, pre-B, or transitional pre-B based on their immunophenotype. The top 50 genes that distinguished each group from the other two groups were selected using the Wilkins' metric. These genes were then used in an ANN analysis to assess their performance in correctly classifying the 273 diagnostic B-lineage ALL samples, for which a stage of differentiation could be determined, through a process of cross validation. The results of this analysis are included below.

44TABLE 42Accuracy Results for immunophenotype discrimination usingWilkins' metric and ANN algorithmAccuracySensitivitySpecificityEarly Pre-Ba78.39%85.47%66.34%Pre-Bb71.79%38.96%84.69%Transitional Pre-Bc91.24%33.33%96.79%aCells with CD19+, CD22+, cytoplasmic Igμ−, surface Igμ− immunophenotype bCells with CD19+, CD22+, cytoplasmic Igμ+, surface Igμ− immunophenotype cCells with CD19+, CD22+, cytoplasmic Igμ+, surface Igμ+ immunophenotype

[0183] The selected genes perform rather poorly in correctly assigning cases to specific B-cell differentiation stages, with accuracies well below those achieved for prediction of the genetic subgroups. When these genes are used in a two-dimensional hierarchical clustering algorithm they failed to cluster cases by immunophenotype, but instead, resulted in the loose clustering of some of the genetic subgroups, including E2A-PBX1, TEL-AML1, BCR-ABL, MLL, and hyperdiploid>50. The analysis was repeated using genes selected by DAV and again, no clustering of the immunophenotypically-defined stages was observed. Thus, it was not possible to identify expression profiles that can accurately identify the immunophenotypically-defined differentiation stages of pediatric B-cell ALL. Moreover, the expression profiles that were defined for the genetic subtypes are not profiles that correspond to specific stages of B-cell differentiation. Although some of the genes that define specific genetic subtypes can be associated with a particular stage of B-cell differentiation, the majority of the discriminating genes show no correlation with differentiation.

[0184] H. Results for Relapse Prediction

[0185] In the prediction of whether a patient would go into continuous complete remission or would relapse, a subtype-specific approach was adopted. An individual classifier was constructed for each subtype of ALL. Given a sample, the subtype was first predicted, and then the corresponding subtype-specific prognostic classifier was invoked to predict whether the patient would relapse. This subtype-specific approach was required because an expression profile predictive of relapse for the entire group could not be defined.

[0186] In the construction of the type-specific classifiers, genes were selected by CFS unless this algorithm returned >20 genes, in which case the top 20 ranked genes by T-statistics were used. When the T-statistics method was used, the selection of how many among the top 20 T-statistics genes were to be used was made by performing cross validation experiments—that is, the top n genes for n=1 . . . 20 were picked the n that gave the best cross validation results was selected. The cross validation results for the optimal ice of genes are summarized in Table 43 below. The genes that were chosen for use subtype-specific relapse predictions are summarized in Table 44.

45TABLE 43Results of relapse prediction on indicated subgroupsP valueby permutationRelapseCCR# genesmetricAccuracytestT-ALL8267t-stats970.034H>5054313t-stats1000.018TEL-3567CFS1000.145AML1MLL574t-stats1000.104Others45620t-stats98.30.079

[0187]

46

TABLE 44

Genes selected by T-statistics/CFS for relapse (T-ALL)

Above/

Reference
Below

Gene Name
GeneSymbol
Number
Mean

Human TBXAS1 gene for
TBXAS1
D34625
Above

thromboxane synthase

Homo sapiens
mRNA for 41-kDa

AB007851
Above

phosphoribosylpyrophosphate

synthetase-

associated protein

Human DNA sequence

Z82206
Above

from PAC 370M22

Human spinal
SMA5
X83301
Above

muscular atrophy gene

Human cell surface
CD44
L05424
Above

glycoprotein CD44

Human mRNA for KIAA0056 gene
KIAA0056
D29954
Above

Human BTK region

U01923
Above

clone ftp-3 mRNA

[0188]

47

TABLE 45

Genes Selected by T statistics/CFS for relapse Hyperdiploid >50

Above/

Affymetrix

Reference
Below

number
Gene Name
Gene Symbol
Number
Mean

1
37721_at
deoxyhypusine synthase
DHPS
U79262
Above

2
38721_at
KIAA1536 protein
KIAA1536
W72733
Above

3
40120_at
hydroxyacyl glutathione
HAGH
X90999
Above

hydrolase

4
41386_i_at
KIAA0346 protein
KIAA0346
AB002344
Above

5
38677_at
stress 70 protein chaperone
STCH
U04735
Above

microsome-associated 60 kD

6
37620_at
Human TFIID subunits TAF20

U57693
Above

and TAF15 mRNA, complete

cds.

7
34703_f_at
EST

AA151971
Above

8
38355_at
DEAD/H Asp-Glu-Ala-Asp/His
DBY
AF000984
Above

box polypeptide Y chromosome

9
41214_at
ribosomal protein S4 Y-linked
RPS4Y
M58459
Above

10
34530_at
Homo sapiens cDNA FLJ22448

W73822
Above

fis clone HRC09541

11
603_at
nuclear receptor subfamily 2
NR2C1
M29960
Above

group C member 1

12
32697_at
inositol myo 1 or 4
IMPA1
AF042729
Above

monophosphatase 1

13
41129_at
KIAA0033 protein
KIAA0033
D26067
Above

14
33333_at
KIAA0403 protein
KIAA0403
AB007863
Above

15
37078_at
CD3Z antigen zeta polypeptide
CD3Z
J04132
Above

TiT3 complex

16
38148_at
cryptochrome 1 photolyase-like
CRY1
D83702
Above

17
39150_at
ring finger protein 11
RNF11
U69559
Above

18
33869_at
DKFZp586N1323 from clone

AL080218
Above

DKFZp586N1323

19
41447_at
KIAA0990 protein
KIAA0990
AB023207
Above

20
39369_at
KIAA0935 protein
KIAA0935
AB023152
Above

[0189]

48

TABLE 46

Genes selected by T-statistics/CFS for relapse (TEL-AML1I)

Above/

Affymetrix

Gene
Reference
Below

number
Gene Name
Symbol
number
Mean

1
35797_at
Human
IL-13Ra
Y10659
Above

interleukin-

13 gene

2
37524_at
Human death-
DRAK2
AB011421
Above

associated

protein kinase

3
34243_i_at
Human 1(3)mbt

U89358
Above

protein homolog

mRNA

4
41398_at

Homo sapiens

AL049305
Above

mRNA. CDNA

DKFZp564A186

5
35195_at

H. sapiens

Y11651
Above

mRNA for

phosphate cyclase

6
32393_s_at

Homo sapiens

W27466
Above

cDNA

7
31909_at

Homo sapiens

KIAA0754
AB018297
Above

mRNA for

KIAA0754

protein

[0190]

49

TABLE 47

Genes selected by T-statistics/CFS for relapse (MLL)

Above/

Affymetrix

Gene
Reference
Below

number
Gene Name
Symbol
number
Mean

1
294_s_at
Protein Kinase

Below

Pitslre, Alpha,

Alt. Splice 1-

Feb

2
38226_at
23h11 Homo

W27152
Below

sapiens
cDNA

3
1398_g_at
Human protein
HUMMLK3A
L32976
Above

kinase

(MLK-3)

mRNA

4
409_at
Human mRNA

X56468
Below

for 14.3.3

protein, a

protein

kinase

regulator

[0191]

50

TABLE 48

Genes selected by T-statistics/CFS for relapse (Others)

Above/

Affymetrix

Reference
Below

number
Gene Name
GeneSymbol
number
Mean

1
33782_r_at
nn82f03.s1 Homo sapiens cDNA, 3 end/

AA587372
Above

clone = IMAGE-1090397

2
33338_at
Human transcription factor ISGF-3 mRNA

M97936
Above

3
40242_at
Human (clone N5-4) protein p84 mRNA

L36529
Above

4
37018_at
qd05c04.x1 Homo sapiens cDNA, 3 end/

AI189287
Above

clone = IMAGE-1722822

5
38337_at

Homo sapiens
zinc finger protein mRNA

U62392
Above

6
41464_at
Human mRNA for KIAA0339 gene
KIAA0339
AB002337
Above

7
38064_at

H. sapiens
lrp mRNA
LRP
X79882
Above

8
33173_g_at
yc89b05.r1 Homo sapiens cDNA, 5 end/

T75292
Below

clone = IMAGE-23231

9
33365_at

Homo sapiens
mRNA for KIAA0945
KIAA0945
AB023162
Above

protein

10
39367_at
ni38e08.s1 Homo sapiens cDNA, 3 end/

AA522537
Above

clone = IMAGE-979142

11
41108_at

Homo sapiens
mRNA for putative GTP-
PGPL
Y14391
Above

binding protein

12
37304_at

Homo sapiens
heterochromatin protein p25
P25beta
U35451
Below

mRNA

13
40359_at
Human DNA-binding protein (HRC1)
HRC1
M91083
Above

mRNA

14
32792_at
Human DNA sequence from clone 465N24

AL031432
Above

on chromosome 1p35.1-36.13. Contains

two novel genes, ESTs, GSSs and CpG

islands

15
34726_at
Human voltage-gated calcium channel beta

U07139
Above

subunit mRNA

16
40299_at

Homo sapiens
G-protein coupled receptor

AF091890
Above

RE2 mRNA,

17
40704_at

H. sapiens
mRNA for phosphatidylinositol

Z29090
Above

3-kinase

18
38568_at

Homo sapiens
p53 binding protein mRNA

U82939
Above

19
32038_s_at
wi30c12.x1 Homo sapiens cDNA, 3 end/

AI739308
Above

clone = IMAGE-2391766

20
39613_at

H. sapiens
HUMM9 mRNA

X74837
Above

[0192] I. Permutations Test Results

[0193] As the number of relapse samples were small, in addition to the usual cross validation experiments, 1000 permutation experiments were performed for each subtype-specific relapse study. In each permutation experiment, the samples were re-partitioned in a manner that preserved class size by randomly swapping the class labels (“relapse” or “continuous complete remission”). The same metric was then employed to pick the same number of genes as in the original partitioning of the samples given by the original class labels. SVM was then used to obtain a prediction accuracy by cross validation for this random partition using these freshly selected genes. The percentage of these 1000 permutation experiments was taken as a p-value that gave an indication on how many random partitions of the original samples could achieve the same accuracy as the original samples. The results of these permutation experiments are summarized in the last column of Table 43 above. These results show that the high accuracy obtained on the predictability of relapse in T-lineage ALL, Hyperdiploid>50, and others are unlikely to be a random event. The higher p-values obtained for the subtypes of TEL-AML1 and MLL are probably due to the small number of relapse samples available for analysis.

51TABLE 49Permutation test results for predictors of T-ALL relapseAffymetrixRanknumbert-statistic valuePerm 1%Perm 5%neighbors133777_at7.83377.37745.47836241853_at6.17276.59484.811716338866_at5.98906.02934.561112441643_at5.61065.68154.38771251126_s_at5.47775.51624.237511641862_at5.37345.37594.120811741131_f_at4.91345.22804.029517

[0194]

52

TABLE 50

Permutation test results for predictors of

Hyperdiploid >50 relapse

Affymetrix
t-statistics

Rank
number
value
Perm 1%
Perm 5%
neighbors

1
37721_at
8.7160
12.7358
9.9506
75

2
38721_at
8.4162
10.7256
8.8438
59

3
40120_at
7.2736
9.9837
8.0383
73

4
41386_i_at
6.3436
9.0552
7.5579
88

5
38677_at
6.2698
8.8633
7.2466
88

6
37620_at
6.2174
8.4154
6.9604
82

7
34703_f_at
6.0770
8.0982
6.8835
83

8
38355_at
5.5120
7.8657
6.7434
92

9
41214_at
5.4262
7.6583
6.6094
90

10
34530_at
5.4013
7.5991
6.5109
87

11
603_at
5.3142
7.5903
6.4409
87

12
32697_at
5.1785
7.5146
6.3265
90

13
41129_at
5.1450
7.3939
6.2121
88

14
33333_at
5.1061
7.2601
6.1389
87

15
37078_at
5.0738
7.1484
6.0308
86

16
38148_at
4.9256
6.9688
5.9230
93

17
39150_at
4.9061
6.9273
5.9015
93

18
33869_at
4.8256
6.8900
5.8367
93

19
41447_at
4.7919
6.8135
5.7621
93

20
39369_at
4.7790
6.7731
5.7391
92

Individually, the discriminating genes for relapse in T-ALL are significant at either the 1% or 5% level, while those for hyperdiploid >50 fall at approximaltely the 7% level.

[0195]

53

TABLE 51

Results of relapse prediction on indicated subgroups

P value by

#

permutation

Relapse
CCR
genes
metric
Accuracy
test

T-ALL
8
26
7
t-stats
97
0.034

H > 50
5
43
13
t-stats
100
0.018

TEL-AML1
3
56
7
CFS
100
0.145

MLL
5
7
4
t-stats
100
0.104

Others
4
56
20
t-stats
98.3
0.079

[0196] As the number of relapse samples were small, in addition to the usual cross validation experiments, 1000 permutation experiments were also performed for each subtype-specific relapse study. In each permutation experiment, the samples were re-partitioned in a manner that preserved class size by randomly swapping the class labels (“relapse” or “continuous complete remission”). The same metric was employed to pick the same number of genes as in the original partitioning of the samples given by the original class labels. SVM was then used to obtain a prediction accuracy by cross validation for this random partition using these freshly selected genes. The percentage of these 1000 permutation experiments was taken as a p-value that gave an indication on how many random partitions of the original samples could achieve the same accuracy as the original samples. The results of these permutation experiments are summarized in the last column of Table 51 above. These results show that the high accuracy obtained on the predictability of relapse in T-lineage ALL, Hyperdiploid>50, and others are unlikely to be a random event. The p-values for the subtypes of TEL-AM1 and MLL are weaker than the other subtypes. However, in the case of TEL-AML1 the number of relapse samples were exceedingly small (3) and in the case of MLL the number of relapse and non-relapse samples were both very small.

[0197] J. Results for Secondary AML Prediction

[0198] For the secondary AML prediction, the same subtype-specific approach was adopted as described earlier in relapse prediction. This time only the TEL-AML1 subtype had sufficient number of samples for a secondary AML prediction model to be developed. For this model, the MIT score (Golub et al. (1999) Science 286:531-37, herein incorporated by reference) was used to select genes and SVM to perform classification using these genes. The MIT score of a gene is defined as T=|μ1-μ2|/(σ1+σ2), where μi is the mean expression of that gene in the ith class and σi is the standard deviation of that gene in the ith class. This formula assigns higher value to a gene that has larger mean difference between two classes and has smaller variance within both classes. The 20 genes with the highest MIT scores in TEL-AML1 patients that went into continuous complete remission versus those TEL-AML1 samples that developed secondary AML are listed in Table 52 below. 100% accuracy for secondary AML prediction accuracy was achieved on TEL-AML1 specific subtype samples using these 20 genes. A permutation test was also performed in the same manner as described earlier in the subtype-specific relapse prediction, and obtained a p-value of 0.031 was obtained, demonstrating that the predictability of the development of secondary AML in TEL-AML1-specific patients was unlikely to be a random event.

54TABLE 52Genes selected by MIT score for secondary AMLAbove/AffymetrixGeneReferenceBelowNumberGene NameSymbolNumberMeanTEL-AML1134890_atATPase H transporting lysosomal vacuolarATP6A1L09235Aboveproton pump alpha polypeptide 70 kDisoform 1240925_athypothetical protein FLJ10803FLJ10803AA554945Above31719_atmutS E. coli homolog 3MSH3U61981Above432877_i_atEST IMAGE: 954213AA524802Above532650_atneuronal proteinNP25Z78388Above633173_g_athypothetical protein FLJ10849FLJ10849T75292Above732545_r_atRSU-1/RSP-1RSU-1L12535Above834889_atATPase H transporting lysosomal vacuolarATP6A1AA056747Aboveproton pump alpha polypeptide 70 kDisoform 1935180_atcDNA DKFZp586F1323 from cloneAL050205AboveDKFZp586F13231034274_atKIAA1116 proteinKIAA1116AB029039Above1135727_athypothetical protein FLJ20517FLJ20517AI249721Above121627_attyrosine kinase (GB: Z25437)HG2715-AboveHT2811131461_atnuclear factor of kappa light polypeptideNFKBIAM69043Belowgene enhancer in B-cells inhibitor alpha1436023_atlacrimal proline rich proteinLPRPAI864120Above1539167_r_atserine or cysteine proteinase inhibitorSERPINH2D83174Aboveclade H heat shock protein 47 member 21639969_atH4 histone family member GH4FGAA255502Above1738692_atNGFI-A binding protein 1 ERG1 bindingNAB1AF045451Aboveprotein 1181594_atpolymerase RNA II DNA directedPOLR2CJ05448Abovepolypeptide C 33 kD1933234_atRBP1-like proteinLOC51742AA887480Above2034739_athypothetical protein FLJ20275FLJ20275W26023Above

[0199]

55

TABLE 53

Permutation test results for secondary AML

Affymetrix
t-statistics
Perm
Perm
Perm

Rank
number
number
1%
5%
median
neighbors

1
34890_at
1.2204
2.7933
2.2138
1.4712
822

2
40925_at
1.0712
2.0006
1.7607
1.2884
859

3
1719_at
1.0599
1.8536
1.6272
1.1894
767

4
32877_i_at
1.0364
1.7125
1.5218
1.1200
715

5
32650_at
1.0217
1.6580
1.4584
1.0776
646

6
33173_g_at
1.0126
1.5868
1.4132
1.0416
595

7
32545_r_at
1.0097
1.5536
1.3630
1.0223
536

8
34889_at
0.9959
1.5164
1.3241
1.0009
512

9
35180_at
0.9854
1.4838
1.2938
0.9777
477

10
34274_at
0.9420
1.4759
1.2721
0.9600
550

11
35727_at
0.8493
1.4482
1.2507
0.9415
809

12
1627_at
0.8471
1.4207
1.2398
0.9254
782

13
1461_at
0.8312
1.4012
1.2260
0.9114
801

14
36023_at
0.8177
1.3551
1.2012
0.8995
813

15
39167_r_at
0.8136
1.3462
1.1806
0.8894
790

16
39969_at
0.8122
1.3395
1.1702
0.8785
759

17
38692_at
0.8109
1.3333
1.1565
0.8696
729

18
1594_at
0.8103
1.3142
1.1503
0.8626
696

[0200]

56

TABLE 54

Additional Genes selected by

T statistics for BCR-ABL risk group

Gene symbol
Accession Number

TUBA1
HG2259-HT2348

TUBA1
X06956

CRADD
U84388

SLC2A5
M55531

PHYH
AF023462

ZFPL1
AF001891

CD34
S53911

KIAA0015
D13640

CLECSF2
X96719

CD34
M81945

GAB1
U43885

E2F5
U31556

CLTB
M20470

ENG
X72012

LOC55884
AF038187

TNFRSF1A
M58286

TMSNB
D82345

SNL
U03057

KIAA0990
AB023207

MAP1A
W26631

MYPT2
AB007972

IFI30
J03909

ERPROT213-21
U94836

DKFZP586A0522
AL050159

LOC51109
AA126515

W29087

TSTA3
U58766

TNFRSF1B
AI813532

GSN
X04412

KIAA0582
AI761647

STATI2
AF037989

AL049313

ITGA4
X16983

FLJ20500
AA522530

SDR1
AF061741

ARHGEF4
AB029035

C18ORF1
AF009426

MAPK14
U19775

FHL1
AF063002

GATA3
X58072

KIAA0076
D38548

KCNN1
U69883

POM121L1
D87002

IFI30
J03909

ABL1
X16416

NELL2
D83018

MEST
D78611

S100A4
W72186

D12S2489E
AJ001687

ATP2B4
W28589

CTGF
X78947

RGS1
S59049

CDK9
X80230

AI524873

STIM1
U52426

VEGFB
U48801

PPP2R2A
M64929

CASP2
U13022

SPS
U34044

HRK
D83699

KIAA0870
AB020677

ABL
U07563

PKIA
S76965

FLJ12474
AA306076

CD97
X94630

HCK
M16591

FYN
M14333

KIR2DL3
AC006293

DMPK
L08835

N33
U42360

FLJ13949
AL041879

PRKCZ
Z15108

IL17R
U58917

FMR2
U48436

INSR
M10051

AHNAK
M80899

KIAA0878
AB020685

CD86
U04343

U82303

KIAA1043
AL033538

N33
U42349

SYN47
Y17829

ITPR1
D26070

SFRS9
AL021546

EPOR
M60459

GAC1
AF030435

CAMK4
D30742

KIAA0084
D42043

LAT
AJ223280

XBP1
Z93930

FLT3LG
U03858

TESK1
D50863

AF070633

KIAA0681
U89358

FUT8
Y17979

[0201]

57

TABLE 55

Additional Genes selected

by T statistics for E2A-PBX1 Risk Group

Gene symbol
Accession Number

PBX1
M86546

AL049381

FAT
X87241

BLK
S76617

IRF4
U52682

GS3955
D87119

KIAA0802
AB018345

SCHIP-1
AF070614

SNL
U03057

KIAA0655
AB014555

GS3955
D87119

IGFBP7
L19182

CDKN1A
U03106

CSF2RB
H04668

STATI2
AF037989

KIAA1029
AB028952

KIAA0247
D87434

AL049397

NP
X00737

TM4SF2
L10373

ALOX5
J03600

LRMP
U10485

PTPN2
AI828880

ALOX5AP
AI806222

AEBP1
AF053944

TGFBR2
D50683

ODC1
M33764

NID2
D86425

ODC1
X16277

CBX1
U35451

CSF3R
M59820

KIAA0172
D79994

IL1B
M15330

KIAA0922
AB023139

LOC51097
AA005018

TUBA1
X06956

ITGA6
S66213

NFKBIL1
Y14768

ADPRT
J03473

ADPRT
J03473

CSF3R
M59818

EFNB1
U09303

CD9
M38690

CDKN2D
U40343

KIAA0442
AB007902

PRKCZ
Z15108

AF055029

RECK
D50406

GOLGA3
D63997

ZAP70
L05148

FLI1
M98833

LASP1
X82456

AJ001381

TBXA2R
D38081

BHLHB2
AB004066

ADARB1
U76421

PTPN6
X62055

X58398

TIMP1
D11139

KIAA0554
AB011126

SRP14
AI525652

ATP9A
AB014511

HELO1
AL034374

GNAQ
U43083

POU4F1
X64624

MERTK
U08023

KIAA0625
AB014525

PCLO
AB011131

IL7R
AF043129

ITGA6
X53586

TUBA1
HG2259-HT2348

PIR121
L47738

MAGED1
W26633

CD48
M37766

TLR1
AL050262

NPR1
X15357

GLUL
X59834

DAPK1
X76104

X58398

ARHGEF4
AB029035

NKEFB
L19185

AL049435

ITM2A
AL021786

RAG2
M94633

L24521

SCGF
AF020044

PRKACB
M34181

KCNN4
AF022797

KCNN1
U69883

MAPKAPK2
U12779

PIN
AI540958

TOP2B
X68060

GATA2
M68891

IL1B
X04500

PDE3B
U38178

DGKD
D73409

KIAA0993
AB023210

ADAM10
AF009615

IGLL1
M27749

PDLIM1
U90878

PRKAR1A
M33336

CD34
S53911

GLA
U78027

BAZ1B
AF072810

EFNA1
M57730

FADS3
AC004770

FLT3
U02687

LOC57228
AF091087

BCL6
U00115

BMP2
M22489

CD22
X59350

KIAA0429
AB007889

DKFZP434C171
AL080169

CTBP2
AF016507

M11810

SIAT9
AB018356

CYBB
X04011

AKR1B1
X15414

NFKBIL1
Y14768

UBE2V1
U49278

DOC-1R
AF089814

BUB3
AF047473

IL7R
M29696

ACK1
L13738

ENIGMA
L35240

KIAA1071
AB028994

IGL
AI932613

MN1
X82209

KIAA0823
AB020630

NFKB1
M58603

CD24
L33930

YWHAQ
X56468

VDAC1
L06132

P85SPR
D63476

SYNGR1
AL022326

NDR
Z35102

JMJ
AL021938

PRSC1
D55696

MRC1
M93221

AI184710

CRIP1
AI017574

KIAA0056
D29954

AF039397

U79265

SLAM
U33017

LYL1
AC005546

KIAA0620
AB014520

VDAC1P
AJ002428

SRP9
AF070649

PRDX1
X67951

SLC9A3R1
AF015926

CD72
M54992

ECM1
U68186

PPP2R5A
L42373

HDGF
D16431

MERTK
U08023

L02326

CD34
M81945

IL17R
U58917

ARL7
AB016811

P4HA2
U90441

BZRP
M36035

F13A1
M14539

KRAS2
M54968

BS69
X86098

ORP150
U65785

D28915

LEF1
AL049409

SH2D1A
AL023657

LY6E
U66711

FACVL1
D88308

EPB42
M60298

AL049471

BMI1
L13689

KCNJ13
N36926

N33
U42349

VIL2
X51521

CCNG2
U47414

C18ORF1
AF009425

NUMA1
Z11584

DBN1
U00802

FLT3
U02687

KIAA0854
AB020661

MGC4175
AI656421

KIAA1012
AB023229

CIRBP
D78134

ST5
U15131

KIAA0001
D13626

CCR1
D10925

CD19
M28170

SNRPE
AA733050

CR2
M26004

HEXA
M16424

IFIT4
AF026939

W26667

EPOR
M60459

TMSNB
D82345

GCLM
L35546

H41
H15872

TUBB2
HG1980-HT2023

TNFAIP2
M92357

GAB1
U43885

PTPRK
L77886

BCL7A
X89984

[0202]

58

TABLE 56

Additional Genes selected by

T statistics for Hyperdiploid > 50

Risk Group

Gene symbol
Accession Number

SH3BP5
AB005047

FLT3
U02687

MX1
M33882

NPY
AI198311

SOD1
X02317

PTPRK
L77886

IL1B
X04500

CD9
M38690

FLT3
U02687

PGK1
V00572

EFNB1
U09303

FOS
K00650

IL1B
M15330

MRC1
M93221

HMG14
J02621

SNRP70
X06815

PDLIM1
U90878

ALOX5
J03600

RAG2
M94633

CALM1
U12022

KIAA1013
AB023230

NDUFA1
N47307

FOS
V01512

DXS1357E
X81109

ICSBP1
M91196

ETS2
J04102

PCDH9
AI524125

LILRA2
AF025531

PSAP
J03077

SCHIP-1
AF070614

CCND2
D13639

KCNN1
U69883

ALTE
AB018328

IGFBP4
U20982

M9
AB019392

SCML2
Y18004

LOC51632
AI557497

UBE2G2
AF032456

STATI2
AF037989

ATRX
U72936

APT6M8-9
AL049929

PTPRE
X54134

GILZ
AI635895

PECAM1
AA100961

ARHGEF4
AB029035

ECM1
U68186

[0203]

59

TABLE 57

Additional Genes selected by

T statistics for the MLL Risk Group

Gene symbol
Accession Number

EPOR
M60459

CD44
L05424

PRKCH
M55284

MADH1
U59423

KLF1
U65404

MME
J03779

PTPRK
L77886

IL1B
X04500

YES1
M15990

ARPC2
U50523

IGFBP4
M62403

ITPR3
U01062

M13929

EFNB1
U09303

FHIT
U46922

NME2
X58965

CCND2
X68452

MPB1
M55914

CDH2
M34064

IGFBP7
L19182

ALOX5
J03600

PTGDR
U31099

PLXNC1
AF030339

EIF3S2
U39067

BLVRA
X93086

HSPC022
W68830

S67247

MYLK
U48959

SLC6A11
S75989

X67098

SERPINB1
M93056

LGALS1
AI535946

HRK
D83699

AL049313

HBS1L
AB028961

KIAA0437
AB022660

GDI2
Y13286

ITGA4
X16983

EEF1B2
X60489

MD-1
AB020499

POU4F1
X64624

TST
X59434

PTPRF
Y00815

ARHGEF4
AB029035

SCHIP-1
AF070614

ASMTL
AA669799

DDR1
L20817

N33
U42360

CR2
M26004

AHNAK
M80899

SCGF
AF020044

EPB49
U28389

PSPHL
AJ001612

MADH1
U59912

ITPR3
U01062

DPEP1
J05257

AKAP12
U81607

DBI
A1557240

KIAA0736
AB018279

MAL
X76220

S100A4
W72186

MDK
X55110

CRK
D10656

CAPG
M94345

KCNH2
U04270

KIAA1069
AB028992

DKFZP564L0862
AL080091

KIAA0298
AB002296

DGKD
D73409

DEPP
AB022718

AL049957

CD8B1
X13444

EFNB1
U09303

AI391564

LDOC1
AB019527

EFNA1
M57730

CD44
L05424

PTPRC
Y00062

PTPRC
Y00638

PTPRC
Y00638

TFPI
M59499

TSPAN-5
AF065389

BCL11A
W27619

AJ001381

KIAA1011
AL080133

FYB
U93049

DKFZp761F2014
AA149431

FGFR1
X66945

M63589

PTPN6
X62055

[0204]

60

TABLE 58

Additional Genes selected by

T statistics for the Novel Risk Group

Gene symbol
Accession Number

CHST2
AB014679

CLTC
D21260

TUBA1
X06956

GNG11
U31384

PCDH9
AI524125

MDS019
AA442560

RAG2
M94633

ITGA6
X53586

UBE2E3
AB017644

CD34
S53911

CD34
M81945

FGFR1
M34641

ECM1
U68186

MADH1
U59423

FUT7
AB012668

PROML1
AF027208

CSNK2A1
M55265

FLNB
AF042166

MADH1
U59912

LIG4
X83441

ZNF151
Y09723

CSF3R
M59818

AL080205

STAU2
AL079286

AEBP1
AF053944

KIAA0320
AB002318

KIAA0746
AB018289

PTPRM
X58288

IGFBP4
M62403

ZNF266
AA868898

PDLIM1
U90878

MTMR3
AB002369

TIMP1
D11139

TTC2
W28595

TM4SF2
L10373

PSA
AA978353

HTR4
Y12505

MMS19L
AF007151

AI391564

TJP2
L27476

BMP2
M22489

ARL7
AB016811

TLR1
AL050262

SMC2L1
AF092563

TGFBR2
D50683

TGFBR2
D50683

SPARC
J03040

GPRK5
L15388

CDH2
M34064

KIAA0877
AB020684

ABLIM
D31883

RNF3
W25793

CCBP2
U94888

CHN2
U07223

ITGA4
X16983

IQGAP2
U51903

FLJ22531
W80358

PIK3CD
U86453

FXYD2
H94881

W30677

AMPD3
U29926

D78577

KIAA0125
D50915

FADS3
AC004770

DKFZP434C171
AL080169

EST00098
AI885170

BMP2
M22489

LILRB4
AF072099

KIAA0429
AB007889

DKFZP586G0522
AL050289

U92818

ATIC
D82348

MONDOA
AB020674

CNK1
AF100153

NGFR
M14764

KIAA0540
AB011112

MYO10
AB018342

PIASX-BETA
AF077954

ACVR1
Z22534

ARHGEF10
AB002292

PON2
AF001601

TST
X59434

SPTBN1
M96803

ERCC2
AA079018

PRSC1
D55696

DKFZP434D174
AL080150

AI184710

CD8B1
X13444

U79265

DKFZp761F2014
AA149431

MEF2A
U49020

JAG2
AF029778

ZNF143
AF071771

CASP1
U13697

HAP1
AF040723

FABGL
D82061

ALDH1
K03000

RAD9
U53174

AL109722

CDC27
AA166687

B4GALT1
D29805

PTPRM
X58288

AHR
L19872

N33
U42349

IL12RB2
U64198

MTR
U73338

KIAA0697
AB014597

CSNK2B
M30448

U15590

W28612

HSU79253
AF052186

RBBP1
S57153

S100A11
D38583

TCF12
M80627

AI971169

EEF1E1
N32257

SAP18
AW021542

PVRL1
AF060231

M13929

MKP-L
AF038844

W26667

CD79B
M89957

KIAA0437
AB022660

AF070633

GCLM
L35546

EDG6
AJ000479

MAL
X76220

[0205]

61

TABLE 59

Additional Genes selected by

T statistics for the T-ALL Risk Group

Gene symbol
Accession Number

SLP65
AF068180

CD3D
AA919102

SH2D1A
AL023657

CD79B
M89957

CD3E
M23323

CTGF
X78947

PFTK1
AB020641

TRB
X00437

CD24
L33930

CD22
X52785

TOP2B
X68060

CD22
X59350

TCL1A
X82240

BRAG
AB011170

CD79A
U05259

SCHIP-1
AF070614

MAL
X76220

HLA-DQB1
M16276

PDE4B
L20971

HLA-DQB1
M60028

CD19
M28170

KIAA0959
AB023176

LILRA2
AF025531

PTPN18
X79568

MEF2C
L08895

PTP4A2
U14603

NPY
AI198311

GAB1
U43885

lck
U23852

TCF7
X59871

TERF2
X93512

ITM2A
AL021786

MEF2C
S57212

SLC9A3R1
AF015926

ENG
X72012

DEPP
AB022718

IL1B
X04500

IL1B
M15330

ECM1
U68186

HLA-DMA
X62744

CRMP1
D78012

WFS1
AF084481

PRKCQ
L01087

GNG7
AB010414

X58398

CDKN1A
U03106

CD9
M38690

PTK2
L13616

TRB
M12886

IF135
L78833

NUCB2
X76732

KIAA0942
AB023159

VATI
U18009

ARL7
AB016811

USP20
AB023220

PLCG2
X14034

PRDX1
X67951

POU2AF1
Z49194

CMAH
D86324

ALOX5
J03600

PTPN7
M64322

MEF2C
S57212

KIAA0668
AL021707

LOC54103
AL079277

EFNB1
U09303

HELO1
AL034374

ADF
S65738

KIAA0906
AB020713

IGFBP4
U20982

LDHB
X13794

CTNNA1
U03100

ENO2
X51956

LAT
AJ223280

PTPN7
D11327

M16942

CSRP2
U57646

GLA
U78027

ADA
X02994

RGS10
AF045229

KIAA0870
AB020677

CD3Z
J04132

STATI2
AF037989

GSN
X04412

INSR
X02160

HLA-DNA
M31525

CD72
M54992

EPHB6
D83492

MYLK
U48959

HLA-DQA1
AA868382

LCK
M36881

FHL1
AF063002

CRIM1
AI651806

AQP3
N74607

HLA-DQB1
M81141

GNG11
U31384

LARGE
AJ007583

FOXO1A
AF032885

NPR1
X15357

GAB1
U43885

PTPRE
X54134

PDLIM1
U90878

NCF4
AL008637

ARHGEF4
AB029035

PTP4A2
U14603

CTNNA1
AF102803

SEPW1
U67171

CHI3L2
U58515

LILRA2
U82277

CD79A
U05259

TCL1B
AB018563

TCF4
M74719

TACTILE
M88282

AB002438

TXN
AI653621

ADE2H1
X53793

AL049449

GLUL
X59834

ZFHX1B
AB011141

P4HB
M22806

IFITM1
J04164

KIAA0182
D80004

SH2D1A
AF100539

GNA11
M69013

NCF4
AL008637

SLC2A5
M55531

KIAA0993
AB023210

HLA-DPB1
M83664

HLX1
M60721

CTNNA1
D14705

FADS3
AC004770

GATA3
X58072

GDI2
Y13286

TM4SF2
L10373

GNA15
M63904

BTG2
U72649

RAG1
M29474

MDK
X55110

X00457

AKR1C3
D17793

SLA
D89077

LDHA
X02152

AL049279

PTPRC
Y00638

BMP2
M22489

ERG
M17254

ICSBP1
M91196

CCT2
AF026166

AKAP2
AB023137

X58398

KIAA0128
D50918

IGHM
X58529

NOTCH3
U97669

JUP
M23410

DKFZP586O1624
AL039458

MYO10
AB018342

CTNNA1
L23805

NOS2A
U31511

D00749

L29376

ICB-1
AF044896

GNAI1
AL049933

S100A11
D38583

MAPKAPK3
U09578

ADA
M13792

S100A13
AI541308

VDAC3
AF038962

AL049265

TRIM
AJ224878

CTBP2
AF016507

F13A1
M14539

ZNF43
HG620-HT620

DKFZp761F2014
AA149431

KIAA0442
AB007902

CTNNA1
U03100

CD2
M16336

BMP2
M22489

HSPC022
W68830

ICAM3
X69819

NCF4
X77094

GS3955
D87119

CTSC
X87212

GH1
V00520

ARPC2
U50523

HLA-DRB1
M32578

GAS1
L13698

LAMB2
M55210

EPHB4
U07695

COX8
A1525665

KIAA0618
N29665

KIAA0870
AI808958

PIK3CG
X83368

IGHD
K02882

IRF4
U52682

HSPCB
M16660

CAPN3
X85030

CD6
X60992

WSX-1
AI263885

FXYD2
H94881

PTK2
HG3075-HT3236

FUCA1
M29877

FADS2
AL050118

KARS
D32053

DSCR1
U85267

SOX4
X70683

TRD
X73617

MHC2TA
U18259

AL049435

MDK
M94250

CALM1
U12022

PCLO
AB011131

AI391564

FHIT
U46922

MONDOA
AB020674

TRG
M30894

SPIB
X66079

FLJ10097
AL035494

TAGLN2
D21261

LGALS9
Z49107

[0206]

62

TABLE 60

Additional Genes selected by

T statistics for the TEL-AML1 Risk

Group

Gene symbol
Accession Number

ARHGEF4
AB029035

TNFRSF7
M63928

PCLO
AB011131

TCFL5
AB012124

KCNN1
U69883

NME2
X58965

PTPRK
L77886

AL049313

TERF2
X93512

GNG11
U31384

RAG1
M29474

AL080190

MADH1
U59423

HG3523-HT4899

MADH1
U59912

P114-RHO-GEF
AB011093

L29254

MDK
M94250

TERF2
AF002999

CRMP1
D78012

HLA-DOB
X03066

NFKBIL1
Y14768

AA216639

AL080059

CBFA2T3
AB010419

MDK
X55110

PIK3C3
Z46973

ALOX5
J03600

PTP4A3
AF041434

POU2AF1
Z49194

POU4F1
L20433

PRKCB1
X07109

GCAT
Z97630

PHYH
AF023462

SPTA1
M61877

IDI1
X17025

FYB
U93049

ITPR1
D26070

GTT1
AL041780

FADS3
AC004770

CCT2
AF026166

ISG20
U88964

SCHIP-1
AF070614

DR6
AF068868

MYO10
AB018342

ZNF91
L11672

T-STAR
AF051321

FUCA1
M29877

HLA-DQB1
M60028

AB002438

CTGF
X78947

FKBP1A
M34539

AI391564

RAB1
AL050268

INSR
X02160

KIAA0540
AB011112

TM4SF2
L10373

CASP1
M87507

MT1L
AA224832

MME
J03779

AI743299

KARS
D32053

CHN2
U07223

IQGAP2
U51903

KIAA0906
AB020713

STATI2
AF037989

HLA-DMA
X62744

CD36L1
Z22555

PRKCB1
X06318

GS3955
D87119

ACTN1
X15804

FLJ20154
AF070644

KIAA0769
AB018312

SDC1
Z48199

SOX4
X70683

NRTN
U78110

CTNND1
AB002382

FHIT
U46922

FARP1
AI701049

FOXO1A
AF032885

NPY
AI198311

VDUP1
S73591

H2AFO
AI885852

TACTILE
M88282

SNL
U03057

JUP
M23410

NR3C2
M16801

PRPS2
Y00971

LILRA2
AF025531

RNAHP
H68340

DPYSL2
U97105

ITGB2
M15395

PCDH9
AI524125

LAIR1
AF013249

CD79A
U05259

NFKBIL1
Y14768

PCCA
S79219

HLA-DMB
U15085

SMARCA4
D26156

Example 2

[0207] To identify additional additional genes whose expression levels could be used as a diagnostic tool to identify ALL subgroups, leukemic blasts from 132 diagnostic samples were analyzed using higher density oligonucleotide arrays that allow the interrogation of a majority of the identified genes in the human genome.

[0208] A subset of the 327 diagnostic pediatric ALL samples described above were reanalyzed using these higher density microarrays. Case selection was based on providing a representation of the known prognostic ALL subtypes including t(9;22)[BCR-ABL], t(1;19)[E2A-PBX1], t(12;21)[TEL-AML1], rearrangement in the MLL gene on chromosome 11q23, and hyperdiploid karyotype with >50 chromosomes. Since the goal was to define expression profiles that could be used to accurately diagnose the known prognostic subtypes of ALL, we chose to over represent these subtypes compared to what is normally seen in a random population of childhood leukemia patients. A total of 132 samples met these criteria and had sufficient material remaining to be used for this analysis. The list of samples and subtype distribution of the cases used in this study are shown in Tables 61 and 52, respectively.

63TABLE 61Diagnostic ALL samples used for class prediction (n = 132)BCR-ABL-#1Hyperdip >50-c18Pseudodip-#6BCR-ABL-#2Hyperdip >50-C21Pseudodip-C2-NBCR-ABL-#3Hyperdip >50-C22Pseudodip-C3BCR-ABL-#4Hyperdip >50-C23Pseudodip-C5BCR-ABL-#5Hyperdip >50-C27-NPseudodip-C6BCR-ABL-#6Hyperdip >50-C32Pseudodip-C7BCR-ABL-#7Hyperdip >50-R4Pseudodip-C9BCR-ABL-#8Hyperdip47-50-C14-NPseudodip-C14BCR-ABL-#9Hyperdip47-50-C3-NPseudodip-C16-NBCR-ABL-Hyperdip-#10Hypodip-#2Pseudodip-R1-NBCR-ABL-C1Hypodip-2M#1T-ALL-#5BCR-ABL-R1Hypodip-C2T-ALL-#6BCR-ABL-R2Hypodip-C5T-ALL-#7BCR-ABL-R3MLL-#1T-ALL-#8BCR-ABL-Hyperdip-R5MLL-#2T-ALL-#10E2A-PBX1-#5MLL-#3T-ALL-C2E2A-PBX1-#6MLL-#4T-ALL-C6E2A-PBX1-#9MLL-#5T-ALL-C7E2A-PBX1-#10MLL-#6T-ALL-C11E2A-PBX1-#12MLL-#7T-ALL-C15E2A-PBX1-#13MLL-#8T-ALL-C19E2A-PBX1-2M#1MLL-2M#1T-ALL-C21E2A-PBX1-C2MLL-2M#2T-ALL-R5E2A-PBX1-C3MLL-C1T-ALL-R6E2A-PBX1-C4MLL-C2TEL-AML1-#6E2A-PBX1-C5MLL-C3TEL-AML1-#9E2A-PBX1-C6MLL-C4TEL-AML1-#10E2A-PBX1-C7MLL-C5TEL-AML1-#14E2A-PBX1-C9MLL-C6TEL-AML1-2M#1E2A-PBX1-C10MLL-R1TEL-AML1-2M#2E2A-PBX1-C11MLL-R2TEL-AML1-C4E2A-PBX1-C12MLL-R3TEL-AML1-C5E2A-PBX1-R1MLL-R4TEL-AML1-C6Hyperdip >50-#8Normal-C1-NTEL-AML1 -C26Hyperdip >50-#12Normal-C2-NTEL-AML1-C28Hyperdip >50-#14Normal-C3 -NTEL-AML1-C30Hyperdip >50-C1Normal-C4-NTEL-AML1-C31Hyperdip >50-C4Normal-C7-NTEL-AML1-C32Hyperdip >50-C6Normal-C8TEL-AML1-C33Hyperdip >50-C8Normal-C9TEL-AML1-C34Hyperdip >50-C11Normal-C11-NTEL-AML1-C37Hyperdip >50-C13Normal-R1TEL-AML1-C38Hyperdip >50-C15Normal-R2-NTEL-AML1-C40Hyperdip >50-C16Pseudodip-#5TEL-AML1-R3*Subtype Name-C# Dx Sample of patient in CCR Subtype Name-R# Dx Sample of patient who developed a hematologic relapse Subtype Name-# Dx Sample used for subgroup classification only Subtype Name-2M# Dx Sample of patient who later developed 2nd AML Subtype Name-N Dx Sample in novel group

[0209]

64

TABLE 62

Subgroup distribution of ALL cases

Subgroup
Train Set
Test Set

BCR-ABL
11
4

E2A-PBX1
13
5

Hyperdiploid >50
13
4

MLL
15
5

T-ALL
12
2

TEL-AML1
15
5

Other
21
7

Total
100
32

[0210] 26,825 probe sets from combined Affymetrix® brand U133A and B microarrays (Affymetrix, Inc., Santa Clara, Calif.) showed variation in expression levels across the 132 diagnostic leukemia samples. In an initial analysis of these data, two complementary unsupervised clustering algorithms: two-dimensional hierarchical clustering and principle component analysis (PCA), were used to assess the major sub-groupings of the leukemia cases based solely on gene expression profiles. These unbiased clustering algorithms demonstrated that the pediatric ALL cases cluster primarily into seven major subtypes: T-ALL and 6 subtypes of B-cell lineage ALL corresponding to (1) rearrangement in the MLL gene on chromosome 11q23, (2) t(1;19)[E2A-PBX1], (3) hyperdiploid>50 chromosomes, (4) t(9;22)[BCR-ABL], (5) the novel subgroup, and (6) t(12;21)[TEL-AML1]. In addition, a heterogeneous group of B-lineage cases were identified that lacked any of the defined genetic lesions and failed to cluster into the novel subgroup. Several of these leukemia subtypes formed distinct branches when all differentially expressed genes were used in the two-dimensional hierarchical clustering algorithm (T-ALL, Hyperdiploid>50 chromosomes, and TEL-AML1), whereas other subtypes clustered in multiple branches, suggestive of gene expression differences within these subclasses. Using PCA, the distinct nature of the B-cell lineage subtypes is better appreciated when the T-ALL cases were removed from the analysis. A diagnostic accuracy of 100% was achieved for two of the leukemia subtypes (T-ALL and TEL-AML1), indicating the need to use supervised learning algorithms to achieve optimal diagnostic accuracy by gene expression profiling.

[0211] Statistical methods were used to identify probe sets that were the best discriminators of the individual leukemia subtypes. In order to identify the genes that provide the highest accuracy in diagnosing specific prognostic subtypes of leukemia, the decision tree format described elsewhere herein was used for the identification of leukemia subtypes. Briefly, we first defined whether a case is T- or B-cell in lineage. If the case is classified as T-cell, a diagnosis of T-ALL is made. If non-T, we then determine if the case can be classified into one of the known B-cell lineage risk groups, deciding sequentially if it is E2A-PBX1, TEL-AML1, BCR-ABL, rearranged MLL gene, and lastly hyperdiploid with >50 chromosomes. Cases not assigned to one of these classes are left unassigned. The use of this decision tree format directly influences the selection of genes, allowing the selection of discriminating genes for groups lower down the tree that might also be expressed by subtypes higher in the tree. Using a number of different supervised learning algorithms, it was found that a higher diagnostic accuracy is obtained using this decision tree format, as compared to a parallel format in which each class is identified against all others.

[0212] Discriminating genes were selected using a chi-square metric on the 100 cases in the training set. Genes were selected that discriminated between a class and all leukemia subtypes below it in the decision tree. The number of discriminating probe sets per leukemia subtype at a statistical significance level of p≦0.001 (as determined by a permutation test) were: T-ALL, 2063; E2A-PBX1, 1059; TEL-AML1, 805; BCR-ABL, 201; MLL chimeric genes, 726; and hyperdiploid with >50 chromosomes, 994. The lists of discriminating genes obtained using the top 100 ranked probe sets for the six prognostically important subgroups are contained in Tables 63-68. As multiple probe sets for the same gene are present on Affymetrix microarrays, the top 100 ranked probe sets represent between 75 and 92 distinct genes, depending on the leukemia subtype. As shown, distinct groups of either over or under expressed genes distinguish cases defined by E2A-PBX1, MLL gene rearrangement, T-ALL, hyperdiploid>50 chromosomes, BCR-ABL, and TEL-AML1.

[0213] The following tables contain a list of the top 100 probe sets for each diagnostic subtype, ranked by their chi-square value. Each table contains the Affymetrix® U133 series probe set number, a gene description, gene symbol, chromosomal location, and primary GenBank reference. Chi-square values were calculated utilizing only the samples in the train set in a differential diagnosis decision tree format. The calculation of the fold change was done in a parallel format using the total data set and comparing the mean signal value in the class versus the mean signal value in the non-class.

65TABLE 63Top 100 chi-square probe sets selected for BCR-ABLBcrChi-above/U133 probeGeneChromosomalGenBanksquarebelowFoldsetGene descriptionsymbollocationReferencevaluemeanchange1241812_atEST FLJ39877FLJ39877 2AV64866947.4Above5.22201876_atParaoxonase/PON27q21.3NM_000305.147.2Above18.7arylesterase 23201028_s_atAntigen identifiedMIC2Xp22.32U82164.144.3Above2.6by monoclonalantibodies 12E7,F21 and O134200953_s_atCyclin D2CCND212p13NM_001759.142.3Above3.55202947_s_atGlycophorin CGYPC2q14-q21NM_002101.242.3Above3.1integral membraneglycoprotein6223449_atSemaphorin 6ASEMA6A5q23.1AF225425.142.3Above4.37201029_s_atAntigen identifiedMIC2Xp22.32NM_002414.141.2Above2.4by monoclonalantibodies 12E7,F21 and O138204429_s_atSolute carrierSLC2A51p36.2BE56046141.2Above5family 2(facilitatedglucose/fructosetransporter),member 59210830_s_atParaoxonasePON27q21.3AF001602.141.2Above23.610215028_atSemaphorin 6ASEMA6A 5AB002438.141.2Above4.511220024_s_atPeriaxinPRX19q13.13-q13.2NM_020956.141.2Above8.212201906_s_atHYA22 proteinHYA223p21.3NM_005808.141.1Above43.413209365_s_atExtracellularECM11q21U65932.141.1Above6matrix protein 114238689_atGPR110 GGPR110 6BG42645541.1Above10.9protein-coupledreceptor 11015222154_s_atDKFZP564A2416DKFZP564A24162q33.1AK002064.140.4Above12.4unknown proteinwith a histone H5signature.16218084_x_atFXYD domain-FXYD519q12-q13.1NM_014164.238Above1.5containing iontransport regulator 517212242_atTubulin, alpha 1TUBA12q36.2AL56507437Above3.2(testis specific)18201445_atCalponin 3, acidicCNN31p22-p21NM_001839.136.3Above10.819202771_atKIAA0233 geneKIAAO23316q24.3NM_014745.136.3Above1.9product20212298_atNeuropilin 1NRP110p12BE62045736.3Above13.821212458_atFLJ21897FLJ21897 2AW13890236.3Above2.422222488_s_atDynactin 4DCTN45q31-q32BE21802836.3Above3.623222762_x_atLIM domainsLIMD13p21.3AU14425936.3Above2.6containing 124200951_s_atCyclin D2CCND212p13NM_001759.135.3Above12.725204430_s_atSolute carrierSLC2A51p36.2NM_003039.135.3Above5.1family 2(facilitatedglucose/fructosetransporter),member 526205467_atCaspase 10CASP102q33-q34NM_001230.135.3Above3.627225660_atSemaphorin 6ASEMA6A5q23.1W9274835.3Above3.328225913_atFLJ21140FLJ2114015AK025943.135.3Above2.9(Ser/Thr proteinkinase)29236489_atEST 6AI28209735.3Above16.730240173_atEST 4AI73296935.3Above10.331240499_atEST10AA48222135.3Above1.332201310_s_atP311 protein.P3115q21.3NM_004772.135.2Below2.2Similar togastrin/cholecystokinin type Breceptor.33215617_atFLJ11754FLJ11754 2AU14571135.2Above14.434242579_atEST 4AA93546135.2Above10.235202717_s_atCDC16 cellCDC1613q34NM_003903.134.4Above1.1division cycle 16homolog36205055_atIntegrin, alpha EITGAE17p13NM_002208.334.4Below2.1(antigen CD103,human mucosallymphocyteantigen 1)37217967_s_atChromosome 1Clorf241q25AF288391.134.4Above3.2ORF 2438201656_atIntegrin, alpha 6ITGA62q31.1NM_000210.133.9Above2.839207196_s_atNef-associatedNAF15q32-q33.1NM_006058.132.2Above1.4factor 140219315_s_athypotheticalFLJ2089816p13.12NM_024600.132.2Above5.3protein FLJ2305841202123_s_atV-abl AbelsonABL19q34.1NM_005157.231.4Above1.8murine leukemiaviral oncogenehomolog 142219938_s_atPro-Ser-ThrPSTPIP218q12NM_024430.131.2Above5phosphataseinteracting protein 243228046_atEST; DKFZp434P0235DKFZp434P0235 4AA74124331.2Above1.14464064_atImmuneIAN4L17q36AI43508930.9Above3.3associatednucleotide 4 like 145222729_atF-box and WD-40FBXW74q31.23BE55187730.5Above2.4domain protein 7(archipelagohomolog,Drosophila)46229975_atEST 4AI82643730.5Above9.147200864_s_atRAB11ARAB11A15q21.3-q22.31NM_004663.129.7Above1.448203089_s_atProtease, serine,PRSS252p12NM_013247.129.7Above1.72549205376_atInositolINPP4B4q31.1NM_003866.129.7Above12.4polyphosphate-4-phosphatase, typeII50209229_s_atKIAA1115KIAA111519q13.42BC002799.129.7Above1.3protein51219871_atHypotheticalFLJ131974p14NM_024614.129.7Above14.5protein FLJ1319752222868_s_atInterleukin 18IL18BP11q13AI52154929.7Above7.1binding protein53235988_atGPR110 GGPR1106p12.3AA74603829.7Above15.8protein-coupledreceptor 11054239273_s_atMatrixMMP2817q11-q21.1AI92720829.7Above90.5metalloproteinase2855206150_atTumor necrosisTNFRSF712p13NM_001242.129.5Above3.2factor receptorsuperfamily,member 756212203_x_atInterferon inducedIFITM38q13.1BF33894729.5Above2.3transmembraneprotein 357217110_s_atMucin 4MUC43q29AJ242547.129.5Above47.558223075_s_athypotheticalFLJ127839q34.13-q34.3AL136566.129.5Above3.9protein FLJ1278359229139_atEST 8AI20220129.5Above10.860229367_s_atHypotheticalFLJ22690 7AW13053629.5Above3.6proteinsFLJ22690.61213093_atFLJ30869FLJ30869Xq28AI47137529.1Above2.562216033_s_atFYN oncogeneFYN 6S74774.129.1Above2.7related to SRC63202369_s_atTRAM-likeKIAA00576p21.1-p12NM_012288.128.7Above3.3protein64212592_atimmunoglobulin JIGJ4q21AV73326628.7Above7.9polypeptide, linkerprotein forimmunoglobulinalpha and mupolypeptides65219218_athypotheticalFLJ2305817q25.3NM_024696.128.7Below6.2protein FLJ2305866242051_atESTYAI69569528.7Above2.267200655_s_atCalmodulin 1CALM114q24-q31NM_006888.128.5Above1.3(phosphorylasekinase, delta)68202794_atInositolINPP12q32NM_002194.228.4Above1.6polyphosphate-1-phosphatase69218348_s_atHSPC055 proteinHSPC05516p13.3NM_014153.127.7Below1.170205269_atLymphocyteLCP25q33.1-AI12325126.9Above1.6cytosolic protein 2qter71238488_atRan bindingLOC511945q12.2BF51160226.9Above2.7protein 1172202242_atTransmembrane 4TM4SF2Xq11.4NM_004615.126.6Above1.7superfamilymember 273218764_atHypotheticalMGC536314q22.1-q22.3NM_024064.126.6Above1.7protein MGC5363q22.374224811_atFLJ30652FLJ30652 3BF11209326.6Above1.575225799_atHypotheticalMGC46772q12.3BF20933726.6Above2.2protein MGC467776228297_atCalponin 3, acidicCNN31p22-p21AI80700426.6Above4.777203508_atTumor necrosisTNFRSF1B1p36.3-p36.2NM_001066.126Above2.6factor receptorsuperfamily,member 1B78208071_s_atLeukocyte-LAIR119q13.4NM_021708.126Above2associated Ig-likereceptor 179209321_s_atAdenylate cyclaseADCY32p24-p22AF033861.126Above2.13.80226345_atDKFZp434O1317DKFZp434O131710AW27015826Below1.481200863_s_atRAB11A, memberRAB11A15q21.3-q22.31AI21510225.8Above1.4RAS oncogenefamily82205270_s_atLymphocyteLCP25q33.1-NM_005565.225.8Above1.6cytosolic protein 2qter83208881_x_atIsopentenyl-IDI110p15.3BC005247.125.8Below1.7diphosphate deltaisomerase84212862_atCDP-CDS220p13AL56898225.8Above1.8diacylglycerolsynthase(phosphatidatecytidylyltransferase) 285213385_atChimerin 2CHN2 7AK026415.125.8Above386218013_x_atDynactin 4DCTN45q31-q32NM_016221.125.8Above3.687218966_atMyosin 5CMYO5C15q21NM_018728.125.8Above1.888200742_s_atCeroid-CLN211p15BG23193225Above1.5lipofuscinosis,neuronal 2, lateinfantile (Jansky-Bielschowskydisease). Apepstatin-insensitivelysosomalpeptidase.89203217_s_atSialyltransferase 9SIAT92p11.2NM_003896.125Above1.890205259_atNuclear receptorNR3C24q31.1NM_000901.125Above1.9subfamily 3,group C, member 291220684_atT-box 21TBX2117q21.2NM_013351.125Above3.392225244_atIMAGE3451454:IMAGE341q42.13AA01989325Above2GRASP protein5145493239519_atEST10AA92767025Above18.294203005_atLymphotoxin betaLTBR12p13NM_002342.124.3Above10receptor (TNFRsuperfamily,member 3)95200665_s_atSecreted protein,SPARC5q31.3-q32NM_003118.124.3Above9.8acidic, cysteine-rich (osteonectin)96204004_atPRKC, apoptosis,PAWR12q21AI33620624.3Above3WT1, regulator97204576_s_atKIAA064316p12.3AA20701324.3Above2proteinKIAA064398214255_atATPase, Class V,ATP10C15q11-q13AB011138.124.3Above9.9type 10C99216985_s_atSyntaxin 3ASTX3A11q12.3AJ002077.124.3Above1210048106_atFLJ20489FLJ2048912p11.1H1424124.3Above2.8

[0214]

66

TABLE 64

Top 100 chi-square probe sets selected for E2A-PBX1

E2A

above/

Chromosomal
GenBank
Chi-square
below
Fold

U133 probe set
Gene Description
Symbol
Location
reference
value
mean
change

1
201579_at
FAT tumor
FAT
4q34-q35
NM_005245.1
88.0
Above
9.9

suppressor

homolog 1

(Drosophila)

2
201695_s_at
nucleoside
NP
14q13.1
NM_000270.1
88.0
Above
3.8

phosphorylase

3
204674_at
lymphoid-
LRMP
12p12.3
NM_006152.1
88.0
Above
5.8

restricted

membrane protein

4
205253_at
pre-B-cell
PBX1
1q23
NM_002585.1
88.0
Above
3549.2

leukemia

transcription

factor 1

5
212148_at
pre-B-cell
PBX1
1q23
BF967998
88.0
Above
5283.5

leukemia

transcription

factor 1, splice

variant

6
212151_at
pre-B-cell
PBX1
1q23
BF967998
88.0
Above
7472.2

leukemia

transcription

factor 1, splice

variant

7
212371_at
DKFZp586C1019
DKFZp58
1
AL049397.1
88.0
Above
2.5

6C1019

8
219155_at
retinal
RDGBBB
17q24.2
NM_012417.1
88.0
Above
2.7

degeneration

beta

9
225483_at
hypothetical
MGC10485
11q25
AI971602
88.0
Above
7.7

protein

MGC10485

10
227439_at
E2a-Pbx1-
EB-1
12
AW005572
88.0
Above
269.8

associated protein

11
227949_at
Q9H4T4 like
H17739
20q13.32
AL357503
88.0
Above
59.3

12
230306_at
hypothetical
MGC10485
11q25
AA514326
88.0
Above
19.2

protein

MGC10485

13
231095_at
retinal
RDGBBB
17q24.2
AW193811
88.0
Above
25.6

degeneration

beta

14
203372_s_at
STAT induced
SOCS2
12q
AB004903.1
80.6
Below
23.4

STAT inhibitor-2

15
206028_s_at
c-mer protooncogene
MERTK
2q14.1
NM_006343.1
80.6
Above
23.7

tyrosine

kinase

16
206181_at
signaling
SLAM
1q22-q23
NM_003037.1
80.6
Above
6.3

lymphocytic

activation

molecule

17
208788_at
homolog of yeast
HELO1
6p21.1-p12.1
AL136939.1
80.6
Above
2.2

long chain

polyunsaturated

fatty acid

elongation

enzyme 2

18
209760_at
KIAA0922
KIAA0922
4q31.23
AL136932.1
80.6
Above
2.9

protein

19
35974_at
lymphoid-
LRMP
12p12.3
U10485
80.6
Above
6.2

restricted

membrane protein

20
38340_at
huntingtin
HIP12
12q24
AB014555
80.6
Above
3.8

interacting protein

12

21
208644_at
ADP-
ADPRT
1q41-q42
M32721.1
80.2
Above
3.0

ribosyltransferase

(NAD+; poly

(ADP-ribose)

polymerase)

22
212789_at
KIAA0056
KIAA0056
11q25
AI796581
80.2
Above
3.9

protein

23
221113_s_at
wingless-type
WNT16
7q31
NM_016087.1
80.2
Above
2547.6

MMTV

integration site

family, member

16

24
224022_x_at
wingless-type
WNT16
7q31
AF169963.1
80.2
Above
569.1

MMTV

integration site

family, member

16

25
231040_at
EST

9
AW512988
80.2
Above
16.4

26
232289_at
FLJ14167
FLJ14167
17
BF237871
80.2
Above
144.1

27
235666_at
EST
FLJ20489
10
AA903473
80.2
Above
654.6

28
203373_at
STAT induced
SOCS2
12q
NM_003877.1
74.2
Below
24.8

STAT inhibitor-2

29
210785_s_at
basement
ICB-1
1p35.3
AB035482.1
74.2
Below
4.1

membrane-

induced gene

30
224733_at
chemokine-like
CKLFSF3
16q23.1
AL574900
74.2
Below
41.7

factor super

family 3

31
225235_at
hypothetical
MGC14859
5q35.3
AW007710
74.2
Above
3.6

protein

MGC14859

32
204114_at
nidogen 2
NID2
14q21-q22
NM_007361.1
73.1
Above
15.1

(osteonidogen)

33
211913_s_at
c-mer protooncogene
MERTK
2q14.1
L08961.1
72.8
Above
37.7

tyrosine

kinase

34
219551_at
uncharacterized
BM040
3q21.1
NM_018456.1
72.8
Above
3.0

bone marrow

protein BM040

35
223693_s_at
hypothetical
FLJ10324
7p22
AL136731.1
72.8
Above
65.6

protein FLJ10324

36
200600_at
moesin
MSN
Xq11.2-q12
NM_002444.1
72.5
Below
2.2

37
213909_at
FLJ12280
FLJ12280
3
AU147799
72.5
Above
12.5

38
221669_s_at
acyl-Coenzyme A
ACAD8
11q25
BC001964.1
72.5
Above
2.6

dehydrogenase

family, member 8

39
235911_at
ESTs, Weakly

3
AI885815
72.5
Above
36.6

similar to PIHUB6

salivary proline-

rich protein

precursor PRB1

(large allele)

40
243533_x_at
ESTs

H09663
72.5
Above
23.2

41
202615_at
DKFZp686D0521
DKFZp686D0521
9
BF222895
68.6
Below
6.2

42
204774_at
ecotropic viral
EVI2A
17q11.2
NM_014210.1
68.6
Below
3.0

integration site 2A

43
218283_at
synovial sarcoma
SS18L2
3p21
NM_016305.1
68.6
Above
1.6

translocation gene

on chromosome

18-like 2

44
209130_at
synaptosomal-
SNAP23
15q14
BC003686.1
67.8
Below
1.9

associated protein,

23 kDa

45
228580_at
serine protease
HTRA3
4p16.1
AI828007
66.6
Above
3.8

HTRA3

46
202796_at
synaptopodin
KIAA1029
5q33.1
NM_007286.1
66.5
Above
52.3

47
218640_s_at
phafin 2
FLJ13187
8q21.3
NM_024613.1
66.5
Above
3.1

48
235099_at
ESTs, Weakly

3
AW080832
66.5
Above
6.7

similar to

PLLP_HUMAN

Plasmolipin

[H. sapiens]

49
201889_at
family with
FAM3C
7q22.1-q31.1
NM_014888.1
65.3
Above
4.6

sequence

similarity 3,

member C

50
202106_at
golgi autoantigen,
GOLGA3
12q24.33
NM_005895.1
65.3
Above
3.3

golgin subfamily

a, 3

51
202208_s_at
ADP-ribosylation
ARL7
2q37.2
BC001051.1
65.3
Above
3.2

factor-like 7

52
205173_x_at
CD58 antigen,
CD58
1p13
NM_001779.1
65.3
Above
2.4

(lymphocyte

function-

associated antigen

3)

53
211744_s_at
CD58 antigen,
CD58
1p13
BC005930.1
65.3
Above
2.5

(lymphocyte

function-

associated antigen

3)

54
212552_at
hippocalcin-like 1
HPCAL1
2p25.1
BE617588
65.3
Below
2.6

55
213358_at
KIAA0802
KIAA0802
18p11.21
AB018345.1
65.3
Above
12.7

protein

56
222699_s_at
phafin 2
FLJ13187
8q21.3
BF439250
65.3
Above
3.5

57
225618_at
EST

17
AI769587
65.3
Below
5.3

58
238778_at
DKFZp451L157
DKFZp451L157
10
AI244661
65.3
Above
23.5

59
239427_at
ESTs

1
AA131524
65.3
Above
13.7

60
47069_at
Rho GTPase
ARHGAP8
22q13.31
AA533284
65.3
Above
3.3

activating protein 8

61
205769_at
solute carrier
SLC27A2
15q21.2
NM_003645.1
65.1
Above
56.0

family 27 (fatty

acid transporter),

member 2

62
210786_s_at
Friend leukemia
FLI1
11q24.1-q24.3
M93255.1
65.1
Above
2.2

virus integration 1

63
212985_at
DKFZp434E033
DKFZp434E033
4
BF115739
65.1
Above
7.1

64
227441_s_at
E2a-Pbx1-
EB-1
12
AW005572
65.1
Above
1139.4

associated protein

65
234261_at
DKFZp761M10121
DKFZp761M10121
12
AL137313.1
65.1
Above
960.8

66
244565_at
ESTs

10
AI685824
65.1
Above
7.6

67
202181_at
KIAA0247 gene
KIAA0247
14q24.1
NM_014734.1
63.7
Above
1.8

product

68
202207_at
ADP-ribosylation
ARL7
2q37.2
NM_005737.2
63.7
Above
3.2

factor-like 7

69
207571_x_at
basement
ICB-1
1p35.3
NM_004848.1
63.7
Below
4.4

membrane-

induced gene

70
209558_s_at
huntingtin
HIP12
12q24
AB013384.1
61.1
Above
23.8

interacting protein

12

71
213005_s_at
KIAA0172
KIAA0172
9p24.3
D79994.1
61.1
Above
8.3

protein

72
236854_at
cDNA
DKFZp667F0617
20
AA743694
61.1
Above
12.6

DKFZp667F0617

73
226233_at
tubulin-specific
TBCE
1q42.3
BG112197
60.0
Above
2.6

chaperone e

74
203435_s_at
membrane
MME
3q25.1-q25.2
NM_007287.1
59.9
Below
2.2

metallo-

endopeptidase

(neutral

endopeptidase,

enkephalinase,

CALLA, CD10)

75
202478_at
GS3955 protein
GS3955
2p25.1
NM_021643.1
59.3
Above
4.0

76
202479_s_at
GS3955 protein
GS3955
2p25.1
BC002637.1
59.3
Above
3.3

77
203999_at
synaptotagmin I
SYT1
12cen-q21
NM_005639.1
59.3
Above
3.9

78
212149_at
KIAA0143
KIAA0143
8q24.12
AA805651
59.3
Below
13.5

protein

79
212873_at
minor
HA-1
19p13.3
BE349017
59.3
Below
2.9

histocompatibility

antigen HA-1

80
218346_s_at
p53 regulated
PA26
6q21
NM_014454.1
59.3
Below
4.7

PA26 nuclear

protein

81
224856_at
FK506 binding
FKBP5
6p21.3-21.2
AL122066.1
59.3
Below
5.5

protein 5

82
200811_at
cold inducible
CIRBP
19p13.3
NM_001280.1
59.1
Below
5.8

RNA binding

protein

83
201722_s_at
UDP-N-acetyl-
GALNT1
18q12.1
NM_020474.2
59.1
Below
1.8

alpha-D-

galactosamine: polypeptide

N-acetylgalactosaminyltransferase 1

(GalNAc-T1)

84
223711_s_at
HSPC144 protein
HSPC144
11q25
AF182413.1
59.1
Above
2.0

85
233273_at
cDNA FLJ12010
FLJ12010
1
AU146834
59.1
Above
30.6

fis

86
201460_at
mitogen-activated
MAPKAPK2
1q32
AI141802
57.9
Above
2.1

protein kinase-

activated protein

kinase 2

87
202421_at
immunoglobulin
IGSF3
1p13
AB007935.1
57.9
Above
4.4

superfamily,

member 3

88
217983_s_at
ribonuclease 6
RNASE6PL
6q27
NM_003730.2
57.9
Below
3.4

precursor

89
218087_s_at
sorbin and SH3
SORBS1
10q23.3-q24.1
NM_015385.1
57.9
Above
25.1

domain containing 1

90
218491_s_at
HSPC144 protein
HSPC144
11q25
NM_014174.1
57.9
Above
1.4

91
201825_s_at
CGI-49 protein
LOC51097
1q44
AL572542
57.8
Above
2.2

92
202206_at
ADP-ribosylation
ARL7
2q37.2
NM_005737.2
57.8
Above
3.9

factor-like 7

93
218683_at
polypyrimidine
PTBP2
1p22.11-P21.3
NM_021190.1
57.8
Above
1.8

tract binding

protein 2

94
226590_at
cDNA clone

9
AA031404
57.8
Above
3.1

EUROIMAGE

1517766

95
227440_at
E2a-Pbx1-
EB-1
12
AW005572
57.8
Above
1168.9

associated protein

96
229770_at
hypothetical
FLJ31978
12q24.33
AI041543
57.8
Above
51.8

protein FLJ31978

97
40148_at
amyloid beta (A4)
APBB2
4p14
U62325
57.8
Above
6.2

precursor protein-

binding, family B,

member 2 (Fe65-

like)

98
212959_s_at
MGC4170 protein
MGC4170
12q23.1
AK001821.1
57.2
Below
3.0

99
203143_s_at
KIAA0040 gene
KIAA0040
1q24-25
T79953
56.3
Above
2.4

product

100
209683_at
hypothetical
DKFZP566A1524
2p24.2
AA243659
56.3
Below
10.0

protein

DKFZp566A1524

[0215]

67

TABLE 65

Top 100 chi-square probe sets selected for Hyperdiploid >50

HD

Chi-
above/

U133 probe

Chromosomal

square
below
Fold

set
Gene description
Symbol
Location
GenBank Ref
value
mean
change

1
200600_at
Moesin
MSN
Xq11.2-q12
NM_002444.1
34.0
Above
1.9

(membrane-

organizing

extensio spike

protein)

2
200737_at
Phosphoglycerate
PGK1
Xq13
NM_000291.1
34.0
Above
1.8

kinase 1

3
200980_s_at
Pyruvate
PDHA1
Xp22.2-p22.1
NM_000284.1
34.0
Above
1.7

dehydrogenase

(lipoamide) alpha 1

4
201136_at
Proteolipid protein
PLP2
Xp11.23
NM_002668.1
34.0
Above
3.3

2 (colonic

epithelium-

enriched)

5
201807_at
Vacuolar protein
VPS26
10q21.1
NM_004896.1
34.0
Above
1.7

sorting 26 (yeast)

6
202214_s_at
Cullin 4B
CUL4B
Xq23
NM_003588.1
34.0
Above
1.9

7
202557_at
Stress 70 protein
STCH
21q11
AI718418
34.0
Above
2.0

chaperone,

microsome

associated, 60 kD

8
202593_s_at
membrane
MIR16
16p12-p11.2
NM_016641.1
34.0
Below
1.6

interacting protein

of RGS16

9
203680_at
Protein kinase,
PRKAR2B
7q22-q31.1
NM_002736.1
34.0
Above
3.3

cAMP-dependent,

regulatory, type II,

beta

10
204194_at
BTB and CNC
BACH1
21q22.11
NM_001186.1
34.0
Above
1.8

homology 1, basic

leucine zipper

transcription

factor 1

11
205324_s_at
FtsJ homolog 1
FTSJ1
Xp11.23
NM_012280.1
34.0
Above
2.1

(E. coli)

12
208598_s_at
Upstream
UREB1
Xp11.22
NM_005703.2
34.0
Above
1.6

regulatory element

binding protein 1

13
208861_s_at
Alpha
ATRX
Xq13.1-q21.1
U72937.2
34.0
Above
1.7

thalassemia/menta

1 retardation

syndrome X-

linked (RAD54

homolog, S.

cerevisiae
)

14
211342_x_at
trinucleotide
TNRC11
Xq13
BC004354.1
34.0
Above
1.8

repeat containing

11 (THR-

associated protein,

230 kDa subunit)

15
216071_x_at
Trinucleotide
TNRC11
Xq13
AF132033
34.0
Above
1.8

repeat containing

11

16
218573_at
APR-1
MAGEH1
Xp11.22
NM_014061.1
34.0
Above
3.0

protein/melanoma-

associated

antigen

17
219485_s_at
proteasome
PSMD10
Xq22.3
NM_002814.1
34.0
Above
2.4

(prosome,

macropain) 26S

subunit, non-

ATPase, 10

18
200655_s_at
Calmodulin 1
CALM1
14q24-q31
NM_006888.1
30.1
Above
1.7

(phosphorylase

kinase, delta)

19
200738_s_at
Phosphoglycerate
PGK1
Xq13
NM_000291.1
30.1
Above
1.8

kinase 1

20
200944_s_at
High-mobility
HMG14
21q22.2
NM_004965.1
30.1
Above
1.7

group (nonhistone

chromosomal)

protein 14;

member of the

HMG 14/17

family

21
201092_at
Retinoblastoma
RBBP7
Xp22.31
NM_002893.2
30.1
Above
1.6

binding protein

7/RbAp46

22
201100_s_at
Ubiquitin specific
USP9X
Xp11.4
NM_004652.2
30.1
Above
1.7

protease 9

23
201688_s_at
Tumor protein
TPD52
8q21
BE974098
30.1
Below
4.1

D52

24
201899_s_at
Ubiquitin-
UBE2A
Xq24-q25
NM_003336.1
30.1
Above
1.8

conjugating

enzyme E2A

(RAD6 homolog)

25
202325_s_at
ATP synthase, H+
ATP5J
21q21.1
NM_001685.1
30.1
Above
1.6

transporting,

mitochondrial F0

complex, subunit

F6

26
202829_s_at
Synaptobrevin-
SYBL1
Xq28
NM_005638.1
30.1
Above
1.5

like 1

27
202854_at
Hypoxanthine
HPRT1
Xq26.1
NM_000194.1
30.1
Above
1.4

phosphoribosyltransferase

1 (Lesch-

Nyhan syndrome)

28
206846_s_at
Histone
HDAC6
Xp11.23
NM_006044.2
30.1
Above
1.5

deacetylase 6

29
209370_s_at
SH3-domain
SH3BP2
4p16.3
AB000462.1
30.1
Above
3.1

binding protein 2

30
209565_at
zinc finger protein
ZNF183
Xq25-q26
BC000832.1
30.1
Above
2.2

183

31
212846_at
KIAA0179
KIAA0179
21q22.3
D80001.1
30.1
Above
2.0

protein.

32
217356_s_at
Phosphoglycerate
PGK1
Xq13
S81916.1
30.1
Above
1.8

kinase

33
218163_at
MCT-1 protein
MCT-1
Xq22-24
NM_014060.1
30.1
Above
1.8

34
218386_x_at
Ubiquitin specific
USP16
21q22.11
NM_006447.1
30.1
Above
1.7

protease 16; de-

ubiquitinates

histone H2A;

ubiquitous

expression.

35
218402_s_at
Hermansky-
HPS4

NM_022081.1
30.1
Below
3.4

Pudlak syndrome 4

36
218495_at
Ubiquitously-
UXT
Xp11.23-p11.22
NM_004182.1
30.1
Above
1.5

expressed

transcript

37
218499_at
Mst3 and SOK1-
MST4
Xq26.1
NM_016542.1
30.1
Above
2.5

related

kinase/STE20-like

kinase; contains a

Ser/Thr protein

kinase domain

38
218757_s_at
Similar to yeast
UPF3B
Xq25-q26
NM_023010.1
30.1
Above
2.3

Upf3, variant B

39
219038_at
Hypothetical
FLJ11565
Xq22.2
NM_024657.1
30.1
Above
6.9

protein FLJ11565

40
229967_at
Chemokine-like
CKLFSF2
16q23.1
AA778552
30.1
Above
4.3

factor super

family 2.

41
242794_at
EST

4q31.1
AI569476
30.1
Above
3.2

42
201132_at
Heterogeneous
HNRPH2
Xq22
NM_019597.1
30.0
Above
2.0

nuclear

ribonucleoprotein

H2 (H')

43
201312_s_at
SH3 domain
SH3BGRL
Xq13.3
NM_003022.1
30.0
Above
1.6

binding glutamic

acid-rich protein

like

44
201894_s_at
Decorin;
DCN
12q13.2
NM_001920.1
30.0
Above
1.5

glycoprotein that

binds to type I

collagen fibrils &

plays a role in

matrix assembly.

45
201923_at
Peroxiredoxin 4
PRDX4
Xp22.13
NM_006406.1
30.0
Above
1.9

46
202371_at
Hypothetical
FLJ21174
Xq22.1
NM_024863.1
30.0
Above
3.6

protein FLJ21174

47
203126_at
Inositol (myo)-1 (or
IMPA2
18p11.2
NM_014214.1
30.0
Above
4.1

4)-

monophosphatase 2

48
204219_s_at
proteasome
PSMC1
19p13.3
NM_002802.1
30.0
Above
1.3

(prosome,

macropain) 26S

subunit, ATPase, 1

49
204835_at
polymerase (DNA
POLA
Xp22.1-p21.3
NM_016937.1
30.0
Above
2.0

directed), alpha

50
212071_s_at
Spectrin, beta,
SPTBN1
2p21
BE968833
30.0
Below
1.7

non-erythrocytic 1

51
212419_at
EST

10q22.3
AL049949.1
30.0
Above
13.1

52
212718_at
Hypothetical
MGC5378
14q32.2
BG110231
30.0
Above
1.5

protein MGC5370

53
213502_x_at

Homo sapiens

FLJ32313
22q11.23
X03529
30.0
Below
1.8

cDNA FLJ32313

fis, clone

PROST2003232,

weakly similar to

BETA-

GLUCURONIDA

SE PRECURSOR

(EC 3.2.1.31)

54
214051_at
Thymosin, beta
TMSNB
Xq21.33-q22.3
BF677486
30.0
Above
3.1

55
226039_at
Mannosyl (alpha-
MGAT4A
2q11.2
AW006441
30.0
Above
3.0

1,3)-glycoprotein

beta-1,4-N-

acetylglucosaminyltransferase

56
227279_at
hypothetical
MGC15737
Xq22.1
AA847654
30.0
Above
5.6

protein

MGC15737

57
200642_at
Superoxide
SOD1
21q22.11
NM_000454.1
26.7
Above
2.3

dismutase 1,

soluble

58
200799_at
Heat shock 70 kD
HSPA1A
6p21.3
NM_005345.3
26.7
Above
2.7

protein 1A

59
200943_at
High-mobility
HMG14
21q22.2
NM_004965.1
26.7
Above
1.6

group (nonhistone

chromosomal)

protein 14;

member of the

HMG 14/17

family

60
201018_at
Eukaryotic
EIF1A
Xp22.12
BE542684
26.7
Above
1.8

translation

initiation factor

1A

61
201311_s_at
SH3 domain
SH3BGRL
Xq13.3
AL515318
26.7
Above
1.6

binding glutamic

acid-rich protein

like

62
201443_s_at
ATPase, H+
ATP6IP2
Xq21
AF248966.1
26.7
Above
1.9

transporting,

lysosomal

interacting protein 2

63
201472_at
Von Hippel-
VBP1
Xq28
NM_003372.2
26.7
Above
1.7

Lindau binding

protein 1

64
201689_s_at
Tumor protein
TPD52
8q21
BE974098
26.7
Below
4.3

D52

65
202602_s_at
HIV TAT specific
HTATSF1
Xq26.1-q27.2
NM_014500.1
26.7
Above
1.5

factor 1

66
203041_s_at
Lysosomal-
LAMP2
Xq24
J04183.1
26.7
Above
3.1

associated

membrane protein 2

67
203102_s_at
Mannosyl (alpha-
MGAT2
14q21
NM_002408.2
26.7
Above
1.6

1,6-)-glycoprotein

beta-1,2-N-

acetylglucosaminyltransferase

68
203744_at
High-mobility
HMG4
Xq28
NM_005342.1
26.7
Above
1.9

group (nonhistone

chromosomal)

protein 4

69
205518_s_at
Cytidine
CMAH
6p22-p23
NM_003570.1
26.7
Below
2.9

monophosphate-

N-

acetylneuraminic

acid hydroxylase

(CMP-N-

acetylneuraminate

monooxygenase)

70
208683_at
Calpain 2, (m/II)
CAPN2
1q41-q42
M23254.1
26.7
Above
2.2

large subunit;

calcium-

dependent Cys

protease.

71
209440_at
Phosphoribosyl
PRPS1
Xq21-q27
BC001605.1
26.7
Above
1.4

pyrophosphate

synthetase 1;

purine

biosynthesis.

72
210786_s_at
Friend leukemia
FLI1
11q24.1-q24.3
M93255.1
26.7
Below
2.5

virus integration 1

73
212070_at
G protein-coupled
GPR56
16q13
AL554008
26.7
Above
2.4

receptor 56

74
213334_x_at
Three prime repair
TREX2
Xq28
BE676218
26.7
Above
1.7

exonuclease 2

75
215117_at
Recombination
RAG2
11p13
AW058148
26.7
Below
27.2

activating gene 2;

V(D)J

recombinase.

76
218694_at
ALEX1 protein
ALEX1
Xq21.33-q22.2
NM_016608.1
26.7
Above
2.8

77
222741_s_at
hypothetical
FLJ11101
6p21.1
AI761426
26.7
Above
1.5

protein FLJ11101

78
223082_at
SH3-domain
SH3KBP1
Xp22.1-p21.3
AF230904.1
26.7
Above
2.0

kinase binding

protein 1

79
225105_at
clone MGC: 23936

12q23.3
BF969397
26.7
Above
2.1

IMAGE: 3838595,

mRNA, complete

cds

80
225406_at
Twisted
TSG
18p11.3
AA195009
26.7
Above
1.9

gastrulation

81
225553_at

Homo sapiens

14q22.2
AL042817
26.7
Above
1.6

cDNA FLJ12874

fis

82
226199_at
Hypothetical
MGC23937
Xq13.1
AL563795
26.7
Above
2.1

protein

MGC23937

83
226875_at
Hypothetical
FLJ32122
Xq24
AI742838
26.7
Above
2.3

protein FLJ32122

84
232974_at
cDNA FLJ12417

Xp22.31
AU148256
26.7
Above
3.1

fis

85
46323_at
SCAN-1 Ca++-
SHAPY
17q25.3
AL120741
26.7
Above
1.7

dependent ER

nucleoside

diphosphatase/apy

rase

86
203694_s_at
DEAD/H (Asp-
DDX16
6p21.3
NM_003587.2
26.3
Above
1.3

Glu-Ala-Asp/His)

box polypeptide

16

87
200658_s_at
Prohibitin
PHB
17q21
AL560017
26.3
Above
2.0

88
201898_s_at
ubiquitin-
UBE2A
Xq24-q25
AI126625
26.3
Above
1.6

conjugating

enzyme E2A

(RAD6 homolog)

89
203556_at
KIAA0854
KIAA0854
8q24.13
NM_014943.1
26.3
Below
1.6

protein

90
203745_at
Holocytochrome c
HCCS
Xp22.3
AI801013
26.3
Above
2.1

synthase

(cytochrome c

heme-lyase)

91
203909_at
Solute carrier
SLC9A6
Xq26.3
NM_006359.1
26.3
Above
1.9

family 9

(sodium/hydrogen

exchanger),

isoform 6

92
204446_s_at
Arachidonate 5-
ALOX5
10q11.2
NM_000698.1
26.3
Above
4.2

lipoxygenase

93
205191_at
Retinitis
RP2
Xp11.4-p11.21
NM_006915.1
26.3
Above
2.1

pigmentosa 2 (X-

linked recessive)

94
206874_s_at
Ste20-related
SLK
10q25.1
AL138761
26.3
Above
1.6

serine/threonine

kinase

95
208073_x_at
Tetratricopeptide
TTC3
21q22.2
NM_003316.1
26.3
Above
1.9

repeat domain 3

96
209056_s_at
CDC5 cell
CDC5L
6p21
AW268817
26.3
Above
1.4

division cycle 5-

like (S. pombe)

97
210645_s_at
Tetratricopeptide
TTC3
21q22.2
D83077.1
26.3
Above
2.2

repeat domain 3

98
215773_x_at
ADP-
ADPRTL2
14q11.2-q12
AJ236912.1
26.3
Above
1.6

ribosyltransferase

(NAD+;

poly(ADP-ribose)

polymerase)-like 2

99
215884_s_at
Ubiquilin 2
UBQLN2
Xp11.23-p11.1
AK001029.1
26.3
Above
1.9

100
217954_s_at
PHD finger
PHF3
6
NM_015153.1
26.3
Above
1.5

protein 3

[0216]

68

TABLE 66

Top 100 chi-square probe sets selected for MLL

MLL

Chi-
above/

U133 probe

Chromosomal

square
below
Fold

set
Description
Symbol
Location
GenBank Ref
value
mean
change

1
202603_at
a disintegrin and
ADAM10
15q22
N51370
44.6
Above
1.8

metalloproteinase

domain 10

2
219463_at
chromosome 20
C20orf103
20p12
NM_012261.1
44.6
Above
24.7

open reading

frame 103

3
224772_at
neuron navigator 1
NAV1

AB032977.1
44.6
Below
3.8

4
204069_at
Meis1, myeloid
MEIS1
2p14-p13
NM_002398.1
44.4
Above
73.7

ecotropic viral

integration site 1

homolog

5
218966_at
myosin 5C
MYO5C
15q21
NM_018728.1
44.4
Below
4.5

6
226939_at
cDNA FLJ37247
FLJ37247

AI202327
44.4
Above
6.9

fis

7
204446_s_at
arachidonate 5-
ALOX5
10q11.2
NM_000698.1
40.7
Below
66.8

lipoxygenase

8
206492_at
fragile histidine
FHIT
3p14.2
NM_002012.1
40.7
Below
36.6

triad gene

9
212588_at
protein tyrosine
PTPRC
1q31-q32
AI809341
40.7
Above
2.3

phosphatase,

receptor type, C

10
215925_s_at
CD72 antigen
CD72
9p11.2
AF283777.2
40.7
Above
3.0

(ligand for CD5)

11
211733_x_at
sterol carrier
SCP2
1p32
BC005911.1
40.1
Above
1.5

protein 2

12
212386_at
cDNA FLJ11918
FLJ11918

AK021980.1
40.1
Below
3.1

fis

13
218764_at
Protein Kinase C
PRKCH
14q22.1-q22.3
NM_024064.1
40.1
Below
7.6

eta isoform.

14
218847_at
IGF-II mRNA-
IMP-2
3q28
NM_006548.1
40.1
Above
23.2

binding protein 2

15
222409_at
coronin, actin
CORO1C
12q24.1
AL162070.1
40.1
Above
4.8

binding protein,

1C

16
242172_at
ESTs

N50406
40.1
Above
33.6

17
201153_s_at
muscleblind-like
MBNL
3q25
NM_021038.1
40.0
Above
2.1

(Drosophila)

18
210487_at
deoxynucleotidyltransferase,
DNTT
10q23-q24
M11722.1
40.0
Below
2.9

terminal

19
219686_at
gene for
HSA250839
4p16.2
NM_018401.1
40.0
Below
28.3

serine/threonine

protein kinase

20
226981_at

Homo sapiens,

AW002079
37.4
Below
1.0

clone

IMAGE: 4401491,

mRNA

21
203375_s_at
tripeptidyl
TPP2
13q32-q33
NM_003291.1
37.2
Above
1.6

peptidase II

22
221676_s_at
coronin, actin
CORO1C
12q24.1
BC002342.1
37.2
Above
3.5

binding protein,

1C

23
201152_s_at
muscleblind-like
MBNL
3q25
NM_021038.1
36.2
Above
2.2

(Drosophila)

24
221773_at
ELK3, ETS-
ELK3
12q23
AW575374
36.2
Below
8.2

domain protein

(SRF accessory

protein 2)

25
201162_at
insulin-like
IGFBP7
4q12
NM_001553.1
36.0
Above
4.3

growth factor

binding protein 7

26
201163_s_at
insulin-like
IGFBP7
4q12
NM_001553.1
36.0
Above
4.0

growth factor

binding protein 7

27
203836_s_at
mitogen-activated
MAP3K5
6q22.33
D84476.1
36.0
Above
13.9

protein kinase

kinase kinase 5

28
203837_at
mitogen-activated
MAP3K5
6q22.33
NM_005923.2
36.0
Above
4.2

protein kinase

kinase kinase 5

29
213891_s_at
cDNA FLJ11918
FLJ11918

AI927067
36.0
Below
3.2

fis

30
214895_s_at
a disintegrin and
ADAM10
15q22
AU135154
36.0
Above
1.9

metalloproteinase

domain 10

31
226415_at
KIAA1576
KIAA1576
16q22.1
AA156723
36.0
Above
40.7

protein

32
235879_at
ESTs

AI697540
36.0
Above
3.8

33
212387_at
cDNA FLJ11918
FLJ11918

AK021980.1
35.8
Below
3.3

fis

34
218988_at
bladder cancer
BLOV1
12q15
NM_018656.1
35.8
Below
16.3

overexpressed

protein

35
228555_at
EST; by BLAT
CAMK2D

AA029441
35.8
Above
3.1

calcium/calmodulin-

dependent

Protine Kinase

type II Delta chain

(CAMK GROUP

I)

36
202975_s_at
Rho-related BTB
RHOBTB3
5q21.2
N21138
35.3
Above
5.5

domain containing 3

37
201105_at
lectin, galactoside-
LGALS1
22q13.1
NM_002305.2
34.5
Above
14.5

binding, soluble, 1

(galectin 1)

38
203434_s_at
membrane
MME
3q25.1-q25.2
AI433463
34.1
Below
31.2

metallo-

endopeptidase

(neutral

endopeptidase,

enkephalinase,

CALLA, CD10)

39
212135_s_at
calcium
ATP2B4

AW517686
34.1
Below
2.4

transporting

ATPase plasma

membrane

protein.

40
212136_at
calcium
ATP2B4

AW517686
34.1
Below
2.1

transporting

ATPase plasma

membrane

protein.

41
230179_at
cDNA
DKFZp547P158

N52572
34.1
Below
6.4

DKFZp547P158

42
218217_at
likely homolog of
RISC
17q23.2
NM_021626.1
32.8
Above
3.4

rat and mouse

retinoid-inducible

serine

carboxypeptidase

43
225841_at
hypothetical
FLJ30525
1p13.2
BE502436
32.8
Above
1.8

protein FLJ30525

44
226668_at

Homo sapiens,

W80623
32.8
Above
2.4

similar to WD

domain, G-beta

repeat containing

protein

45
200989_at
hypoxia-inducible
HIF1A
14q21-q24
NM_001530.1
32.2
Below
1.8

factor 1, alpha

subunit (basic

helix-loop-helix

transcription

factor)

46
201151_s_at
muscleblind-like
MBNL
3q25
NM_021038.1
32.2
Above
2.6

(Drosophila)

47
201563_at
sorbitol
SORD
15q15.3
L29008.1
32.2
Above
1.8

dehydrogenase

48
203753_at
transcription
TCF4
18q21.1
NM_003199.1
32.2
Below
2.9

factor 4

49
205668_at
lymphocyte
LY75
2q24
NM_002349.1
32.2
Above
2.1

antigen 75

50
206471_s_at
plexin C1
PLXNC1
12q23.3
NM_005761.1
32.2
Above
7.7

51
211302_s_at
phosphodiesterase
PDE4B
1p31
L20966.1
32.2
Below
3.0

4B, cAMP-

specific

52
212012_at
Melanoma
D2S448
2pter-
AF200348.1
32.2
Below
2.4

associated gene

p25.1

53
212063_at
CD44 antigen
CD44
11p13
BE903880
32.2
Above
3.1

54
213241_at
PLEXIN c1
PLXNC1

AF035307.1
32.2
Above
2.5

55
214651_s_at
homeo box A9
HOXA9
7p15-p14
U41813.1
32.2
Above
28.5

56
218140_x_at
APMCF1 protein
APMCF1
3q22.2
NM_021203.1
32.2
Above
1.4

57
219988_s_at
hypothetical
FLJ10597
1p34.1
NM_018150.1
32.2
Above
1.9

protein FLJ10597

58
223046_at
egl nine homolog
EGLN1
1q42.1
NM_022051.1
32.2
Below
4.2

1 (C. elegans)

59
224150_s_at
p10-binding
BITE
3q22-q23
AF289495.1
32.2
Above
2.1

protein

60
224933_s_at
hypothetical
DKFZp761F0118
10q22.1
AB037801.1
32.2
Above
1.9

protein

DKFZp761F0118

61
201078_at
transmembrane 9
TM9SF2
13q32.3
NM_004800.1
32.0
Above
1.5

superfamily

member 2

62
205550_s_at
brain and
BRE
2p23.3
NM_004899.1
32.0
Above
2.0

reproductive

organ-expressed

(TNFRSF1A

modulator)

63
212382_at
cDNA FLJ11918
FLJ11918

AK021980.1
32.0
Below
2.7

fis

64
225019_at
calcium/calmodulin-
CAMK2D
4q25
AA777512
32.0
Above
3.6

dependent

protein kinase

(CaM kinase) II

delta

65
225202_at
Rho-related BTB
RHOBTB3
5q21.2
BE620739
32.0
Above
5.5

domain containing 3

66
228855_at
nudix (nucleoside
NUDT7

AI927964
32.0
Above
5.6

diphosphate

linked moiety X)-

type motif 7

67
231899_at
KIAA1726
KIAA1726
11q23.1
AB051513.1
32.0
Above
33.0

protein

68
52164_at
chromosome 11
C11orf24
11q13
AA065185
32.0
Above
2.3

open reading

frame 24

69
212660_at
KIAA0239
KIAA0239
5q31.1
AI735639
31.7
Below
1.7

protein

70
213513_x_at
actin related
ARPC2
2q36.1
BG034239
31.7
Above
1.3

protein 2/3

complex, subunit

2, 34 kDa

71
222603_at
hypothetical
FLJ23309
9p24
AL136980
31.7
Above
3.6

protein FLJ23309

72
238558_at
ESTs

AI445833
31.7
Above
3.8

73
202391_at
brain abundant,
BASP1
5p15.1-p14
NM_006317.1
31.3
Above
2.1

membrane

attached signal

protein 1

74
202604_x_at
a disintegrin and
ADAM10
15q22
NM_001110.1
31.3
Above
1.8

metalloproteinase

domain 10

75
203435_s_at
membrane
MME
3q25.1-q25.2
NM_007287.1
31.3
Below
54.8

metallo-

endopeptidase

(neutral

endopeptidase,

enkephalinase,

CALLA, CD10)

76
204445_s_at
arachidonate 5-
ALOX5
10q11.2
AI361850
31.3
Below
687.0

lipoxygenase

77
209705_at
likely ortholog of
M96
1p22.1
AF073293.1
31.3
Below
1.5

mouse metal

response element

binding

transcription

factor 2

78
214366_s_at
arachidonate 5-
ALOX5
10q11.2
AA995910
31.3
Below
54.7

lipoxygenase

79
215000_s_at
fasciculation and
FEZ2
2p21
AL117593.1
31.3
Above
1.7

elongation protein

zeta 2 (zygin II)

80
220643_s_at
Fas apoptotic
FAIM
3q23
NM_018147.1
31.3
Above
2.9

inhibitory

molecule

81
226459_at

Homo sapiens

AW575754
31.3
Above
1.6

gastric cancer-

related protein

GCYS-20 (gcys-

20) mRNA,

complete cds;

homology with

mouse epidermal

growth factor

receptor pathway

substrate 8

82
238712_at
ESTs

BF801735
31.3
Above
2.7

83
229686_at
cDNA FLJ35637
FLJ35637

AI436587
31.0
Below
1.5

fis

84
222620_s_at
hypothetical
DNAJL1
10p11.23
BF591419
29.8
Above
2.4

protein similar to

mouse Dnajl1

85
224516_s_at
hypothetical
HSPC195
5q31.3
BC006428.1
29.8
Above
2.7

protein HSPC195

86
203217_s_at
sialyltransferase 9
SIAT9
2p11.2
NM_003896.1
28.8
Below
2.1

(CMP-

NeuAc: lactosylceramide

alpha-2,3-

sialyltransferase;

GM3 synthase)

87
204030_s_at
schwannomin
SCHIP1
3q25.32
NM_014575.1
28.8
Below
17.6

interacting protein 1

88
209191_at
tubulin beta-5
TUBB-5

BC002654.1
28.8
Above
6.4

89
213541_s_at
v-ets
ERG
21q22.3
AI351043
28.8
Below
2.8

erythroblastosis

virus E26

oncogene like

(avian)

90
213773_x_at
Williams Beuren
WBSCR20A
7q11.23
AW248552
28.8
Above
1.3

syndrome

chromosome

region 20A

91
219243_at
immunity
HIMAP4
7q35
NM_018326.1
28.8
Below
13.4

associated protein 4

92
219256_s_at
hypothetical
FLJ20356
4p16.1
NM_018986.1
28.8
Below
2.6

protein FLJ20356

93
223358_s_at
phosphodiesterase
PDE7A
8q13
AW269834
28.8
Above
1.5

7A

94
224796_at
development and
DDEF1
8q24.1-q24.2
W03103
28.8
Below
1.8

differentiation

enhancing factor 1

95
203076_s_at
MAD, mothers
MADH2
18q21.1
U65019.1
28.7
Below
2.0

against

decapentaplegic

homolog 2

(Drosophila)

96
212385_at
cDNA FLJ11918
FLJ11918

AK021980.1
28.7
Below
3.2

fis

97
216026_s_at
polymerase (DNA
POLE
12q24.3
AL080203.1
28.7
Below
3.0

directed), epsilon

98
217118_s_at
KIAA0930
KIAA0930
22q13.31
AK025608.1
28.7
Above
1.9

protein

99
219821_s_at
hypothetical
FLJ20330
6pter-
NM_018988.1
28.7
Below
5.5

protein FLJ20330

p22.1

100
201875_s_at
hypothetical
FLJ21047
1q23.2
NM_024569.1
28.5
Above
2.0

protein FLJ21047

[0217]

69

TABLE 67

Top 100 chi-square probe sets selected for T-ALL

T-ALL

above/

U133 probe

Chromosomal

Chi-
below
Fold

set
Gene Description
Symbol
Location
GenBank Ref
square
mean
change

1
201137_s_at
major
HLA-
6p21.3
NM_002121.1
100.0
Below
21.0

histocompatibility
DPB1

complex, class II,

DP beta 1

2
202113_s_at
sorting nexin 2
SNX2
5q23
AF043453.1
100.0
Below
4.2

3
202114_at
sorting nexin 2
SNX2
5q23
NM_003100.1
100.0
Below
4.6

4
203675_at
nucleobindin 2
NUCB2
11p15.1-p14
NM_005013.1
100.0
Above
3.6

5
204670_x_at
major
HLA-
6p21.3
NM_002125.1
100.0
Below
13.4

histocompatibility
DRB3

complex, class II,

DR beta 3

6
205297_s_at
CD79B antigen
CD79B
17q23
NM_000626.1
100.0
Below
23.3

(immunoglobulin-

associated beta)

7
205456_at
CD3E antigen,
CD3E
11q23
NM_000733.1
100.0
Above
20.7

epsilon

polypeptide (TiT3

complex)

8
206398_s_at
CD19 antigen
CD19
16p11.2
NM_001770.1
100.0
Below
5693.6

9
208306_x_at
major
HLA-
6p21.3
NM_021983.2
100.0
Below
8.3

histocompatibility
DRB4

complex, class II,

DR beta 4

10
208894_at
major
HLA-
6p21.3
M60334.1
100.0
Below
20.9

histocompatibility
DRA

complex, class II,

DR alpha

11
209312_x_at
major
HLA-
6p21.3
U65585.1
100.0
Below
12.6

histocompatibility
DRB1

complex, class II,

DR beta 1

12
209619_at
CD74 antigen
CD74
5q32
K01144.1
100.0
Below
15.1

(invariant

polypeptide of

major

histocompatibility

complex, class II

antigen-

associated)

13
210116_at
SH2 domain
SH2D1A
Xq25-q26
AF072930.1
100.0
Above
150.7

protein 1A,

Duncan's disease

(lymphoproliferative

syndrome)

14
210982_s_at
major
HLA-
6p21.3
M60333.1
100.0
Below
23.4

histocompatibility
DRA

complex, class II,

DR alpha

15
211990_at
major
HLA-
6p21.3
M27487.1
100.0
Below
19.6

histocompatibility
DPA1

complex, class II,

DP alpha 1

16
211991_s_at
major
HLA-
6p21.3
M27487.1
100.0
Below
24.5

histocompatibility
DPA1

complex, class II,

DP alpha 1

17
213539_at
CD3D antigen,
CD3D
11q23
NM_000732.1
100.0
Above
35.7

delta polypeptide

(TiT3 complex)

18
214049_x_at
CD7 antigen (p41)
CD7
17q25.2-q25.3
AI829961
100.0
Above
312.2

19
214551_s_at
CD7 antigen (p41)
CD7
17q25.2-q25.3
NM_006137.2
100.0
Above
228.1

20
217147_s_at
T-cell receptor
TRIM
3q13
AJ240085.1
100.0
Above
42.6

interacting

molecule

21
217478_s_at
MHC, class IIa,
HLA-

X76775
100.0
Below
11.9

HLA-DMA
DMA

22
221969_at
paired box gene 5
PAX5
9p13
BF510692
100.0
Below
3922.0

(B-cell lineage

specific activator

protein)

23
227646_at
early B-cell factor
EBF
5q34
BG435302
100.0
Below
85.0

24
229487_at
cDNA FLJ39389
FLJ39389
5
W73890
100.0
Below
7685.7

fis

25
229838_at
cDNA FLJ39156
FLJ39156

AI377271
100.0
Above
12.7

fis

26
232204_at
early B-cell factor
EBF
5q34
AF208502.1
100.0
Below
7129.1

27
203965_at
ubiquitin specific
USP20
9q34.12-q34.13
NM_006676.1
91.3
Above
9.0

protease 20

28
204891_s_at
lymphocyte-
LCK
1p34.3
NM_005356.1
91.3
Above
13.8

specific protein

tyrosine kinase

29
205255_x_at
transcription
TCF7
5q31.1
NM_003202.1
91.3
Above
8.4

factor 7 (T-cell

specific, HMG-

box)

30
207655_s_at
B-cell linker
BLNK
10q23.2-q23.33
NM_013314.1
91.3
Below
103.2

31
209771_x_at
CD24 antigen
CD24
6q21
AA761181
91.3
Below
40.1

(small cell lung

carcinoma cluster

4 antigen)

32
211796_s_at
T cell receptor
TRB
7q34
AF043179.1
91.3
Above
20.7

beta locus

33
213792_s_at
insulin receptor
INSR
19p13.3-p13.2
AA485908
91.3
Below
8.0

34
215193_x_at
major
HLA-
6p21.3
AJ297586.1
91.3
Below
12.1

histocompatibility
DRB3

complex, class II,

DR beta 3

35
216379_x_at
KIAA1919
KIAA1919
6q22.1
AK000168.1
91.3
Below
44.0

protein

36
219191_s_at
bridging integrator 2
BIN2
12q13
NM_016293.1
91.3
Above
271.0

37
219563_at
hypothetical
FLJ21276
14q32.2
NM_024633.1
91.3
Below
5.8

protein FLJ21276

38
219724_s_at
KIAA0748 gene
KIAA0748
12q12
NM_014796.1
91.3
Above
11.6

product

39
221750_at
3-hydroxy-3-
HMGCS1
5p14-p13
BG035985
91.3
Above
3.4

methylglutaryl-

Coenzyme A

synthase 1

(soluble)

40
226157_at
cDNA FLJ39131
FLJ39131
3
AI569747
91.3
Above
4.4

fis

41
226496_at
hypothetical
FLJ22611
9p11.1
BG291039
91.3
Below
7.6

protein FLJ22611

42
266_s_at
CD24 antigen
CD24
6q21
L33930
91.3
Below
69.7

(small cell lung

carcinoma cluster

4 antigen)

43
39318_at
T-cell
TCL1A
14q32.1
X82240
91.3
Below
367.4

leukemia/lymphoma

1A

44
204214_s_at
RAB32, member
RAB32
6q24.3
NM_006834.1
90.6
Above
127.9

RAS oncogene

family

45
204777_s_at
mal, T-cell
MAL
2cen-q13
NM_002371.2
90.6
Above
96.8

differentiation

protein

46
204890_s_at
lymphocyte-
LCK
1p34.3
U07236.1
90.6
Above
18.6

specific protein

tyrosine kinase

47
205049_s_at
CD79A antigen
CD79A
19q13.2
NM_001783.1
90.6
Below
11.4

(immunoglobulin-

associated alpha)

48
205254_x_at
transcription
TCF7
5q31.1
AW027359
90.6
Above
352.0

factor 7 (T-cell

specific, HMG-

box)

49
205504_at
Bruton
BTK
Xq21.33-q22
NM_000061.1
90.6
Below
6.6

agammaglobuline

mia tyrosine

kinase

50
210915_x_at
T cell receptor
TRB
7q34
M15564.1
90.6
Above
15.9

beta locus

51
211211_x_at
SH2 domain
SH2D1A
Xq25-q26
AF100542.1
90.6
Above
1963.5

protein 1A,

Duncan's disease

(lymphoproliferative

syndrome)

52
213830_at
T cell receptor
TRD
14q11.2
AW007751
90.6
Above
7411.2

delta locus

53
216191_s_at
T cell receptor
TRD
14q11.2
X72501.1
90.6
Above
253.7

delta locus

54
217143_s_at
T cell receptor
TRD
14q11.2
X06557.1
90.6
Above
151.9

delta locus

55
219528_s_at
B-cell
BCL11B
14q32.31-q32.32
NM_022898.1
90.6
Above
11.6

CLL/lymphoma

11B (zinc finger

protein)

56
220418_at
ubiquitin
UBASH3A
21q22.3
NM_018961.1
90.6
Above
759.3

associated and

SH3 domain

containing, A

57
222895_s_at
B-cell
BCL11B
14q32.31-q32.32
AA918317
90.6
Above
11.7

CLL/lymphoma

11B (zinc finger

protein)

58
223553_s_at
hypothetical
FLJ22570
5q35.3
BC004564.1
90.6
Below
6.1

protein FLJ22570

59
225090_at
HRD1 protein
HRD1
11q12
AA844682
90.6
Below
3.6

60
226459_at

Homo sapiens

AW575754
90.6
Below
10.7

gastric cancer-

related protein

GCYS-20 (gcys-

20) mRNA,

complete cds

61
228314_at
cDNA FLJ37485
FLJ37485

BE877357
90.6
Below
4.7

fis

62
201384_s_at
membrane
M17S2
17q21.1
NM_005899.1
83.8
Above
3.3

component,

chromosome 17,

surface marker 2

(ovarian

carcinoma antigen

CA125)

63
202540_s_at
3-hydroxy-3-
HMGCR
5q13.3-q14
NM_000859.1
83.8
Above
4.4

methylglutaryl-

Coenzyme A

reductase

64
203198_at
cyclin-dependent
CDK9
9q34.1
NM_001261.1
83.8
Below
4.8

kinase 9 (CDC2-

related kinase)

65
203932_at
major
HLA-
6p21.3
NM_002118.1
83.8
Below
7.9

histocompatibility
DMB

complex, class II,

DM beta

66
204613_at
phospholipase C,
PLCG2
16q24.1
NM_002661.1
83.8
Below
3.9

gamma 2

(phosphatidylinositol-

specific)

67
205267_at
POU domain,
POU2AF1
11q23.1
NM_006235.1
83.8
Below
11.2

class 2,

associating factor 1

68
208650_s_at
CD24 antigen
CD24
6q21
BG327863
83.8
Below
74.7

(small cell lung

carcinoma cluster

4 antigen)

69
208651_x_at
CD24 antigen
CD24
6q21
M58664.1
83.8
Below
52.7

(small cell lung

carcinoma cluster

4 antigen)

70
209995_s_at
T-cell
TCL1A
14q32.1
BC003574.1
83.8
Below
20166.2

leukemia/lymphoma 1A

71
210038_at
protein kinase C,
PRKCQ
10p15
AL137145
83.8
Above
12.7

theta

72
211126_s_at
cysteine and
CSRP2
12q21.1
U46006.1
83.8
Below
18.0

glycine-rich

protein 2

73
220068_at
pre-B lymphocyte
VPREB3
22q11.23
NM_013378.1
83.8
Below
6559.8

gene 3

74
226245_at
cDNA
DKFZp451C132

U55984
83.8
Above
8.7

DKFZp451C132

75
202615_at
cDNA
DKFZp686D0521

BF222895
82.2
Above
3.1

DKFZp686D0521

76
224861_at
cDNA FLJ31057
FLJ31057

BF477658
82.2
Above
3.5

fis

77
201194_at
selenoprotein W, 1
SEPW1
19q13.3
NM_003009.1
82.0
Above
3.8

78
201349_at
solute carrier
SLC9A3R1
17q25.2
NM_004252.1
82.0
Above
2.9

family 9

(sodium/hydrogen

exchanger),

isoform 3

regulatory factor 1

79
202539_s_at
3-hydroxy-3-
HMGCR
5q13.3-q14
AL518627
82.0
Above
3.5

methylglutaryl-

Coenzyme A

reductase

80
203588_s_at
transcription
TFDP2
3q23
BG034328
82.0
Above
17.5

factor Dp-2 (E2F

dimerization

partner 2)

81
204852_s_at
protein tyrosine
PTPN7
1q32.1
NM_002832.1
82.0
Above
9.5

phosphatase, non-

receptor type 7

82
207434_s_at
FXYD domain
FXYD2
11q23
NM_021603.1
82.0
Above
14.6

containing ion

transport regulator 2

83
208872_s_at
DNA segment,
D5S346
5q22-q23
AA814140
82.0
Below
2.6

single copy probe

LNS-CAI/LNS-

CAII

84
209200_at
MADS box
MEF2C
5q14
N22468
82.0
Below
7.5

transcription

enhancer factor 2,

polypeptide C

(myocyte

enhancer factor

2C)

85
212795_at
KIAA1033
KIAA1033
12q24.11
AL137753.1
82.0
Below
2.4

protein

86
212827_at
immunoglobulin
IGHM
14q32.33
X17115.1
82.0
Below
13.1

heavy constant mu

87
213193_x_at
T cell receptor
TRB
7q34
AL559122
82.0
Above
10.9

beta locus

88
221002_s_at
tetraspanin similar
DC-
10q23.2
NM_030927.1
82.0
Below
2.1

to TM4SF9
TM4F2

89
225314_at
hypothetical
MGC45416
4p12
BG291649
82.0
Above
5.5

protein

MGC45416

90
227432_s_at
insulin receptor
INSR
19p13.3-p13.2
AI215106
82.0
Below
6.0

91
203332_s_at
inositol
INPP5D
2q36-q37
NM_005541.1
81.5
Below
2.2

polyphosphate-5-

phosphatase,

145 kDa

92
203589_s_at
transcription
TFDP2
3q23
NM_006286.1
81.5
Above
35.1

factor Dp-2 (E2F

dimerization

partner 2)

93
205674_x_at
FXYD domain
FXYD2
11q23
NM_001680.2
81.5
Above
12.2

containing ion

transport regulator 2

94
209881_s_at
Linker for
LAT
16q13
AF036905.1
81.5
Above
1823.4

activation of T

cells

95
211005_at
Linker for
LAT
16q13
AF036906.1
81.5
Above
67.8

activation of T

cells

96
211075_s_at
CD47
CD47

Z25521.1
81.5
Above
2.1

97
211210_x_at
SH2 domain
SH2D1A
Xq25-q26
AF100539.1
81.5
Above
300.2

protein 1A,

Duncan's disease

(lymphoproliferative

syndrome)

98
213601_at
slit homolog 1
SLITI
10q23.3-q24
AB011537.2
81.5
Above
1752.1

(Drosophila)

99
213857_s_at
CD47 antigen
CD47
3q13.1-q13.2
BG230614
81.5
Above
2.2

(Rh-related

antigen, integrin-

associated signal

transducer)

100
214924_s_at
KIAA1042
KIAA1042
3p25.3-p24.1
AK000754.1
81.5
Below
2.3

protein

[0218]

70

TABLE 68

Top 100 chi-square probe sets selected for TEL-AML1

TEL-

AML

Chi-
above/

U133 probe
Gene

Chromosomal

square
below
Fold

set
Description
Symbol
Location
GenBank Ref
value
mean
change

1
224722_at
KIAA1323
KIAA1323
18q11.1
W80418
75
Above
7.6

2
227377_at
FLJ12722
FLJ12722
17q21.32
AK022784.1
75
Above
2446.3

3
237206_at
EST

17p12
AI452798
75
Above
23.7

4
241505_at
EST

BF513468
75
Above
13.4

5
203184_at
Fibrillin 2
FBN2
5q23.2
NM_001999.2
69.1
Above
14.4

(congenital

contractural

arachnodactyly)

6
205109_s_at
Rho guanine
ARHGEF4
2q22
NM_015320.1
69.1
Above
148.1

nucleotide

exchange factor

(GEF) 4

7
210650_s_at
Piccolo
PCLO
7q21.11
BC001304.1
69.1
Above
101.2

8
213558_at
Piccolo
PCLO
7q21.11
AB011131.1
69.1
Above
77.5

9
220451_s_at
Livin IAP
BIRC7
20q13.3
NM_022161.1
69.1
Above
25.4

(inhibitor of

apoptosis)

10
224720_at
KIAA1323
KIAA1323
18q11.1
W80418
69.1
Above
4.3

11
235694_at
IMAGE: 4661943

20q13.33
N49233
69.1
Above
9.3

Unknown EST

12
202808_at
Hypothetical
FLJ20154
10q24.32
AK000161.1
68.9
Above
3.7

protein FLJ20154

13
206032_at
Desmocollin 3
DSC3
18q12.1
AI797281
68.9
Above
54.1

14
206033_s_at
Desmocollin 3
DSC3
18q12.1
NM_001941.2
68.9
Above
357.1

15
209228_x_at
Putative prostate
N33
8p22
U42349.1
68.9
Above
20.8

cancer tumor

suppressor gene

N33

16
224725_at
KIAA1323
KIAA1323
18q11.1
W80418
68.9
Above
3.6

17
203910_at
PTPL1-associated
PARG1
1p22.1
NM_004815.1
64
Above
7.1

RhoGAP

18
204849_at
Transcription
TCFL5
20q13.33
NM_006602.1
64
Above
8.9

factor-like 5

(helix-loop-helix

domain)

19
206231_at
Potassium
KCNN1
19p13.1
NM_002248.2
64
Above
72.7

intermediate/small

conductance

calcium-activated

channel,

subfamily N,

member 1

20
208056_s_at
Core-binding
CBFA2T3
16q24
NM_005187.2
63
Above
2.5

factor, runt

domain, alpha

subunit 2;

translocated to, 3

21
211222_s_at
Huntingtin-
HAP1
17q21.2
AF040723.1
63
Above
80.8

associated protein

1 (neuroan 1,

HAP-1)

22
223468_s_at
hypothetical
RGM
15q26.1
AL136826.1
63
Above
10.6

protein from

EUROIMAGE

363668 RGM:

likely ortholog of

chicken repulsive

guidance molecule

23
227266_s_at
FYN-binding
FYB
5p13.1
BF679849
63
Above
3.1

protein

24
228158_at
Lymphocyte-

2p11.1
AI623211
63
Above
7.9

specific protein 1

25
37986_at
EPO receptor
EPOR
19p13.2
M60459
63
Above
15.5

26
203464_s_at
Epsin 2
EPN2
17p11.1
NM_014964.1
62.9
Above
43.3

27
213317_at
chloride
CLIC5
6p21.1
AL049313.1
62.9
Above
99.3

intracellular

channel 5

28
213423_x_at
Putative prostate
N33
8p22
AI884858
62.9
Above
15.7

cancer tumor

suppressor

29
226817_at
Desmocollin 2
DSC2
18q12.1
AU154691
62.9
Above
48.3

30
227862_at
ESTs

1p35.1
AA037766
62.9
Above
14.7

31
229339_at
EST

17p12
AI093327
62.9
Above
31.1

32
211795_s_at
FYN binding
FYB
5p13.1
AF198052.1
59.4
Above
4.1

protein

33
218627_at
Hypothetical
FLJ11259
12q23.1
NM_018370.1
57.9
Above
4.6

protein FLJ11259

34
221748_s_at

Homo sapiens

TNS
2q35
AL046979
57.9
Above
6.6

cDNA FLJ32766

fis

35
200709_at
FK506 binding
FKBP1A
20p13
NM_000801.1
57.1
Above
1.8

protein 1A (12 kD)

36
204615_x_at
Isopentenyl-
IDI1
10p15.3
NM_004508.1
57.1
Above
2.6

diphosphate delta

isomerase

37
208881_x_at
Isopentenyl-
IDI1
10p15.3
BC005247.1
57.1
Above
2.6

diphosphate delta

isomerase

38
213301_x_at
Transcriptional
TIF1
7q34
AL538264
57.1
Above
2.0

intermediary

factor 1

39
221747_at
Tensin
TNS
2q35
AL046979
57.1
Above
49.2

40
224726_at
KIAA1323
KIAA1323
18q11.1
W80418
57.1
Above
26.1

41
231455_at
ESTs

2p25.2
AA768888
57.1
Above
7.7

42
232750_at

Homo sapiens

FLJ13750
2q35
AU158570
57.1
Above
35.0

cDNA FLJ13750

43
209685_s_at
Protein kinase C,
PRKCB1
16p11.2
M13975.1
53.6
Above
1.9

beta 1

44
204404_at
EST like
SLC12A2
5q23.3
NM_001046.1
53.4
Above
2.0

Na+/K+/Cl−

transporter with

AA permease

domain, memb 2

45
239673_at
ESTs

4q31.23
AW080999
53.4
Above
9.0

46
240950_s_at

Homo sapiens

FLJ32658
19q13.33
AA400740
53.4
Above
9.9

cDNA FLJ32658

47
204297_at
Phosphoinositide-
PIK3C3
18q12.3
NM_002647.1
52.5
Above
4.5

3-kinase, class 3

48
206591_at
Recombination
RAG1
11p13
NM_000448.1
52.1
Above
5.4

activating gene 1

49
209962_at
Erythropoietin
EPOR
19p13.2
M34986.1
52.1
Above
17.0

receptor

50
209963_s_at
Erythropoietin
EPOR
19p13.2
M34986.1
52.1
Above
7.6

receptor

51
210186_s_at
FK506 binding
FKBP1A
20p13
BC005147.1
52.1
Above
1.8

protein 1A (12 kD)

52
219866_at
Chloride
CLIC5
6p21.1
NM_016929.1
52.1
Above
60.3

intracellular

channel 5

53
203474_at
IQ motif
IQGAP2
5q13.2
NM_006633.1
51.6
Below
2.8

containing

GTPase activating

protein 2

54
210058_at
Mitogen-activated
MAPK13
6p21.1
BC000433.1
51.6
Above
2.3

protein kinase 13

55
211891_s_at
Rho guanine
ARHGEF4
2q22
AB042199.1
51.6
Above
452.6

nucleotide

exchange factor

(GEF) 4

56
214214_s_at
Complement
C1QBP
17p13.3
AU151801
51.6
Below
2.0

component 1, q

subcomponent

binding protein

57
218152_at
High-mobility
HMG20A
15q24
NM_018200.1
51.6
Above
1.7

group 20A

58
234983_at
ESTs
FLJ21415
12q24.22
BE893995
51.6
Above
2.4

59
240446_at
KIAA1323
KIAA1323
18q11.2
AI798164
51.6
Above
102.2

60
244107_at
ESTs

18q12.1
AW189097
51.6
Above
518.9

61
205794_s_at
Neuro-oncological
NOVA1
14q12
NM_002515.1
51.4
Above
40.4

ventral antigen 1

62
217628_at
chloride
CLIC5
6p21.1
BF032808
51.4
Above
87.4

intracellular

channel 5

63
218804_at
Hypothetical
FLJ10261
11q13.3
NM_018043.1
51.4
Above
41.6

protein FLJ10261

64
230698_at
EST

7q11.22
AW072102
51.4
Above
8.7

65
225129_at
cDNA FLJ37548
FLJ37548
16q13
AW170571
49.4
Above
3.0

fis

66
201266_at
Thioredoxin
TXNRD1
12q23-q24.1
NM_003330.1
48.2
Above
1.7

reductase 1

67
203611_at
Telomeric repeat
TERF2
16q22.1
NM_005652.1
48.2
Above
5.3

binding factor 2

68
213017_at
Lung alpha/beta
LABH3
18q11.1
AL534702
48.2
Above
4.0

hydrolase 3

69
236430_at
hypothetical
MGC23911
16q22.1
AA708152
48.2
Above
16.8

protein

MGC23911

70
209035_at
Midkine (neurite
MDK
11p11.2
M69148.1
47.7
Above
4.6

growth-promoting

factor 2).

71
209193_at
Pim-1 oncogene
PIM1
6p21.2
M24779.1
47.7
Above
2.0

72
218625_at
Neuritin 1
NRN1
6p24.1
NM_016588.1
47.7
Above
5.1

73
226038_at
Hypothetical
FLJ23749
8p23.1
BF680438
47.7
Above
5.2

protein FLJ23749

74
232227_at
EST

9q34.3
AV736391
47.7
Above
14.7

75
204160_s_at
Ectonucleotide
ENPP4
6p12.3
AW194947
46.5
Above
7.2

pyrophosphatase/phosphodiesterase

4 (putative

function)

76
206233_at
UDP-
B4GALT6
18q11
AF097159.1
46.5
Above
2.6

Gal: betaGlcNAc

beta 1,4-

galactosyltransferase,

polypeptide 6

77
218813_s_at
SH3-domain

9q34.11
NM_020145.1
46.5
Above
6.2

GRB2-like
SH3GLB2

endophilin B2

78
227111_at

Homo sapiens

FLJ31099
9q33
BG179317
46.5
Above
2.7

cDNA FLJ31099

fis, clone

IMR321000230

79
202382_s_at
Glucosamine-6-
GNPI
5q21
NM_005471.1
46.2
Above
5.6

phosphate

isomerase

80
202838_at
Fucosidase, alpha-
FUCA1
1p34
NM_000147.1
46.2
Above
4.8

L-1, tissue

81
225731_at
Hypothetical
KIAA1223
4q26
AB033049.1
46.2
Above
2.8

protein

KIAA1223

82
225835_at
FLJ21409
SLC12A2
5q23.2
AK025062.1
46.2
Above
3.6

83
229790_at
Telomeric repeat
TERF2
16q22.1
AW006832
46.2
Above
7.4

binding factor 2

84
230069_at
Hypothetical
FLJ12876
5q35.3
BF593817
46.2
Above
9.4

protein FLJ12876

85
235872_at
ESTs

BE408975
46.2
Above
17.7

86
239300_at
EST

18q12.3
AI632214
46.2
Above
3.0

87
241940_at
EST

18q11.2
BF477544
46.2
Above
2.9

88
203370_s_at
Enigma (LIM
ENIGMA
5q35.3
NM_005451.2
45.9
Above
8.1

domain protein)

89
215149_at
LOC149153:
LOC149153
1p36.32
AF052109.1
45.9
Above
9.2

90
217901_at
Desmoglein 2
DSG2
18q12.1
BF031829
45.9
Above
6.7

desmosomal

cadherin

91
235333_at
UDP-
BA4GALT6
18q12.1
BG503479
45.9
Above
2.0

Gal: betaGlcNAc

beta 1,4-

galactosyltransferase,

polypeptide 6

92
242881_x_at
EST

BG285837
45.9
Above
11.8

93
200783_s_at
Stathmin
STMN1
1p35.1
NM_005563.2
45.8
Above
1.5

1/oncoprotein 18

leukemia-

associated

phosphoprotein

94
201334_s_at
Rho guanine
ARHGEF12
11q23.3
NM_015313.1
45.8
Above
6.1

nucleotide

exchange factor

(GEF) 12

95
203038_at
Protein tyrosine
PTPRK
6q22.33
NM_002844.1
45.8
Above
9.1

phosphatase,

receptor type, K

96
209735_at
ATP-binding
ABCG2
4q22
AF098951.2
45.8
Above
4.5

cassette, sub-

family G

(WHITE),

member 2

97
212063_at
Unactive
P23
12q12
BE903880
45.8
Below
7.4

progesterone

receptor, 23 kD

98
212399_s_at
Hypothetical
KIAA0121
3p25.2
D50911.2
45.8
Above
1.8

protein

KIAA0121

99
212438_at
Putative nucleic
RY1
2p13.1
BG252325
45.2
Above
1.7

acid binding

protein RY-1

100
214761_at
OLF-1/early B-
OAZ
16q12
AW149417
45.2
Above
2.1

cell factor

associated zinc

finger protein

[0219] Biologic Insights from the New Class Defining Genes

[0220] Interestingly, the overall quantitative pattern of expression of discriminating genes varied significantly between leukemia subtypes (Table 69). Within the B-cell lineage leukemia subtypes, E2A-PBX1, TEL-AML1, BCR-ABL, and Hyperdiploid>50 chromosomes were characterized primarily by genes that were overexpressed, where as almost 40% of the discriminating genes that characterized MLL fusion gene expressing leukemias were underexpressed. More remarkably, the discriminating genes for the leukemia subtypes defined by chimeric transcription factors were markedly overexpressed, with an average fold increase of 112 and 48 for E2A-PBX1 and TEL-AML1, respectively. By contrast, the discriminating genes for BCR-ABL and MLL fusion gene expressing leukemias showed an average fold increases of only 6.8. and 8.6, respectively, whereas the discriminating genes for hyperdiploid>50 chromosomes had an average fold-increase of only 2.6 fold. These data suggest that the quantitative global changes in a cell's expression profile vary markedly depending on the genetic lesion(s) that underlie the initiation of the leukemic process.

71TABLE 69Summary of fold change by diagnosticsubgroup (by gene)Mean foldSubgroupchangeRangeBCR-ABL6.81.1-90.5E2A-PBX1112.01.6-5435Hyperdiploid >502.61.3-27.2MLL rearrangement8.61.0-75T-ALL3872.1-7685TEL-AML148.31.5-2446

[0221] Tables 70-74 show genes whose expression is limited to a single B-cell lineage class, and therefore function not only as class discriminators in the decision tree format, but are also class discriminators in a parallel format in which a class is distinguished against all others. Thus, these genes have the potential of serving as unique class specific diagnostic or therapeutic targets. In addition, these genes may provide unique insights into the underlying biology of the different leukemia subtypes. For example, BCR-ABL expressing ALLs are characterized by the over expression of Dynactin 4, which encodes a RING finger containing protein that is part of the 20S dynactin multisubunit complex involved in movement, intracellular transport and division through its interaction with the cytoplasmic microtubule-based motor dynein; PSTPIP2, which encodes a proline/serine/threonine phosphatase-interacting protein that is also involved in controlling the organization of the cytoskeleton, and is tyrosine phosphorylated following activation of receptor tyrosine kinases (Karki et al. (2000) J. Biol. Chem.275:4834-4839); and several novel ESTs.

72TABLE 70Genes highly Correlated with BCR-ABLGenBank ReferenceGene DescriptionAK002064DKFZP564A2416 histone H5 signatureBE218028Dynactin 4NM_024600FLJ20898NM_024430Pro-Ser-Thr phsphatase interac. protein 2AV648669FLJ39877

[0222] E2A-PBX1 expressing leukemias are characterized by the expression of PBX1, the receptor tyrosine kinase gene C-MERTK, and the FAT tumor suppressor, which encodes a member of the cadherin repeat domain containing family of transmembrane proteins (see Table 64). Among the discriminating genes were two genes, EB-1 and Wnt16 that had previously been shown to be over expressed in this leukemia subtype (Wu et al. (1998) J. Biol. Chem. 273:30487-30496; and Fu et al. (1999) Oncogene 10 18:4920-4929). In addition, the retinal degeneration B beta gene (McWhirter et al. (1999) Proc. Natl. Acad. Sci. U S A. 96:11464-11469), and a number of novel ESTs were identified as being uniquely over expressed in this leukemia subtype, whereas the SOCS2 negative regulators of cytokine signaling was found to be under expressed (Fullwood and Hsuan (1999) J. Biol. Chem. 274:31553-31558).26

73TABLE 71Genes highly Correlated with E2A-PBX1GenBank ReferenceGene DescriptionNM_012417retinal degeneration B betaAI971602MGC10485AW005572EB-1AL357503Q9H4T4 likeNM_016087Wnt16

[0223] Hyperdiploid leukemias with >50 chromosomes were characterized by the over expression of MST4, which encodes a novel serine/threonine kinase (Horvat and Medrano (2001) Genomics 72:209-212); SH3BP2, which encodes a SH3-domain containing binding protein (Lin et al. (2001) Oncogene 20:6559-6569) histone deacetylase 6, which encodes a protein involved in transcriptional repression; the retinoblastoma binding protein 7 gene, which encodes a protein found in many functional histone deacetylase complexes (Bell et al. (1997) Genomics 44:163-170), and TNRC11 a trinucleotide repeat containing gene that is also known as HOPA or TRAP230 and is part of the thyroid hormone receptor-associated protein (TRAP) complex (Huang et al (1991) Nature 350:160-162; and Ito et al. (1999) Mol Cell. 3:361-370.

74TABLE 72Genes highly Correlated with Hyperdiploid >50GenBank ReferenceGene DescriptionNM_002893Retinoblastoma binding protein 7AB000462SH3-domain binding protein 2NM_006044Histone deacetylase 6BC004354trinucleotide repeat containing 11NM_016542Mst3 and SOK1-related kinase

[0224] Cases with MLL gene rearrangements were characterized by the over expression of HOXA9 and Meis1 (see Table 66). Included in the up-regulated genes was a novel transcript from chromosome 20 that was over expressed almost 25 fold. This transcript is predicted to encode a protein of 280 amino acids that shows a low level of homology to a lysosome-associated membrane glycoprotein (LAMP). Also specifically over expressed in this leukemia subtype is a gene encoding an insulin growth factor (IGF) II RNA binding protein, that has been shown to repress the translation of the IGF-II growth factor (Armstrong et al (2002). Nat. Genet. 30:41-47). Among the down regulated genes was neuron navigator 1 (Nielsen et al. (1999) Mol Cell Biol. 19:1262-1270), which encodes an 1874 amino acid protein and is involved in direction guidance of migratory cells, and a member of the TCF/LEF family of transcription factors, TCF-4. TCF-4 functions downstream of β-catenin in the Wnt-mediated signaling cascade and has been shown to be essential for the maintenance of intestinal crypt stem cells (Maes et al. (2002) Genomics 80:21-30).

75TABLE 73Genes highly Correlated with MLLGenBank ReferenceGene DescriptionNM_012261C20orf103AI202327FLJ37247NM_006548IGF-II mRNA-binding protein 2NM_018401gene for serine/threonin protein kinaseNM_018728myosin 5CAB032977neuron navigator 1

[0225] Genes that were discriminators of TEL-AML1 leukemias included a gene localized to chromosome 18q11.1 that encodes a 795 amino acid protein that has 8 ankyrin repeat domains and a C-terminal RING finger domain. This combination of domains is identified in only a limited number of mammalian proteins, most notably BARD1, a regulator of the BRCA1 tumor suppressor (Korinek et al. (1998) Nat Genet.19:379-383). Other genes overexpressed in the subtype include desmocollin (Irminger-Finger and Leung (2002) Int. J. Biochem. Cell Biol. 34:582-587), FLJ12722 a novel protein of unknown function, and a member of the IAP family of apoptosis inhibitors, BIRC7, which is overexpressed 25 fold (Whittock et al. (2000) Biochem Biophys Res Commun. 276:454-460).

76TABLE 74Genes highly Correlated with TEL-AML1GenBank ReferenceGene DescriptionW80418KIAA1323AK022784FLJ12722NM_0022161BIRC7A1452798FLJ39434A1797281Desmocollin 3

[0226] Expression Profiling Accurately Identifies the Prognostic Subtypes of ALL

[0227] To assess the accuracy of identifying prognostically important ALL genetic subtypes by expression profiling, the class discriminating genes identified using a chi-squared metric were used in an ANN-based supervised learning algorithm. Class assignment utilized the decision tree differential diagnostic format described elsewhere herein, and required that the node value for assignment exceeded a statistically defined confidence level. Using this approach resulted in exceptionally accurate class prediction in a randomly selected training set that consisted of three-fourths of the total cases (100 cases). When this classification model was then applied to a blinded test set consisting of the remaining 32 samples, an overall accuracy of 97% was achieved for class assignment. To control for over-fitting of the data, 10 additional rounds of this analysis were performed in which for each round new training and test sets were developed, genes reselected using the new training set, and then their performance assessed on the new test set. This resulted in an average accuracy of class assignment in the blinded test sets of 97.2%, with a range from 93.8% to 100%. Although the number of genes required for optimal class assignment varied between classes, the best overall diagnostic accuracy was achieved using the top 50 genes per class. A similar level of accuracy was achieved using a variety of other supervised learning algorithms, including κ-NN and SVM.

[0228] Interestingly, of the rare misclassification errors, two were cases of BCR-ABL expressing ALL that by gene expression analysis was classified as hyperdiploid>50 chromosomes. The karyotype of these cases showed the presence of both the Philadelphia chromosome and a hyperdiploid karyotype consisting of >50 chromosomes—including trisomy of chromosomes X and 21 (data not shown). The expression profile thus correctly identified the presence of the hyperdiploid>50 chromosomes class; however, since each case is assigned to only a single class, the algorithm failed to correctly identify the presence of BCR-ABL. Nevertheless, the data presented demonstrates the exceptional accuracy of this single platform for the diagnosis of the prognostically important subtypes of ALL.

[0229] Overview of Experimental Procedure

[0230] A. Gene Expression Profiling

[0231] The preparation of mononuclear cell suspensions from diagnostic bone marrow aspirates, extraction of total RNA, and preparation of hybridization solutions was performed as described for Example 1. Individual hybridization solutions from our previous study had been stored at −80° C. since initial hybridization (approximately 1 year). These solutions were thawed and hybridized to Affymetrix® HG-U133A and HG-U133B oligonucleotide microarrays (Affymetrix Inc., Santa Clara, Calif.) according to Affymetrix protocols. In two cases where the original hybridization solutions were no longer available, replicate viably frozen mononuclear cell preparations from the diagnostic bone marrow aspirate were obtained, RNA isolated, cDNA and cRNA synthesized, labeled, fragmented and hybridized as described for Example 1.

[0232] After sample hybridization, arrays were then stained with phycoerythrin-conjugated streptavidin (Molecular Probes, Eugene, Oreg.). Antibody amplification was performed with biotinylated anti-streptavidin (Vector Laboratories, Burlingame, Calif.), followed by staining with phycoerythrin-conjugated streptavidin (Molecular Probes). Arrays were scanned using a laser confocal scanner (Agilent, Palo Alto, Calif.) and then analyzed with Affymetrix® Microarray suite 5.0 (MAS 5.0). Detection values (present, marginal or absent) were determined by default parameters, and signal values were scaled by global methods to a target value of 500. Microarray scan images were visually inspected for apparent defects, and Affymetrix internal controls were utilized to monitor the success of hybridization, washing, and staining procedures. Minimal quality control parameters for inclusion in the study included greater than 10% present calls and a GAPDH 3′/5′ ratio of ≦3. The arrays included in this study had an average % present call of 35.9% for the A chip and 21.0% for the B chip (combined average of 28.5%).

[0233] B. Statistical Analysis

[0234] The dataset was separated into a train set (100) and test set (32). The identification of subtype discriminating genes was performed using the training set. Moreover, both gene discovery and subsequent class predictions were performed using a differential diagnosis decision tree format. In this format, classification was performed in a sequential order starting with T-ALL and proceeding in order E2A-PBX1, TEL-AML1, BCR-ABL, MLL rearrangement, and Hyperdiploid>50 chromosomes. Unassigned cases were classified as other. Samples classified into the class under diagnosis were removed prior to proceeding to the next level in the decision tree. In addition, prior to analysis a variation filter was applied to remove any probe set that showed minimal variation across the dataset, and thus contributed minimally, if at all, to the discrimination of leukemia subtypes. Specifically, probe sets were eliminated from further analysis if the number of cases with a present call was less than ½ the number of samples comprising the leukemia subgroup under analysis, had a signal value<100 in all samples in the dataset, or had a maximal signal value in the dataset—minimal signal value in the dataset that was less than 100. In addition, all signal values with absent or marginal calls were reset to 1, while probe sets with a present “P” call and a signal<100 had the signal reset to 100. The values for signals from the Affymetrix® control sets were removed prior to analysis.

[0235] Unsupervised hierarchical clustering and principal component analysis (PCA) were performed using GeneMaths software (version 1.5, Applied Maths, Belgium). Data reduction to define the genes most useful in class distinction was primarily performed using a chi-square metric. In this procedure, an entropy-based discretization method was first applied to identify genes whose expression across the dataset showed differentiation between class and non-class.17 The assigned descretized value for the gene was then used in a chi-square calculation to determine if the association with a class was more than would be expected by random chance. The stronger the association with the class, the larger the chi-square value calculated. For the genes that couldn't be discretized, their chi-squared values were set to zero. To evaluate the statistical significance of the discriminating genes, we used a permutation test in which for each class, case labels were randomly reassigned to generate new groups of identical size. The label permutated data was discretized again and the chi-square values were recalculated. The permutation test was repeated for a total of 1000 times. The true chi-square values for each probe set were then compared to the values generated from the 1000 permutations to determine how many times a chi-square value for a probe set in a randomly labeled group was greater than that obtained for the true class distinction. A p value was calculated as the number of times the chi-square value exceeded the true value in the 1000 permutations.

[0236] The discriminating genes selected were then used in supervised learning algorithms to build classifiers that could identify the specific genetic subgroup. Algorithms used included k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), and an artificial neural network (ANN). See, Example 1, Witten and Frank (1999) Data mining: Practical machine learning tools and techniques with Java implementation. Morgan Kaufinan; Platt (1998) Fast training of support vector machines using sequential minimal optimization in Advances in kernel methods—support vector learning Schlkopf B, Burges C, and Smola A, eds. MIT Press; and Cover and Hart (1967) IEEE Transactions on Information Theory 13:21-27. Performance of each model was initially assessed by three-fold cross validation on a randomly selected stratified training set. True error rates of the best performing classifiers were then determined using the remaining one-fourth of the samples as a blinded test group. Class assignment required that a sample's calculated node value exceed a statistically determined confidence level in order for it to be assigned to a class. Details of the supervised learning algorithms and their use are described below.

[0237] Detailed Experimental Procedures

[0238] A. Patient Dataset

[0239] 132 cases of pediatric ALL were selected from the original 327 diagnostic bone marrow aspirates described in Example 1 to reanalyze on the higher density U133A and B microarrays. The selection of cases was based on having sufficient numbers of each subtype to build accurate class predictions, rather than reflecting the actual frequency of these groups in the pediatric population.

[0240] B. Hybridization of Microarrays

[0241] The hybridization solutions according to Example 1 were thawed at 45° C., then microcentrifuged for 5 minutes to remove any insoluble material from the mixture. The hybridization solutions were added to U133A chips and allowed to hybridize for 16 hours at 45° C. At the end of the incubation period, the hybridization solution was removed from each U133A chip and refrozen. Subsequently, the hybridizations were thawed and hybridized to the U133B chip.

[0242] A non-stringent wash buffer (6×SSPE, 0.01% Tween 20) was added to each chip cassette after the hybridization solution was removed and the cassette allowed to equilibrate to room temperature. The microarray cassettes were then placed on the fluidics station and the antibody amplification protocol performed. The arrays were washed at 25° C. with the non-stringent buffer followed by a more stringent wash at 50° C. with 100 mM MES, 0.1M NaCl2, 0.01% Tween 20. The arrays were then stained with Streptavidin Phycoerythrin (SAPE, Molecular Probes, Eugene, Oreg.) for 10 minutes at 25° C. Following another non-stringent wash, the arrays were hybridized for 10 minutes at 25° C. with an antibody solution (100 mM MES, 1 M [Na+], 0.05% Tween 20, 2 mg/ml BSA, 0.1 mg/ml goat IgG, and 3 □g/ml biotinylated antibody). This solution was removed and the cassettes restained with the SAPE solution.

[0243] Arrays were scanned on a laser confocal scanner (Agilent, Palo Alto, Calif.) and then analyzed with Affymetrix® Microarray Suite 5.0 (MAS 5.0). Detection values (present, marginal or absent) were determined by default parameters, and signal values were scaled by global methods to a target value of 500. After completing the scans, the arrays were visually inspected for defects and Affymetrix internal controls were utilized to monitor the success of hybridization, washing, and staining procedures.

[0244] C. Statistical Methods

[0245] The chi-square metric and the kNN and ANN supervised learning algorithms were performed as described for Example 1. The SVM supervised learning algorithm that was used in this study is available as part of the software package Rv 1.6.0. See, Ribeiro, and Brown. The ISBA Bulletin, 8(1):12-16, and www.r-project.org.

[0246] To determine the performance of each model using ANN, a confidence threshold was built for each diagnostic subtype utilizing a modification of the method described by Khan et al. (2001) Nat. Med. 7:673-679. Models were built based on a decision tree format where each level of the decision tree contains only two possible distinctions—class and non-class (for example, T verses non-T). At each level, using only samples in the training set, 3 ANN models were built by 3-fold cross validation. The training set samples were then shuffled and 3 additional ANN models were built. This model building process was repeated for a total of 100 times at each step of the decision tree. Then an empirical probability distribution for the ANN output node value was built only for subtype under study, for example, T-ALL at the first step of the decision tree. Only nodal values greater than 0.5 for each subtype were included. For each individual sample in the training set, the 100 validation subtype node values were averaged and compared to threshold. Individual samples were assigned to the subtype under study only when its average subtype nodal value was greater than the 95% confidence threshold. For samples in the test set, subtype nodal values are averaged from all models generated in the 3-fold cross validation. A sample is assigned to the class under study when the average subtype nodal value is greater than the 95% confidence level defined on the training set. A sample not assigned to the subtype will progress to the next level of the decision tree, where the entire process is repeate.

[0247] All publications and patent applications mentioned in the specification are indicative of the level of those skilled in the art to which this invention pertains. All publications and patent applications are herein incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference.

[0248] Although the foregoing invention has been described in some detail by way of illustration and example for purposes of clarity of understanding, it will be obvious that certain changes and modifications may be practiced within the scope of the appended claims.

Classification and prognosis prediction of acute lymphoblastic leukemia by gene expression profiling

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