Method for diagnosis of colorectal tumors

Abstract

The invention provides objective methods for detecting and diagnosing colorectal cancers and pre-malignant lesions. For example, the methods disclosed herein can reliably detect very early-stage colorectal cancers. In one embodiment, the diagnostic method involves the scoring of gene expression profiles that discriminate between adenomas and carcinomas. The profile score calculated acts as diagnostic indicator that can objectively indicate whether a sample tissue is non-cancerous, pre-cancerous, or cancerous. The present invention further provides methods of diagnosing colorectal tumors in a subject, methods of screening for therapeutic agents useful in the treatment of colorectal tumors, methods of treating colorectal tumors and method of vaccinating a subject against colorectal tumors.

Description

TECHNICAL FIELD

The present invention relates to the field of cancer research. More particularly, the present invention relates to methods for detecting colorectal cancer and objectively distinguishing between colorectal adenomas and carcinomas. The invention further relates to methods of diagnosing colorectal tumors in a subject, methods of screening for therapeutic agents useful in the treatment of colorectal tumors, methods of treating colorectal tumors and method of vaccinating a subject against colorectal tumors.

BACKGROUND OF THE INVENTION

The invention relates to detection and diagnosis of tumors, particularly colorectal tumors.

Colorectal carcinoma is a leading cause of cancer deaths in developed countries. Specifically, more than 130,000 new cases of colorectal cancer in the United States are reported each year. Colorectal cancer represents about 15% of all cancers. Of these, approximately 5% are directly related to inherited genetic defects. Many patients have a diagnosis of pre-cancerous colon or rectal polyps before the onset of cancer. While many small colorectal polyps are benign, some types may progress to cancer.

The most widely used screening test for colorectal cancer is colonoscopy. This method is used to visualize a suspicious growth and/or take a tissue biopsy. Typically, the tissue biopsy is histologically examined and a diagnosis delivered based on the microscopic appearance of the biopsied cells. However, this method is limited in that it yields subjective results and can not be used for very early detection of pre-cancerous states. The development of a sensitive, specific and convenient diagnostic system for detecting very early-stage colorectal cancers or pre-malignant lesions is highly desirable as it could ultimately eliminate this disease.

The present invention represents a marked improvement in the field of colon cancer detection and diagnosis. Prior to the invention, knowledge of genes involved in colorectal tumors was fragmentary. The information described herein provides genome-wide information about how gene expression profiles are altered during multi-step carcinogenesis. Specifically, the present invention describes genes that discrimiate between colorectal adenomas and carcinomas, referred to herein as “marker genes”. On the basis of expression of selected “marker” genes, a scoring system was established that can assist clinicians in distinguishing adenomas from carcinomas. The information disclosed herein not only contributes to a more profound understanding of colorectal tumorigenesis, particularly of adenoma-carcinoma progression, but also provide indicators for developing novel strategies to diagnose, treat, and ultimately prevent colorectal carcinomas.

SUMMARY OF THE INVENTION

Accordingly, the present invention provides diagnostic methods that correlate the expression of marker genes to the presence or absence of colorectal cancer. More particularly, the present invention provides sensitive, specific and convenient diagnostic methods for distinguishing between malignant and pre-malignant lesions and diagnosing the presence of colorectal cancer in a subject. For example, the diagnostic methods of the present invention can reliably detect very early-stage colorectal cancers.

The marker genes of the present invention are characterized as being either up regulated or down-regulated in colorectal tumors. Up-regulated marker genes include, RNA/protein processing genes, oncogenes (e.g., HMGIY, DEK and NPM1), cell adhesion/cytoskeleton molecules (e.g., TUBB, K-ALPHA, TGFBI, CDH3 and PAP), growth control molecules (e.g., IMPDH2 and ODC1), signal transduction molecules (e.g., BRF1, PLAB, LAP18, CD81 and MICMARCKS), cell-cycle control molecules (e.g., RAN and UBE2I), transcription factors (e.g., HMG1 and HMG2), as well as tumor-associated molecules such as PPP2R1B, LDBB and SLC29A1. Marker genes commonly up-regulated in colorectal tumors are set forth in Table 1. Marker genes were up-regulated in colorectal adenoma as compared to normal tissues, and no significant difference in marker gene expression was observed between carcinoma and normal tissue (Table 3). Marker genes were up-regulated in colorectal carcinoma as compared to normal tissues, and no significant difference in marker gene expression was observed between adenoma and normal tissue (Table 4).

Colorectal tumor-associated down-regulated marker genes include associated with programmed cell death (e.g. CASP8, CASP9, CFLAR, DFFA, PAWR TNF, TNFRSF10C and TNFRSF12. Further down-regulated marker genes include, immune modulators (e.g., chemokine receptors such as IL1RL2, IL17R and IL3RA), growth suppression molecules (e.g., Suppressin, DCN, MADH2 and SS, tumor suppression molecules (e.g., TP53), cell adhesion/cytoskeleton molecules (e.g, ADAM8, AVIL, CDH17, CEACAM1, CTNNA2, ICAPA, KRT9, and ARHGAP5), metabolic factors (e.g., BPH-L, CA2, CASA, HSD11B2 and ECHS1), ion transporters (e.g., SLC15A2, SLC22A1, SLC4A3 and SLC5A1), a natural antimicrobial molecule (e.g. DEFA6). Marker genes commonly down-regulated in colorectal tumors are set forth in Table 2.

In the present invention, the term “colorectal tumor” refers to both colorectal adenoma and colorectal carcinoma Marker genes listed in Table 3 and Table 4 are useful as stage specific markers of colorectal adenoma and colorectal carcinoma, respectively. On the other hand, marker genes listed in Table 1 and Table 2 are general marker genes for colorectal tumors. The term “general marker” employed herein means that the existence of that marker proves the existence of some tumor including adenoma and carcinoma.

In the diagnostic methods of the present invention, it is preferable that multiple marker genes are selected for comparison of expression levels thereof. The more marker genes selected for comparison, the more reliable the diagnosis. The expression levels of a number of genes can be compared conveniently by using an expression profile. The term “expression profile” refers to a collection of expression levels of a number of genes, preferably marker genes that are differentially expressed in colorectal carcinoma as compared to colorectal adenoma.

Accordingly, in one embodiment, the present invention provides a method for diagnosing colorectal tumors in a subject comprising the steps of:

• • (a) detecting an expression level of one or more marker genes in a specimen collected from a subject to be diagnosed, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 1 and the genes listed in Table 2; and
  • (b) comparing the expression level of the one or more marker genes to that of a control, wherein high expression level of a marker gene from Table 1 or a low expression level of a marker gene from Table 2, as compared to control, is indicative of colorectal cancer.

The expression levels of marker genes in a particular specimen can be estimated by quantifying mRNA corresponding to, or protein encoded by, the marker genes. Quantification methods for mRNA are known to those skilled in the art. For example, the levels of mRNAs corresponding to the marker genes can be estimated by Northern blotting or RT-PCR. Since all the nucleotide sequences of the marker genes are known, anyone skilled in the art can design nucleotide sequences of probes or primers to quantify the marker genes.

Also the expression level of the marker genes can be analyzed based on the activity or amount of proteins encoded by the marker genes. A method for determining the amount of marker proteins is shown below. For example, immunoasssays are useful to detect/quantify the protein in a biological material. Any biological material can be used for the detection/quantification of the protein or it's activity. For example, a blood sample is analyzed to determine the protein encoded by serum marker. Alternatively, a suitable method can be selected to determine the activity of proteins encoded by the marker genes according to the activity of each protein analyzed.

Expression levels of the marker genes in a specimen (test sample) are estimated and compared with those in a normal sample. When such a comparison shows that the expression level of a marker gene set forth in Table 1 is higher than that in the normal sample, the subject is judged to be affected with a colorectal tumor. The expression level of marker genes in specimens from a normal individual and a subject may be determined at the same time. Alternatively, normal ranges of the expression levels can be determined by a statistical method based on the results obtained by analyzing the expression level of the marker genes in specimens previously collected from a control group. A result obtained by examining the sample of a subject is compared with the normal range and when the result does not fall within the normal range, the subject is judged to be affected with a colorectal tumor. Similarly, colorectal adenoma and / or carcinoma may be diagnosed using marker genes set forth in Table 3 or Table 4, respectively.

In the present invention, a diagnostic agent for diagnosing colorectal tumor, adenoma, and/or carcinoma is also provided. The diagnostic agent of the present invention comprises a compound that binds to the DNA or protein of a marker gene. Preferably, an oligonucleotide that hybridizes to the polynucleotide of a marker gene, or an antibody that specifically binds to the protein encoded by a marker gene may be used as the compound.

The present invention further provides a method for diagnosing colorectal cancer in a subject comprising the step of comparing the marker gene expression profile of a sample specimen collected from a subject with the marker gene expression profile of a control (i.e. a non-cancerous) specimen. When expression profiling analysis shows that the expression profile contains characteristics of colorectal cancer, the subject is judged to be affected with the disease. Specifically, when not all but most of the marker genes exhibit colorectal cancer-associated patterns of alterations of gene expression levels, the expression profile comprising those of the marker genes has characteristics of colorectal cancer. For example, when 50% or more, preferably 60% or more, more preferably 80% or more, still more preferably 90% or more of the marker genes constituting the expression profile exhibit colorectal cancer-associated patterns of alterations in gene expression levels, one can safely conclude that the expression profile has characteristics of colorectal cancer.

In a preferred embodiment, the marker genes comprise genes up-regulated in colorectal carcinomas as compared with colorectal adenomas, such as those shown in Table 4. Alternatively, the marker genes may comprise genes unregulated in colorectal adenomas as compared with colorectal carcinomas, such as those shown in Table 3. Multiple marker genes from various categories may also be selected. Specifically, the present invention provides a method of identifying adenoma comprising the steps of:

• • (a) detecting an expression level of one or more marker genes in a specimen collected from a subject to be diagnosed, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 3; and
  • (b) comparing the expression level of the one or more marker genes to that of a control, wherein high expression level of a marker gene from Table 3 as compared to control is indicative of adenoma.

Furthermore, the present invention provides a method of identifying carcinoma comprising the steps of:

• • (a) detecting an expression level of one or more marker genes in a specimen collected from a subject to be diagnosed, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 4; and
  • (b) comparing the expression level of the one or more marker genes to that of a control, wherein high expression level of a marker gene from Table 4 as compared to control is indicative of carcinoma

Clinically important information can be obtained by distinguishing between adenoma and carcinoma Adenoma is a pre-cancerous tumor, whereas carcinoma is a cancerous tumor requiring treatment. Any of the marker genes listed in Tables 3 and 4 are used in the present method for identifying carcinoma Alternatively, expression levels of one or more marker gene selected from Table 3 and one or more marker gene selected from Table 4 may be detected for the identification of carcinoma according to the present invention. Compared to an identification using one or more marker gene from either Table 3 or 4, a more accurate identification can be achieved by confirming elevated expression of one or more marker gene selected from Table 3 and no significant changes in the expression of one or more marker gene from Table 4, or elevated expression of one or more marker gene selected from Table 4 and no significant changes in the expression of one or more marker gene from Table 3.

In an alternate embodiment, the diagnostic method of the present invention involves the step of scoring expression profiles for genes that discriminate between adenomas and carcinomas. The steps of the method include receiving expression profiles for genes selected as differentially expressed in adenomas versus carcinomas (i.e., “marker genes”) and determining a function of the log ratios of the expression profiles over the selected genes. The step of “determining a function of the log ratios of the expression profiles over the selected genes” may comprise summing the weighted log ratios of the expression profiles over the selected genes. The weight for each gene is assigned a first value when the average log ratio is higher for carcinomas than for adenomas and a second value when the average log ratio is lower for carcinomas than for adenomas. Preferably, the second value is substantially the opposite of the first value, e.g., the first value is 1 and the second value is −1.

The method of the present invention further provides a diagnostic determination of the cancer status of a tissue sample. For example, in one embodiment, the diagnostic method of the present invention preferably involves the steps of measuring the level of expression of a gene in a test sample, e.g., a tumor biopsy or a biopsy of a normal tissue, and determining a gene expression ratio value for each of a plurality of differentially-expressed index (or marker) genes. The gene expression ratio corresponds to the amount of expression in the test sample as compared to the amount of expression in normal tissue. A sign [e.g., a plus sign (+) or a minus sign (−)] is assigned for each value. The sign is +1 if ave_carcinoma is greater than ave_adenoma and said sign is −1 is ave_carcinoma is less than ave_adeonoma.

Each value is combined to determine a diagnostic indicator, which objectively indicates whether a tissue is pre-cancerous, or cancerous. For example, the indicator discriminates between adenomas and carcinomas.

In another embodiment, the method includes the step of determining a ratio of expression for each of a plurality of selected marker genes in the tissue and combining indicia of the ratios to determine a cancer value. The combining of a particular ratio for a particular gene influences the cancer value toward a carcinogenic indication if the particular gene is associated with (indicative of) carcinoma (i.e., a carcinoma marker gene) and influences the cancer value toward an adenoma indication if the particular gene is associated with (indicative of) at least one of adenoma and normal (i.e., an adenoma marker gene). Preferably, the plurality is greater than 10 genes, more preferably greater than 25 genes, more preferably greater than 40 genes, and most preferably greater than 50 genes.

A significant advantage of the diagnostic methods of the present invention is that the diagnostic determination is made objectively rather than subjectively. Earlier methods were limited because they relied on the subjective examination of histological samples. Another advantage of the diagnostic methods of the present invention is sensitivity. The methods described herein can discriminate among normal, pre-cancerous, and cancerous tissue very early in the carcinogenic process, whereas subjective histological examination cannot be used for very early detection of pre-cancerous states.

The present invention further provides methods for treating colorectal tumors, such as colorectal adenomas and colorectal carcinomas. The present invention revealed that expression levels of certain discriminating marker genes are significantly increased (i.e., up-regulation) or decreased (i.e., down-regulation) in colorectal tumors as compared to normal epithelia (see genes listed Tables 1 and 2) and/or in colorectal carcinomas as compared to colorectal adenomas (see genes listed in Table 3 and 4). Accordingly, any of these marker genes can be used as a target in treating the colorectal tumors. Specifically, when the expression level of a marker gene is elevated in a colorectal tumor (up-regulation; e.g., genes of Table1, 3, and 4), then the condition can be treated by reducing expression levels or suppressing its activities. Methods for controlling the expression levels of marker genes are known to those skilled in the art. For example, an antisense nucleic acids or RNAi (RNA interference) corresponding to the nucleotide sequence of the marker gene can be administered to reduce the expression level of the marker gene. Alternatively, an antibody against the protein encoded by the marker gene can be administered to inhibit the biological activity of the protein.

Conversely, when the expression level of a marker gene is decreased in colorectal tumors (down regulation; e.g., genes of Table 2), then the condition can be treated by increasing the expression level or enhancing the activity. For example, colorectal tumors can be treated by administering a protein encoded by a down-regulated marker gene. The protein may be directly administered to the patient or, alternatively, may be expressed in vivo subsequent to being introduced into the patient, for example, by administering an expression vector or host cell carrying the down-regulated marker gene of interest. Suitable mechanisms for in vivo expression of a gene of interest are known in the art. Alternatively, colorectal tumors can be treated by administering an antibody that binds to a protein encoded by an up-regulated marker gene of interest. In a further embodiment, colorectal tumors can be treated by administering an antisense nucleic acids against an up-regulated marker gene of interest.

In addition to providing methods of treating colorectal tumors, the invention also provides methods of preventing colorectal tumors, more particularly the onset and progression of colorectal cancer. Specifically, the present invention provides a method for vaccinating a subject against colorectal tumors comprising the step of administering a DNA corresponding to one or more marker genes, proteins encoded by a marker gene, or an antigenic fragment of such a protein, wherein the marker genes comprises a gene up-regulated in colorectal tumors, such as those listed in Table 1, Table 3, and Table 4. The vaccine may comprise multiple vaccine antigens corresponding to multiple up-regulated marker genes.

Marker genes listed in Tables 3 and 4 are specific marker genes of adenoma and carcinoma, respectively. However, in fact, malignant tumors are formed due to the progress of adenoma to carcinoma Thus, colorectal carcinoma can be prevented by preventing the onset of adenoma.

In a further embodiment, the present invention provides methods for screening candidate agents which are potential targets in the treatment of colorectal tumors. As discussed in detail above, by controlling the expression levels or activities of marker genes, one can control the onset and progression of colorectal cancer. Thus, candidate agents, which are potential targets in the treatment of colorectal tumors, can be identified through screenings that use the expression levels and activities of marker genes as indices. In the context of the present invention, such screening may comprise, for example, the following steps:

• • (1) contacting a candidate compound with a cell expressing one or more marker genes, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 1, Table 2, Table 3, and Table 4; and
  • (2) selecting a compound that reduces the expression level of one or more marker genes selected from Table 1, Table 3, and Table 4 as compared to a control or enhances the expression of one or more marker genes selected from Table 2 as compared to a control. Cells expressing a marker gene include, for example, cell lines established from colorectal cancer lesions; such cells can be used for the above screening of the present invention.

Alternatively, the screening method of the present invention may comprise the following steps:

• • (1) contacting a candidate compound with a protein encoded by a marker gene, wherein the marker gene is selected from the group consisting of the genes listed in Table 1, Table 2, Table 3, and Table 4;
  • (2) measuring the activity of said protein; and
  • (3) selecting a compound that reduces the activity of said protein when said marker gene is selected from Table 1, Table 3, and Table 4 or that enhances the activity of said protein when said marker gene is selected from Table 2. A protein required for the screening can be obtained as a recombinant protein using the nucleotide sequence of the marker gene. Based on the information of the marker gene, one skilled in the art can select any biological activity of the protein as an index for screening and a measurement method based on the selected biological activity.

Alternatively, the screening method of the present invention may comprise the following steps:

• • (1) contacting a candidate compound with a cell into which a vector comprising the transcriptional regulatory region of one or more marker genes and a reporter gene that is expressed under the control of the transcriptional regulatory region has been introduced, wherein the one or more marker genes are selected from the group consisting of the genes listed in Table 1, Table 2, Table 3, and Table 4;
  • (2) measuring the activity of said reporter gene; and
  • (3) selecting a compound that reduces the expression level of said reporter gene when said marker gene is selected from Table 1, Table 3, and Table 4 or that enhances the expression level of said reporter gene when said marker gene is selected from Table 2, as compared to a control. Suitable reporter genes and host cells are well known in the art. The reporter construct required for the screening can be prepared by using the transcriptional regulatory region of a marker gene. When the transcriptional regulatory region of a marker gene has been known to those skilled in the art, a reporter construct can be prepared by using the previous sequence information. When the transcriptional regulatory region of a marker gene remains unidentified, a nucleotide segment containing the transcriptional regulatory region can be isolated from a genome library based on the nucleotide sequence information of the marker gene.

Alternatively, the screening method of the present invention may comprise the following steps:

• • (1) administering a candidate compound to a test animal;
  • (2) measuring the expression level of one or more marker genes in a biological sample from the test animal, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 1, Table 2, Table 3, and Table 4;
  • (3) selecting a compound that reduces the expression level of one or more marker genes selected from Table 1, Table 3, and Table 4 as compared to a control or enhances the expression of one or more marker genes selected from Table 2 as compared to a control.

In the screening methods of the present invention wherein the expression level of the selected marker gene is decreased in colorectal tumors (i.e., down-regulated marker genes), compounds that have the activity to increase, compared to the control, the expression level of the gene should be selected as the candidate agents. Conversely, when a marker gene whose expression level is increased in colorectal tumors (i.e., unregulated marker genes) is selected in the screening method, compounds that have the activity of decreasing the expression level compared to the control should be selected as the candidate agents.

The marker genes listed in Tables 3 and 4 are specific marker genes of adenoma and carcinoma, respectively. However, in fact, malignant tumors are formed due to the advance of adenoma to carcinoma Thus, colorectal carcinoma can be prevented by preventing the onset of adenoma.

There is no limitation on the type of candidate compound used in the screening of the present invention. The candidate compounds of the present invention can be obtained using any of the numerous approaches of combinatorial library methods known in the art, including: biological library methods; spatially addressable parallel solid phase or solution phase library methods; 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 peptide libraries, while the other four approaches are applicable to peptide, non-peptide oligomer or small molecule libraries of compounds (Lam (1997) Anticancer Drug Des. 12:145). 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; Carrell et al. (1994) Angew. Chem. Int. Ed Engl. 33:2059; Carell et al. (1994) Angew. Chem. Int. Ed. Engl. 33:2061; and Gallop et al. (1994) J. Med Chem. 37:1233. Libraries of compounds may be presented in solution (e.g., Houghten (1992) Bio Techniques 13:412), or on beads (Lam (1991) Nature 354:82), chips (Fodor (1993) Nature 364:555), bacteria (U.S. Pat. No. 5,223,409), spores (U.S. Pat. Nos. 5,571,698; 5,403,484; and 5,223,409), plasmids (Cull et al. (1992) Proc. Natl. Acad. Sci. USA 89:1865) or phage (Scott and Smith (1990) Science 249:386; Devlin (1990) Science 249:404; Cwirla et al. (1990) Proc. Natl. Acad Sci. USA 87:6378; and Felici (1991) J. Mol. Biol. 222:301).(United States Published Patent Application 2002/0103360).

Other features and advantages of the invention will be apparent from the following detailed description and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-B are diagrams of a two-dimensional hierarchical clustering of 771 genes across 20 colorectal tumors. The color in each well represents relative expression of each gene (vertical axis) in each paired sample (horizontal axis); more intense colors reflect wider differences between tumor and normal epithelium. Red, increased in tumor; green, decreased; black, unchanged; gray, no expression in the tumor cells. In the sample axis, carcinomas (IT) and adenomas (P) were separated to two different trunks. In the gene axis, 771 genes were clustered in different branches according to their similarity; the shorter the branches the greater the similarity. Sub-clusters A and B were selected for further analysis.

FIG. 2 is a diagram representing fifty-one genes, the expression of which was found to be up-regulated in both adenomas and carcinomas. (Cy3/Cy5)ave indicates average value of Cy3/Cy5 in the 20 paired samples. Genes that appear repeatedly represent the same genes spotted on different set of slides. Red, increased in tumor, green, decreased; black, unchanged; gray, no expression in the tumor cells.

FIGS. 3A-B are diagrams representing the functional clusters in the gene axis. FIG. 3A shows ten of 24 genes in cluster A (genes whose expression is more abundant in carcinomas than in adenomas), and FIG. 3B shows 12 of 29 genes in cluster B (genes whose expression is more abundant in adenomas than in carcinomas). Bold italic type indicates genes that are related to bioenergetics homeostasis. Genes that appear repeatedly represent the same genes spotted on different set of slides.

FIGS. 4A-B are bar graphs showing a validation of microarray data. FIG. 4A shows Log2(Cy3/Cy5) values of 20 samples (11 carcinomas and 9 adenomas) in cDNA microarray analysis. FIG. 4B shows Log2(Tumor/Normal) values for 13 additional samples (6 carcinomas and 7 adenomas) obtained by QPCR. The expression ratio (Tumor: Normal) of TGFB1, LAP13, HECH, NME1, TCEA1 and PSMA7 determined by QPCR were in line with the microarray data for all six genes. Data are presented here as 10-90th percentiles of calculated values. Statistical significance was examined by Mann-Whitney U tests.

FIG. 5A is a diagram representing clustering analysis. The data for each gene were first median-centered, and an “Average Linkage Clustering” was subsequently applied to the data set (red, data>median value; green, data<median value). In the sample axis, 25 tumors were separated to two trunrs (adenoma group and carcinoma group). Asterisks (*) indicate additional test samples. A sample, 056P3, was diagnosed as an early adenocarcinoma by histological examination. In the gene axis, the 18 genes on the top showed higher expression in carcinoma than in adenoma, and were labeled with “1” as a sign. The 32 genes at the bottom showed higher expression in adenoma than in carcinoma, and were labeled with “−1” as a sign. Statistical significance was examined by the Mann-Whitney U test.

FIG. 5B is a diagram representing Molecular Diagnosis Scores (MDSs). The data were presented as 10-90th percentiles of the calculated values. Asterisks denote the five additional samples for validating the MDS system. Tumor 056P3 is a well-differentiated adenocarcinoma.

DETAILED DESCRIPTION

In the context of the present invention, the following definitions apply:

Tumors of the colorectal epithelium are classified as benign, malignant or pre-malignant. In the context of the present invention, the term “colorectal tumors” encompasses benign, malignant and pre-malignant tumors of the epithelium of the colon or rectal. The term “colorectal cancer” refers to a malignant state, characterized by uncontrolled, abnormal growth of cells. Cancer cells can spread locally or though the blood stream and lymphatic system to other parts of the body.

A “carcinoma” is a malignant new growth of cells that arises from the epithelium. Carcinomas are cancerous tumors that tend to infiltrate into adjacent tissue and metastasize to distant organs. An adenocarcinoma is a specific type of carcinoma arising from the lining of the walls of an organ, such as colon or rectum. Herein, the terms “carcinoma” and “adenocarcinoma” are used interchangeably. There is a clear need in the art for new methods for diagnosing, treating and preventing colorectal carcinoma, particularly at the early stages—before to the carcinoma metastasizes to other organ systems.

An “adenoma” is a benign epithelial tumor in which the cells form a recognizable glandular structure or in which the cells are clearly derived from glandular epithelium. Many colon cancers have been demonstrated to develop through the “adenoma-to-carcinoma sequence” model in the literature (auto et al., (1975) Cancer, 36, 2251-2270). Accordingly, in colorectal tumors, adenoma is the pre-malignant phase of colorectal carcinoma Early detection and diagnosis of adenoma is useful in preventing the onset of carcinormalikewise, the treatment and prevention of adenoma can protect the progressing into colorectal carcinoma in a subject.

The present invention describes genes that discriminate between colorectal tumors and normal epithelium as well as genes that discriminate between adenomas and carcinomas. Such genes are herein collectively referred to as “marker genes”. The present invention demonstrates that the expression of such marker genes can be analyzed to distinguish between tumor cells from normal cells, more preferably adenomas (i.e., benign or pre-malignant tumors) and carcinomas (i.e., malignant tumors).

The term “expression profile” as used herein refers to a collection of expression levels of a number of genes. In the context of the present invention, the expression profile preferably comprises marker genes that discriminate between adenomas and carcinomas. The present invention involves the step of analyzing expression profiles of marker genes to determine if a sample displays characteristics of colorectal cancer, thereby distinguishing colorectal cancers from pre-malignant lesions and diagnosing the presence of colorectal cancer in a subject.

The term “characteristics of a colorectal cancer” is used herein to refer to a pattern of alterations in the expression levels of a set of marker genes which is characteristic to colorectal cancer. Specifically, certain marker genes are described herein either up-regulated or down-regulated in colorectal cancer. When the expression level of one or more up-regulated marker genes included in the expression profile is elevated as compared with that in a control, the expression profile can be assessed as having the characteristics of colorectal cancer. Likewise, when the expression level of one or more down-regulated marker genes included in the expression profile is lowered as compared with that of a control, the expression profile can be assessed as having the characteristics of colorectal cancer. When, not all, but most of the pattern of alteration in the expression levels constituting the expression profile is characteristic to colorectal cancer, the expression profile is assessed to have the characteristics of colorectal cancer.

In the context of the present invention, expression profiles can be obtained by using a “DNA array”. A “DNA array” is a device that is convenient for comparing expression levels of a number of genes at the same time. DNA array -based expression profiling can be carried out, for example, by the method as disclosed in “Microarray Biochip Technology” (Mark Schena, Eaton Publishing, 2000), etc.

A DNA array comprises immobilized high-density probes to detect a number of genes. In the present invention, any type of polynucleotide can be used as probes for the DNA array. Preferably, cDNAs, PCR products, and oligonucleotides are usefuil as probes. Thus, expression levels of many genes can be estimated at the same time by a single-round analysis. Namely, the expression profile of a specimen can be determined with a DNA array. The DNA array-based method of the present invention comprises the following steps of:

(1) synthesizing aRNAs or eDNAs including those of marker genes;

(2) hybridizing the aRNAs or cDNAs with probes for the marker genes; and

(3) detecting the aRNA or cDNA hybridizing with the probes and quantifyig the amount of mRNA thereof.

The term “aRNA” refers to RNA transcribed from a template cDNA with RNA polymerase (amplified RNA). A aRNA transcription kit for DNA array-based expression profiling is commercially available. With such a kit, aRNA can be synthesized using T7 promoter-attached CDNA as a template with T7 RNA polymerase. Alternatively, by PCR using random primer, CDNA can be amplified using, as a template, a CDNA synthesized from mRNA.

The DNA array may further comprise probes, which have been spotted thereon, to detect the marker genes of the present invention. There is no limitation on the number of marker genes spotted on the DNA array. For example, one may select 5% or more, preferably 20% or more, more preferably 50% or more, still more preferably 70 % or more of the marker genes of the present invention. Genes other than the marker genes may be also spotted on the DNA array. For example, a probe for a gene whose expression level is not significantly altered may be spotted on the DNA array. Such a gene can be used for normalizing assay results to compare assay results of multiple arrays or different assays.

A “probe” is designed for each selected marker gene, and spotted on a DNA array. Such a “probe” may be, for example, an oligonucleotide comprising 5-50 nucleotide residues. A method for synthesizing such oligonucleotides on a DNA array is known to those skilled in the art. Longer DNAs can be synthesized by PCR or chemically. A method for spotting long DNA, which is synthesized by PCR or the like, onto a glass slide is also known to those skilled in the art. A DNA array that is obtained by the method as described above can be used for diagnosing colorectal cancer according to the present invention.

The prepared DNA array is contacted with aRNA, followed by the detection of hybridization between the probe and aRNA. The aRNA can be previously labeled with a fluorescent dye. A fluorescent dye such as Cy3(red) and Cy5 (blue) can be used to label a aRNA. aRNA s from subject and control are labeled with different fluorescent dyes, respectively. The difference in the expression level between the two can be estimated based on a difference in the signal intensity. The signal of fluorescent dye on the DNA array can be detected by a scanner and analyzed using a special program. For example, the Suite from Affymetrix is a software package for DNA array analysis.

The compound isolated by the screening is a candidate for drugs that inhibit the activity of the protein encoded by marker genes and can be applied to the treatment or prevention of colorectal tumors.

Moreover, compound in which a part of the structure of the compound inhibiting the activity of proteins encoded by marker genes is converted by addition, deletion and/or replacement are also included in the compounds obtainable by the screening method of the present invention.

When administrating the compound isolated by the method of the invention as a pharmaceutical for humans and other mammals, such as mice, rats, guinea-pigs, rabbits, chicken, cats, dogs, sheep, pigs, cattle, monkeys, baboons, and chimpanzees, the isolated compound can be directly administered or can be formulated into a dosage form using known pharmaceutical preparation methods. For example, according to the need, the drugs can be taken orally, as sugar-coated tablets, capsules, elixirs and microcapsules, or non-orally, in the form of injections of sterile solutions or suspensions with water or any other pharmaceutically acceptable liquid. For example, the compounds can be mixed with pharmaceutically acceptable carriers or media, specifically, sterilized water, physiological saline, plant-oils, emulsifiers, suspending agents, surfactants, stabilizers, flavoring agents, excipients, vehicles, preservatives, binders, and such, in a unit dose form required for generally accepted drug implementation. The amount of active ingredients in these preparations makes a suitable dosage within the indicated range acquirable.

Examples of additives that can be mixed to tablets and capsules are, binders such as gelatin, corn starch, tragacanth gum and arabic gum; excipients such as crystalline cellulose; swelling agents such as corn starch, gelatin and alginic acid; lubricants such as magnesium stearate; sweeteners such as sucrose, lactose or saccharin; and flavoring agents such as peppermint, Gaultheria adenothrix oil and cherry. When the unit-dose form is a capsule, a liquid carrier, such as an oil, can also be further included in the above ingredients. Sterile composites for injections can be formulated following normal drug implementations using vehicles such as distilled water used for injections.

Physiological saline, glucose, and other isotonic liquids including adjuvants, such as D-sorbitol, D-mannnose, D-mannitol, and sodium chloride, can be used as aqueous solutions for injections. These can be used in conjunction with suitable solubilizers, such as alcohol, specifically ethanol, polyalcohols such as propylene glycol and polyethylene glycol, non-ionic surfactants, such as Polysorbate 80 (TM) and HCO-50.

Sesame oil or Soy-bean oil can be used as a oleaginous liquid and may be used in conjunction with benzyl benzoate or benzyl alcohol as a solubilizer and may be formulated with a buffer, such as phosphate buffer and sodium acetate buffer; a pain-killer, such as procaine hydrochloride; a stabilizer, such as benzyl alcohol andphenol; and an anti-oxidant. The prepared injection may be filled into a suitable ampule.

Methods well known to one skilled in the art may be used to administer the pharmaceutical composition of the present inevntion to patients, for example as intraarterial, intravenous, or percutaneous injections and also as intranasal, transbronchial, intramuscular or oral administrations. The dosage and method of administration vary according to the body-weight and age of a patient and the administration method; however, one skilled in the art can routinely select a suitable metod of administration. If said compound is encodable by a DNA, the DNA can be inserted into a vector for gene therapy and the vector administered to a patient to perform the therapy. The dosage and method of administration vary according to the body-weight, age, and symptoms of the patient but one skilled in the art can suitably select them.

For example, although the dose of a compound that binds to the protein of the present invention and regulates its activity depends on the symptoms, the dose is about 0.1 mg to about 100 mg per day, preferably about 1.0 mg to about 50 mg per day and more preferably about 1.0 mg to about 20 mg per day, when administered orally to a normal adult (weight 60 kg).

When administering parenterally, in the form of an injection to a normal adult (weight 60 kg), although there are some differences according to the patient, target organ, symptoms and method of administration, it is convenient to intravenously inject a dose of about 0.01 mg to about 30 mg per day, preferably about 0.1 to about 20 mg per day and more preferably about 0.1 to about 10 mg per day. Also, in the case of other animals too, it is possible to administer an amount converted to 60 kgs of body-weight

As noted above, antisense nucleic acids corresponding to the nucleotide sequence of a marker gene can be used to reduce the expression level of the marker gene. Antisense nucleic acids corresponding to marker genes that are up-regulated in colorectal carcinoma are useful for the treatment of colorectal carcinoma Specifically, the antisense nucleic acids of the present invention may act by binding to the marker genes or mRNAs corresponding thereto, thereby inhibiting the transcription or translation of the genes, promoting the degradation of the mRNAs, and/or inhibiting the expression of proteins encoded by the marker genes, finally inhibiting the function of the proteins . The term “antisense nucleic acids” as used herein encompasses both nucleotides that are entirely complementary to the target sequence and those having a mismatch of one or more nucleotides, so long as the antisense nucleic acids can specifically hybridize to the target sequences. For example, the antisense nucleic acids of the present invention include polynucleotides that have a homology of at least 70% or higher, preferably at 80% or higher, more preferably 90% or higher, even more preferably 95% or higher over a span of at least 15 continuous nucleotides. Algorithms known in the art can be used to determine the homology.

The antisense nucleic acid derivatives of the present invention act on cells producing the proteins encoded by marker genes by binding to the DNAs or mRNAs encoding the proteins, inhibiting their transcription or translation, promoting the degradation of the mRNAs, and inhibiting the expression of the proteins, thereby resulting in the inhibition of the protein function.

An antisense nucleic acid derivative of the present invention can be made into an external preparation, such as a liniment or a poultice, by mixing with a suitable base material which is inactive against the derivative.

Also, as needed, the derivatives can be formulated into tablets, powders, granules, capsules, liposome capsules, injections, solutions, nose-drops and freeze-drying agents by adding excipients, isotonic agents, solubilizers, stabilizers, preservatives, pain-killers, and such. These can be prepared by following known methods.

The antisense nucleic acids derivative is given to the patient by directly applying onto the ailing site or by injecting into a blood vessel so that it will reach the site of ailment. An antisense-mounting medium can also be used to increase durability and membrane-permeability. Examples are, liposomes, poly-L-lysine, lipids, cholesterol, lipofectin or derivatives of these.

The dosage of the antisense nucleic acid derivative of the presentinvention can be adjusted suitably according to the patient's condition and used in desired amounts. For example, a dose range of 0.1 to 100 mg/kg, preferably 0.1 to 50 mg/kg can be administered.

The antisense nucleic acids of the invention inhibit the expression of the protein of the invention and is thereby useful for suppressing the biological activity of a protein of the invention. Also, expression-inhibitors, comprising the antisense nucleic acids of the invention, are useful since they can inhibit the biological activity of a protein of the invention.

The antisense nucleic acids of present invention include modified oligonucleotides. For example, thioated nucleotides may be used to confer nuclease resistance to an oligonucleotide.

The present invention refers to the use of antibodies, particularly antibodies against a protein encoded by an up-regulated marker gene, or a fragment of the antibody. As used herein, the term “antibody” refers to an immunoglobulin molecule having a specific structure, that interacts (i.e., binds) only with the antigen that was used for synthesizing the antibody (i.e., the up-regulated marker gene product) or with an antigen closely related to it. Furthermore, an antibody may be a fragment of an antibody or a modified antibody, so long as it binds to one or more of the proteins encoded by the marker genes. For instance, the antibody fragment may be Fab, F(ab′)2, Fv, or single chain Fv (scFv), in which Fv fragments from H and L chains are ligated by an appropriate linker (Huston J. S. et al. Proc. Natl. Acad. Sci. U.S.A. 85:5879-5883 (1988)). More specifically, an antibody fragment may be generated by treating an antibody with an enzyme, such as papain or pepsin. Alternatively, a gene encoding the antibody fragment may be constructed, inserted into an expression vector, and expressed in an appropriate host cell (see, for example, Co M. S. et al. J. Immunol. 152:2968-2976 (1994); Better M. and Horwitz A. H. Methods Enzymol. 178:476-496 (1989); Pluckthun A. and Skerra A. Methods Enzymol. 178:497-515 (1989); Lamoyi E. Methods Enzymol. 121:652-663 (1986); Rousseaux J. et al. Methods Enzymol. 121:663-669 (1986); Bird R. E. and Walker B. W. Trends Biotechnol. 9:132-137 (1991)).

An antibody may be modified by conjugation with a variety of molecules, such as polyethylene glycol (PEG). The present invention provides such modified antibodies. The modified antibody can be obtained by chemically modifying an antibody. These modification methods are conventional in the field.

Alternatively, an antibody may be obtained as a chimeric antibody, between a variable region derived from a nonhuman antibody and a constant region derived from a human antibody, or as a humanized antibody, comprising the complementarity determining region (CDR) derived from a nonhuman antibody, the frame work region (FR) derived from a human antibody, and the constant region. Such antibodies can be prepared by using known technologies.

The present invention provides preventative vaccines. In the context of the present invention, the term “vaccine” refers to antigenic formulations that induce immunity against colorectal tumors. The immunity may be transient and one or more booster administrations may be required.

The antigen within the vaccine may comprise a DNA corresponding to one or more up-regulated marker gene, such as those set forth in Table 1, or a protein encoded by such a marker gene or an antigenic fragment thereof. In the context of the present invention, the term “antigenic fragment” refers to a portion of a molecule, when introduced into the body, stimulates the production of an antibody specific to the marker gene of interest.

Experimental Section

Prior to the present invention, knowledge of genes involved in colorectal tumors was fragmentary. Herein, expression profiles of pre-malignant and malignant lesions of the colon were examined and compared to provide information about genes that undergo altered expression during progression from adenoma to carcinoma. The data described herein provides genome-wide information about how expression profiles are altered during multi-step carcinogenesis.

To elucidate the mechanisms underlying the pathway from adenoma to carcinoma, gene-expression profiles of 20 colorectal tumors (9 adenomas and 11 differentiated adenocarcinomas) were analyzed by means of a CDNA microarray representing 23,040 genes coupled with laser-capture microdissection. Index genes (genes whose expression is different in carcinoma compared to adenoma or normal tissue) were identified. Specifically, 51 genes whose expression was consistently up-regulated and 376 that were consistently down-regulated in both types of tumors as compared to normal colonic epithelium were identified. Fifty. (50) genes whose expression levels were significantly different between adenomas and carcinomas were also identified. A two-dimensional hierarchical clustering analysis of expression profiles of the 20 tumors correctly separated the carcinoma group from the adenoma group. On the basis of expression profiles of the 50 discriminating genes, a scoring system was established to separate adenomas from carcinomas. Application of this scoring system to the evaluation of five additional colorectal tumors correctly predicted their cancer status, which was also independently determined by histological examination.

The scoring system of the present invention provides objective diagnostic information to assist clinicians in diagnosing colorectal tumors and distinguishing adenomas from carcinomas. The data reported herein provides valuable information to enhance understanding of colorectal carcinogenesis, to facilitate development of novel diagnostic strategies, and to identify molecular targets for therapeutic drugs and preventive agents.

The results of the “Molecular Diagnosis Score” (MDS) system using expression profiles of the 50 genes corroborated its feasibility for predicting the histological features of colorectal tumors. Analysis of gene-expression profiles of very early colon cancers is used to define a more precise cut-off value to distinguish between benign and malignant lesions. Nevertheless, since histological diagnosis of adenomas and carcinomas is sometimes very difficult and may vary among pathologists (Schlemper et al., 2000), the MDS system may ultimately be useful in distinguishing benign from malignant tumors because it enables an objective quantification of each tumor based on a genome-wide database.

Tissue samples from non-cancer, pre-cancerous, and cancerous tissues were obtained and analyzed as follows.

Tissue Samples and Laser-Capture Microdissection (LCM)

Eleven differentiated adenocarcinomas, 9 adenomas, and their corresponding normal mucosae of the colon were obtained from 16 patients who underwent colectomy. In four cases, both adenomas and carcinomas had arisen in the same patient. All 20-paired samples were embedded in TissueTek OCT medium (Miles, Inc.) and frozen at −80° C. Procedures of fixation, staining and LCM were performed using known methods, e.g., the method of Kitahara et al., 2001, Cancer Res ., 61, 3544-3549. About 10,000 cells were selectively collected by LCM from each tissue sample.

RNA Extraction, T7-Based RNA Amplification and cDNA Microarray

Extraction of total RNA and T7-based RNA amplification were carried out by standard methods. Two rounds of amplification yielded 15-80 μg of amplified RNA (aRNA) from each sample. A 2.5-μg aliquot of aRNA from each tumor and normal epithelium were labeled with Cy3-dCTP and Cy5-dCTP, respectively (Amersham Pharmacia Biotech). To reduce experimental fluctuation, duplicate sets of cDNA microarray slides containing 23,040 cDNAs for each analysis were used. Fabrication of the CDNA microarray slides, hybridization, washing, and detection of signals were carried out using methods known in the art. The 23,040 genes surveyed were selected from UniGene database (National Center for Biotechnology Information), and their cDNA fragments were amplified by RT-PCR using gene-specific primers for each gene and a variety of human polyA RNAs as template (Clontech).

Data Analysis

The intensity of each signal of Cy3 and Cy5 was evaluated photometrically using Array Vision software (Imaging Research Inc., St. Catherines, Ont. Canada) and normalized according to the expression of 52 housekeeping genes described by Kitahara et al, 2001, Cancer Res ., 61, 3544-3549. After normalization, each gene was separated into one of four categories based on the average Cy3/Cy5 ratio (r): up-regulated (r>2), down-regulated (r<0.5), unchanged (0.5<r<2) and low (expression level below cutoff level for detection). Excel, Cluster and TreeView software packages were used for subsequent analysis.

Validation of Data

To assess the reproducibility of hierarchical clustering, clustering results were compared in the sample axis by using different sets of genes. Specifically, 23,040 target sequences were spotted on five slides and clustering analysis was performed for the 20 samples in all five sets. When one sample consistently fell into the same cluster in different sets of genes, the data was defined as reproducible. The reproducibility was more than 80% when Cy3 or Cy5 fluorescent units were above 100,000. An average was calculated for Cy3- and Cy5-fluorescence intensities of each gene in all 20 cases. Genes were excluded from further analysis when both intensities fell below a cut-off of 1×10⁵ units. Accordingly, a total of 2,425 genes was selected.

Thus, 771 genes were chosen based on the criteria that the values were obtained in more than 16 cases (80%) and the standard deviations of observed values were grater than 5 0.5.

Calculation of “Molecular Diagnosis Score” (MS)

The MDS of each tumor was defined as the sum of weighted log ratios of expression profiles of the 50 genes selected as differentially expressed in adenomas vs. carcinomas: MDS₁=ΣAS_k log₂(r_ik), where r_ik is the expression ratio (Cy3/Cy5) of gene k of patient i, and S_k is the sign for gene k which was determined as follows. The first calculation was the determination of the average log ratio log₂(r_ik) for gene k in the 11 adenocarcinomas and the 9 adenomas (ave_carcinoma=Σlog₂(r_ik)/n_carcinoma and ave_adenoma=Σlog₂(r_ik)/n_adenoma). Then, a sign (±) was determined for each gene: S_k=+1, if ave_carcinoma>ave_adenoma, and S_k=−1, if ave_carcinoma<ave_adenoma (FIG. 4A).

Real-Time Quantitative RT-PCR

To verify the microarray data, six genes were selected and their expression levels examined in 13 additional samples (7 adenomas and 6 carcinomas) by means of real-time quantitative RT-PCR (TaqMan PCR, Perkin-Elmer), using a 7700 Sequence Detector (Perkin-Elmer). Each single-stranded cDNA was reverse-transcribed from amplified RNA and diluted for subsequent PCR amplification. Malate dehydrogenase 1 (MDH1) served as a relative quantitative control since it showed the smallest Cy3/Cy5 fluctuations in 100 hybridizations. Each PCR was carried out in a 25-μl volume and amplified for 10 min at 95° C. for activation of AmpliTaq Gold™, followed by 40 cycles of 95° C. for 15 s and 60° C. for 1 min. The genes and sequences of the primers and probes used for quantitative RT-PCR are listed in Table A below.

TABLE A
Genes, Sequences of Primers and Probes used for quantitative RT-PCR
Symbol	Primer	Probe
MDH1	F:5′-TCCCTGTTGTAATCAAGAATAAGACCT-3′	5′-Vic-TTGTTGAAGGTCTCCCTATTA-
	R:5′-CAGTTCCTTTGCAGTAAGATCCATC-3′	ATGATTTCTCACGTG-Tamra-3′
TGFBI	F:5′-GCAGACTCTGCGCTTGAGATC-3′	5′-Fam-AACAAGCATCAGCGTTTTCC-
	R:5′-GGGCTAGTCGCACAGACCTC-3′	AGGGCT-Tamra-3′
LAP18	F:5′-CAAATGGCTGCCAAACTGG-3′	5′-Fam-CGTTTGCGAGAGAAGGATAA
	R:5′-GGATTCTTTGTTCTTCCGCACT-3′	GCACATTGAAG-Tamra-3′
HECH	F:5′-GACAGCAGTGGAGAATTGATGTTT-3′	5′-Fam-TGAGGCAGACTTGGTGCTGG
	R:5′-ACAATTTGAGGACACTTCATATTTGC-3′	CG-Tamra-3′
NME1	F:5′-GCATACAAGTTGGCAGGAACATTA-3′	5′-Fam-CATGGCAGTGATTCTGTGGA
	R:5′-ACCACAAGCCGATCTCCTTCT-3′	GAGTGCA-Tamra-3′.
TCEA1	F:5′-AGATGCGGAAAAACTTGACCA-3′	5′-Fam-AAGCCATCAGAGAGCATCAG
	R:5′-AGTCAGTCTGGGTCCCACCA-3′	ATGGCC-Tamra-3′
PSMA7	F:5′-GCAGCGTTATACGCAGAGCA-3′	5′-Fam-TGGGCGCAGGCCGTTTGG-
	R:5′-ACCCACGATGAGGGCAGAG-3′	Tamra-3′

Statistics

Assessment of statistical differences of gene expression in carcinomas vs. adenomas was determined by Mann-Whitney U tests. A P value ≦0.05 was considered statistically significant. Statistical analyses were performed using Stat View software.

Two-Dimensional Hierarchical Clustering

To analyze correlation among the samples and genes, a two-dimensional hierarchical clustering algorithm (http://www.microarrays.org/software) was applied to the gene expression data obtained from 20 tumors. Genes were excluded from further analysis when average Cy3- and Cy5-fluorescence intensities fell below 1×10⁵ units. This resulted in the selection of a set of genes whose values were obtained in more than 16 cases (80%).

Next, genes with standard deviations of observed values less than 0.5 were excluded. A total of 771 genes passed through this filter for subsequent clustering analysis.

In the sample axis, the 20 samples were separated into two major groups based on their expression profiles; all of the 9 tumors belonging to one group were adenomas and the other major group consisted of the eleven carcinomas (FIGS. 1A-B). This result is consistent with a recent report that four colon adenomas were separated from 18 adenocarcinomas using oligonucleotide arrays (Notterman et al., 2001). The expression profiles obtained on the microarray clearly demonstrated that adenomas and adenocarcinomas have specific expression profiles,.and indicated that molecular classification of colonic tumors is feasible.

Up-Regulated Genes

Since many colon cancers arise from adenomas, genes involved in early stages of colorectal tumorigenesis are deregulated (compared to normal tissue) in both types of tumors. To identify such genes, genes were selected from a data set of 2,425 genes according to the following criteria: if the Cy3/Cy5 ratio of the gene was >2 in more than 50% of the tumors, it was defined as a consistently up-regulated gene, and if the ratio was <0.5 in more than 50% of the tumors, it was defined as consistently down-regulated.

With these criteria, 51 genes were identified as commonly up-regulated in both tumor phenotypes as compared with their corresponding normal epithelia (FIG. 2). These commonly up-regulated genes are set forth in Table 1 below:

TABLE 1
Genes commonly up-regulated in colonic tumors
					(Cy3/
	ACCESSION			(Cy3/	Cy5 < 0.5),
No.	No.	GENE	DESCRIPTION	Cy5)ave	%, n = 20
1	M77349	TGFBI	transforming growth factor, beta-	12.96	100
			induced, 68 kD
2	X57351	IFITM2	interferon induced transmembrane	5.26	95
			protein 2 (1-8D)
3	M33680	CD81	CD81 antigen (target of	4.34	95
			antiproliferative antibody 1)
4	X53305	LAP18	leukemia-associated	6.27	95
			phosphoprotein p18 (stathmin)
5	AF026292	CCT7	chaperonin containing TCP1,	3.47	90
			subunit 7 (eta)
6	M16660	HSPCB	heat shock 90 kD protein 1, beta	2.96	90
7	AA654440	PABPC1	poly(A)-binding protein,	3.23	90
			cytoplasmic 1
8	AA316619	PRL30	ribosomal protein L30	4.1	90
9	AA149559	MACMARCKS	macrophage myristoylated alanine-	4.31	90
			rich C kinase substrate
10	N76634	FLJ20315	hypothetical protein FLJ20315	4.43	90
11	X55715	RPS3	ribosomal protein S3	5.21	85
12	M58458	RPS4X	ribosomal protein S4, X-linked	4.6	85
13	AA043590	HECH	heterochromatin-like protein 1	4.02	85
14	N77266	RAN	RAN, member RAS oncogene	3.36	80
			family
15	L17131	HMGIY	high-mobility group (nonhistone	4.02	80
			chromosomal) protein isoforms I
			and Y
16	X06323	MRPL3	mitochondrial ribosomal protein L3	2.93	80
17	E02628		cDNA cording for human	3.2	80
			polypeptide chain elongation
			factor-1 alpha
18	D63874	HMG1	high-mobility group (nonhistone	3.23	80
			chromosomal) protein 1
19	Y00711	LDHB	lactate dehydrogenase B	6.47	80
20	AI076603	ESTs	ESTs	3.12	80
21	M16650	ODC1	ornithine decarboxylase 1	3.9	75
22	AA706503	EEF1A1	eukaryotic translation elongation	3.12	75
			factor 1 alpha 1
23	M22382	HSPD1	heat shock 60 kD protein 1	4.6	75
			(chaperonin)
24	AI087287	NOLA2	nucleolar protein family A, member	3	75
			2 (H/ACA small nucleolar RNPs)
25	S79522	RPS27A	ribosomal protein S27a	2.6	75
26	AI300002	CCNI	cyclin I	2.96	75
27	R12013	HDCMC04P	hypothetical protein HDCMC04P	3.33	75
28	L06132	VDAC1	voltage-dependent anion channel 1	2.77	70
29	U66818	UBE2I	ubiquitin-conjugating enzyme E2I	3.19	70
			(homologous to yeast UBC9)
30	J04208	IMPDH2	IMP (inisine monophosphate)	2.81	70
			dehydrogenase 2
31	D56784	DEK	DEK oncogene (DNA binding)	3.15	70
32	AA676585	NPM1	nucleophosmin (nucleolar	5.03	70
			phosphoprotein B23, numatrin)
33	D17554	RPL6	ribosomal protein L6	3.46	70
34	U09953	RPL9	ribosomal protein L9	3.7	70
35	M77234	RPS3A	ribosomal protein S3A	3.25	70
36	AA916688	BRF1	butyrate response factor 1 (EGF-	2.81	70
			response factor 1)
37	AA714394	HMG2	high-mobility group (nonhistone	4.54	70
			chromosomal) protein 2
38	AA579959	CYP2S1	cytochrome P540 family member	4.03	70
			predicted from ESTs
39	AI582493	EST	EST	3.28	70
40	X63629	CDH3	cadherin 3, type 1, P-cadherin	3.59	65
			(placental)
41	AA634090	HNRPA1	heterogeneous nuclear	3.72	65
			ribonucleoprotein A1
42	X17206	RPS2	ribosomal protein S2	3.96	65
43	K00558	K-ALPHA	tubulin, alpha, ubiquitous	3.05	60
44	D87666	HSCPA	heat shock 90 kD protein 1, alpha	2.37	60
45	N30179	PLAB	prostate differentiation factor	7.5	60
46	L15533	PAP	pancreatitis-associated protein	10.04	55
47	D51696	TUBB	tubulin, beta polypeptide	2.96	55
48	X73460	RPL3	ribosomal protein L3	2.36	55
49	M65254	PPP2R1B	protein phosphatase 2 (formerly	2.21	55
			2A), regulatory subunit A (PR 65),
			beta isoform
50	AW511361	SLC29A1	solute carrier family 29 (nucleoside	4.29	55
			transporters), member 1
51	AI291596	PIGPC1	p53-induced protein PIGPC1	2.59	55

Among the 5 1 genes, 19 were involved in RNA/protein processing; e.g. ribosomes, translation elongation/initiation factors, and chaperonins. Other up-regulated genes detected included oncogenes (HMGIY, DEK and NPM1), genes encoding cell adhesion/cytoskeleton molecules (TUBB, K-ALPHA, TGFBI, CDH3 and PAP), genes involved in growth control (IMPDH2 and ODC1), signal transduction (BRF1, PLAB, LAP18, CD81 and MACMARCKS), and cell-cycle control (RAN and UBE2I); transcription factors (HMG1 and HMG2), tumor-associated molecules (PPP2R1B, LDHB and SLC29A1), and others.

Down-Regulated Genes

Next, 376 genes (including 127 expressed sequence tags) were identified as consistently down-regulated in both types of tumor by the criteria described above. This group includes genes associated with programmed cell death (CASP8, CASP9, CFLAR, DFFA, PA WR, TNF, TNFRSF10C and TNFRSF12), immunity (chemokine receptors such as IL1RL2, IL17R and IL3RA), growth suppression (Suppressin, DCN, MADH2 and SST), and tumor suppression (TP53). Other down-regulated genes encode cell adhesion/cytoskeleton molecules (e.g. ADAM8, AVL, CDH17, CEACAM1, CTNNA2, ICAPA, KRT9, and ARHGAP5), various metabolic factors (e.g. BPHL, CA2, CA5A, HSD11B2 and ECHS1), ion transporters (SLC15A2, SLC22A1, SLC4A3 and SLC5A1), a nataral antimicrobial molecule (DEFA6), and others. Metabolic enzymes and ion-transport mediators are key factors for maintaining pivotal cellular functions such as detoxication (CA2, CA5A and BPHL) and acid-base balance. Down-regulation of these genes indicates a disruption of cellular homeostasis in tumors (Lawrence et al., 2001).

The list of genes commonly down-regulated in colorectal tumors is set forth in Table 2 below:

TABLE 2
Genes commonly down-regulated in colonic tumors
					(Cy3/Cy5 < 0.5),
	ACCESSION			(Cy3/Cy5)	%,	down-
No.	No.	GENE	DESCRIPTION	ave	n = 20	TP
1	D49817	PFKFB3	6-phosphofructo-2-	0.2	80	16
			kinase/fructose-2,6-
			biphosphatase 3
2	M55040	ACHE	acetylcholinesterase (YT	0.2	75	15
			blood group)
3	AI052697	AP1G2	adaptor-related protein	0.2	90	18
			complex 1, gamma 2 subunit
4	J03037	CA2	carbonic anhydrase II	0.2	85	17
5	M98331	DEFA6	defensin, alpha 6, Paneth	0.2	75	15
			cell-specific
6	J04058	ETFA	electron-transfer-	0.2	70	14
			flavoprotein, alpha
			polypeptide (glutaric aciduria
			II)
7	M83941	EPHA3	EphA3	0.2	100	20
8	M34057	LTBP1	latent transforming growth	0.2	75	15
			factor beta binding protein 1
9	AF014923	LILRA3	leukocyte immunoglobulin-	0.2	75	15
			like receptor, subfamily A
			(without TM domain),
			member 3
10	U10689	MAGEA5	melanoma antigen, family A, 5	0.2	80	16
11	U97584	PDE4A	phosphodiesterase 4A,	0.2	75	15
			cAMP-specific (dunce
			(Drosophila)-homolog
			phosphodiesterase E2)
12	AA262548	PAWR	PRKC, apoptosis, WT1,	0.2	60	12
			regulator
13	AB011004	UAP1	UDP-N-acteylglucosamine	0.2	100	20
			pyrophosphorylase 1
14	M17254	ERG	v-ets avian erythroblastosis	0.2	70	14
			virus E26 oncogene related
15	Y11094	WNT8B	wingless-type MMTV	0.2	80	16
			integration site family,
			member 8B
16	AA705840		EST	0.2	85	17
17	AA586930		EST	0.2	80	16
18	AA229955		ESTs	0.2	80	16
19	AA628600		ESTs	0.2	75	15
20	AA385061		ESTs	0.2	70	14
21	AA521288		ESTs, Highly similar to	0.2	75	15
			carbonic anhydrase VB
			[H. sapiens]
22	AI091443		Homo sapiens cDNA:	0.2	85	17
			FLJ21425 fis, clone
			COL04162
23	AA633352		Homo sapiens cDNA:	0.2	70	14
			FLJ23067 fis, clone
			LNG04993
24	AI346913	CLONE24904	hypothetical protein	0.2	95	19
25	D26579	ADAM8	a disintegrin and	0.3	80	16
			metalloproteinase domain 8
26	M26393	ACADS	acyl-Coenzyme A	0.3	85	17
			dehydrogenase, C-2 to C-3
			short chain
27	AA583019	ACYP2	acylphosphatase 2, muscle	0.3	95	19
			type
28	U02390	CAP2	adenylyl cyclase-associated	0.3	85	17
			protein 2
29	J03853	ADRA2C	adrenergic, alpha-2C-,	0.3	70	14
			receptor
30	M80776	ADRBK1	adrenergic, beta, receptor	0.3	75	15
			kinase 1
31	AF041449	AVIL	advillin	0.3	90	18
32	M12963	ADH1	alcohol dehydrogenase 1	0.3	80	16
			(class I), alpha polypeptide
33	J04795	AKR1B1	aldo-keto reductase family 1,	0.3	70	14
			member B1 (aldose
			reductase)
34	AI261581	AGPS	alkylglycerone phosphate	0.3	65	13
			synthase
35	Y07701	NPEPPS	aminopeptidase puromycin	0.3	65	13
			sensitive
36	D00097	APCS	amyloid P component,	0.3	60	12
			serum
37	M11567	ANG	angiogenin, ribonuclease,	0.3	85	17
			RNase A family, 5
38	X69838	G9A	ankyrin repeat-containing	0.3	80	16
			protein
39	U48408	AQP6	aquaporin 6, kidney specific	0.3	95	19
40	D31833	AVPR1B	arginine vasopressin	0.3	75	15
			receptor 1B
41	X52151	ARSA	arylsulfatase A	0.3	70	14
42	L05628	ABCC1	ATP-binding cassette, sub-	0.3	85	17
			family C (CFTR/MRP),
			member 1
43	U66879	BAD	BCL2-antagonist of cell	0.3	80	16
			death
44	X81372	BPHL	biphenyl hydrolase-like	0.3	75	15
			(serine hydrolase; breast
			epithelial mucin-associated
			antigen)
45	U39817	BLM	Bloom syndrome	0.3	100	20
46	U07969	CDH17	cadherin 17, LI cadherin	0.3	80	16
			(liver-intestine)
47	L37042	CSNK1A1	casein kinase 1, alpha 1	0.3	80	16
48	AF015450	CFLAR	CASP8 and FADD-like	0.3	90	18
			apoptosis regulator
49	X98173	CASP8	caspase 8, apoptosis-related	0.3	95	19
			cysteine protease
50	U60521	CASP9	caspase 9, apoptosis-related	0.3	95	19
			cysteine protease
51	M94151	CTNNA2	catenin (cadherin-associated	0.3	80	16
			protein), alpha 2
52	AF013611	CTSW	cathepsin W (lymphopain)	0.3	70	14
53	H90902	CDC23	CDC23 (cell division cycle	0.3	80	16
			23, yeast, homolog)
54	U67615	CHS1	Chediak-Higashi syndrome 1	0.3	95	19
55	U54994	CCR5	chemokine (C-C motif)	0.3	75	15
			receptor 5
56	M30185	CETP	cholesteryl ester transfer	0.3	95	19
			protein, plasma
57	U20980	CHAF1B	chromatin assembly factor 1,	0.3	85	17
			subunit B (p60)
58	X92098	RNP24	coated vesicle membrane	0.3	90	18
			protein
59	X70476	COPB2	coatomer protein complex,	0.3	95	19
			subunit beta 2 (beta prime)
60	L29349	CSF2RA	colony stimulating factor 2	0.3	90	18
			receptor, alpha, low-affinity
			(granulocyte-macrophage)
61	M59941	CSF2RB	colony stimulating factor 2	0.3	90	18
			receptor, beta, low-affinity
			(granulocyte-macrophage)
62	AI312573	CPNE3	copine III	0.3	70	14
63	R58976	CORO1C	coronin, actin-binding	0.3	85	17
			protein, 1C
64	J03870	CST1	cystatin SN	0.3	70	14
65	X82224	CCBL1	cysteine conjugate-beta	0.3	95	19
			lyase; cytoplasmic
			(glutamine transaminase K,
			kyneurenine
			aminotransferase)
66	D49738	CKAP1	cytoskeleton-associated	0.3	95	19
			protein 1
67	M14219	DCN	decorin	0.3	85	17
68	S79854	DIO3	deiodinase, iodothyronine,	0.3	100	20
			type III
69	L40817	DNASE1L1	deoxyribonuclease I-like 1	0.3	90	18
70	AI149258	DKK3	dickkopf (Xenopus laevis)	0.3	85	17
			homolog 3
71	U91985	DFFA	DNA fragmentation factor,	0.3	60	12
			45 kD, alpha polypeptide
72	AA252866	KIP2	DNA-dependent protein	0.3	85	17
			kinase catalytic subunit-
			interacting protein 2
73	N63007	DPM1	dolichyl-phosphate	0.3	70	14
			mannosyltransferase
			polypeptide 1, catalytic
			subunit
74	AJ000522	DNAH17	dynein, axonemal, heavy	0.3	90	18
			polypeptide 17
75	U03877	EFEMP1	EGF-containing fibulin-like	0.3	75	15
			extracellular matrix protein 1
76	AF011466	EDG4	endothelial differentiation,	0.3	85	17
			lysophosphatidic acid G-
			protein-coupled receptor, 4
77	X94553	FOXE2	forkhead box E2	0.3	85	17
78	U58975	FRAT1	frequently rearranged in	0.3	85	17
			advanced T-cell lymphomas
79	U63917	GPR30	G protein-coupled receptor	0.3	80	16
			30
80	M84443	GALK2	galactokinase 2	0.3	90	18
81	M19722	FGR	Gardner-Rasheed feline	0.3	80	16
			sarcoma viral (v-fgr)
			oncogene homolog
82	X17254	GATA1	GATA-binding protein 1	0.3	85	17
			(globin transcription factor 1)
83	D14886	GTF2A1	general transcription factor	0.3	85	17
			IIA, 1 (37 kD and 19 kD
			subunits)
84	L19659	GCNT2	glucosaminyl (N-acetyl)	0.3	75	15
			transferase 2, I-branching
			enzyme
85	U92459	GRM8	glutamate receptor,	0.3	85	17
			metabotropic 8
86	U79725	GPA33	glycoprotein A33	0.3	75	15
			(transmembrane)
87	X54101	GNLY	granulysin	0.3	80	16
88	M18930	HPN	hepsin (transmembrane	0.3	95	19
			protease, serine 1)
89	AF040714	HOXA10	homeo box A10	0.3	95	19
90	X61755	HOXC5	homeo box C5	0.3	80	16
91	U14631	HSD11B2	hydroxysteroid (11-beta)	0.3	85	17
			dehydrogenase 2
92	X57206	ITPKB	inositol 1,4,5-trisphosphate	0.3	75	15
			3-kinase B
93	Y11360	IMPA1	inositol(myo)(or 4)-	0.3	95	19
			monophosphatase 1
94	U30329	IPF1	insulin promoter factor 1,	0.3	90	18
			homeodomain transcription
			factor
95	AF055028	IGFBP7	insulin-like growth factor	0.3	90	18
			binding protein 7
96	AA226073	ITM2C	integral membrane protein	0.3	95	19
			2C
97	AF012023	ICAPA	integrin cytoplasmic domain-	0.3	95	19
			associated protein 1
98	M34480	ITGA2B	integrin, alpha 2b (platelet	0.3	70	14
			glycoprotein IIb of IIb/IIIa
			complex, antigen CD41B)
99	L25851	ITGAE	integrin, alpha E (antigen	0.3	95	19
			CD103, human mucosal
			lymphocyte antigen 1; alpha
			polypeptide)
100	Y00796	ITGAL	integrin, alpha L (antigen	0.3	90	18
			CD11A (p180), lymphocyte
			function-associated antigen
			1; alpha polypeptide)
101	Z56281	IRF3	interferon regulatory factor 3	0.3	90	18
102	U49065	IL1RL2	interleukin 1 receptor-like 2	0.3	90	18
103	U03187	IL12RB1	interleukin 12 receptor, beta 1	0.3	75	15
104	M74782	IL3RA	interleukin 3 receptor, alpha	0.3	75	15
			(low affinity)
105	L01100	ICA1	islet cell autoantigen 1	0.3	70	14
			(69 kD)
106	X55885	KDELR1	KDEL (Lys-Asp-Glu-Leu)	0.3	80	16
			endoplasmic reticulum
			protein retention receptor 1
107	Z29074	KRT9	keratin 9 (epidermolytic	0.3	70	14
			palmoplantar keratoderma)
108	AF028840	LOC51045	Kruppel-associated box	0.3	80	16
			protein
109	U69566	LATS2	LATS (large tumor	0.3	85	17
			suppressor, Drosophila)
			homolog 2
110	AA779658	LEPR	leptin receptor	0.3	80	16
111	D50532	HML2	macrophage lectin 2	0.3	90	18
			(calcium dependent)
112	AA628220	MBL1P1	mannose-binding lectin	0.3	90	18
			(protein A) 1, pseudogene 1
113	AF056334	MAGEC1	melanoma antigen, family C, 1	0.3	80	16
114	M65131	MUT	methylmalonyl Coenzyme A	0.3	75	15
			mutase
115	X96698	METTL1	methyltransferase-like 1	0.3	95	19
116	U77129	MAP4K5	mitogen-activated protein	0.3	100	20
			kinase kinase kinase kinase 5
117	AF060154	MSC	musculin (activated B-cell	0.3	90	18
			factor)
118	U75330	NCAM2	neural cell adhesion	0.3	95	19
			molecule 2
119	U77968	NPAS1	neuronal PAS domain	0.3	60	12
			protein 1
120	U17989	GS2NA	nuclear autoantigen	0.3	80	16
121	U16258	NFKBIL2	nuclear factor of kappa light	0.3	90	18
			polypeptide gene enhancer
			in B-cells inhibitor-like 2
122	U15306	NFX1	nuclear transcription factor,	0.3	80	16
			X-box binding 1
123	U30185	OPRL1	opiate receptor-like 1	0.3	75	15
124	U42387	PPYR1	pancreatic polypeptide	0.3	95	19
			receptor 1
125	L40401	ZAP128	peroxisomal long-chain acyl-	0.3	90	18
			coA thioesterase; putative
			protein
126	AI188655	PDCL	phosducin-like	0.3	75	15
127	U03090	PLA2G5	phospholipase A2, group V	0.3	95	19
128	U07364	KCNJ4	potassium inwardly-	0.3	85	17
			rectifying channel, subfamily
			J, member 4
129	AI341177	PPARBP	PPAR binding protein	0.3	85	17
130	AJ001810	CFIM25	pre-mRNA cleavage factor	0.3	85	17
			lm (25 kD)
131	AF009243	PRRG2	proline-rich Gla (G-	0.3	90	18
			carboxyglutamic acid)
			polypeptide 2
132	AI357236	PRM1	protamine 1	0.3	80	16
133	AB003177	PSMD9	proteasome (prosome,	0.3	80	16
			macropain) 26S subunit,
			non-ATPase, 9
134	AA532845	P5	protein disulfide isomerase-	0.3	80	16
			related protein
135	U48250	PRKCBP2	protein kinase C binding	0.3	80	16
			protein 2
136	X80910	PPP1CB	protein phosphatase 1,	0.3	90	18
			catalytic subunit, beta
			isoform
137	U26446	PPOX	protoporphyrinogen oxidase	0.3	95	19
138	X83688	P2RX1	purinergic receptor P2X,	0.3	90	18
			ligand-gated ion channel, 1
139	D38449	GPR	putative G protein coupled	0.3	75	15
			receptor
140	AA196253	RAD51C	RAD51 (S. cerevisiae)	0.3	75	15
			homolog C
141	L08010	REG1B	regenerating islet-derived 1	0.3	90	18
			beta (pancreatic stone
			protein, pancreatic thread
			protein)
142	AF073710	RGS9	regulator of G-protein	0.3	75	15
			signalling 9
143	AF012270	RRH	retinal pigment epithelium-	0.3	80	16
			derived rhodopsin homolog
144	U17032	ARHGAP5	Rho GTPase activating	0.3	75	15
			protein 5
145	AL009266	RBM9	RNA binding motif protein 9	0.3	70	14
146	D28483	RBMS2	RNA binding motif, single	0.3	85	17
			stranded interacting protein 2
147	AI161013	S100A12	S100 calcium-binding	0.3	85	17
			protein A12 (calgranulin C)
148	AF031920	SGCE	sarcoglycan, epsilon	0.3	70	14
149	M90439	SERPINF1	serine (or cysteine)	0.3	85	17
			proteinase inhibitor, clade F
			(alpha-2 antiplasmin,
			pigment epithelium derived
			factor), member 1
150	U59305	PK428	Ser-Thr protein kinase	0.3	85	17
			related to the myotonic
			dystrophy protein kinase
151	U71383	SIGLEC5	sialic acid binding lg-like	0.3	90	18
			lectin 5
152	L41142	STAT5A	signal transducer and	0.3	70	14
			activator of transcription 5A
153	AA521019	SNRPG	small nuclear	0.3	85	17
			ribonucleoprotein
			polypeptide G
154	AA084871	YKT6	SNARE protein	0.3	85	17
155	M81758	SCN4A	sodium channel, voltage-	0.3	75	15
			gated, type IV, alpha
			polypeptide
156	S78203	SLC15A2	solute carrier family 15	0.3	85	17
			(H+/peptide transporter),
			member 2
157	U77086	SLC22A1	solute carrier family 22	0.3	80	16
			(organic cation transporter),
			member 1
158	AA401224	SLC25A14	solute carrier family 25	0.3	80	16
			(mitochondrial carrier, brain),
			member 14
159	L02785	SLC26A3	solute carrier family 26,	0.3	80	16
			member 3
160	U05596	SLC4A3	solute carrier family 4, anion	0.3	75	15
			exchanger, member 3
161	Y16610	SPG7	spastic paraplegia 7,	0.3	95	19
			paraplegin (pure and
			complicated autosomal
			recessive)
162	AA889336	SPAG6	sperm associated antigen 6	0.3	85	17
163	AJ222801	SMPD2	sphingomyelin	0.3	80	16
			phosphodiesterase 2,
			neutral membrane (neutral
			sphingomyelinase)
164	AF055460	STC2	stanniocalcin 2	0.3	95	19
165	X63597	SI	sucrase-isomaltase	0.3	80	16
166	AF007165	SPN	suppressin (nuclear	0.3	75	15
			deformed epidermal
			autoregulatory factor
			(DEAF)-related)
167	L10123	SPAR	surfactant protein A binding	0.3	85	17
			protein
168	AF009039	SYNJ1	synaptojanin 1	0.3	85	17
169	AI348910	STX10	syntaxin 10	0.3	85	17
170	AF004562	STXBP1	syntaxin binding protein 1	0.3	100	20
171	U03399	TCP10	t-complex 10 (a murine tcp	0.3	70	14
			homolog)
172	D29767	TEC	tec protein tyrosine kinase	0.3	85	17
173	U86136	TEP1	telomerase-associated	0.3	95	19
			protein 1
174	X59434	TST	thiosulfate sulfurtransferase	0.3	90	18
			(rhodanese)
175	D38081	TBXA2R	thromboxane A2 receptor	0.3	65	13
176	AI142918	TJP3	tight junction protein 3 (zona	0.3	80	16
			occludens 3)
177	AF007872	TOR1B	torsin family 1, member B	0.3	95	19
			(torsin B)
178	U85658	TFAP2C	transcription factor AP-2	0.3	90	18
			gamma (activating
			enhancer-binding protein 2
			gamma)
179	AA215687	TACC3	transforming, acidic coiled-	0.3	100	20
			coil containing protein 3
180	D10653	TM4SF2	transmembrane 4	0.3	85	17
			superfamily member 2
181	M16441	TNF	tumor necrosis factor (TNF	0.3	85	17
			superfamily, member 2)
182	AF012536	TNFRSF10C	tumor necrosis factor	0.3	95	19
			receptor superfamily,
			member 10c, decoy without
			an intracellular domain
183	U43408	TNK1	tyrosine kinase, non-	0.3	65	13
			receptor, 1
184	D49676	U2AF1RS1	U2 small nuclear	0.3	90	18
			ribonucleoprotein auxiliary
			factor, small subunit 1
185	AF079564	USP2	ubiquitin specific protease 2	0.3	65	13
186	AA703115	USP24	ubiquitin specific protease	0.3	70	14
			24
187	AA702803	BM039	uncharacterized bone	0.3	80	16
			marrow protein BM039
188	AI081684	VNN1	vanin 1	0.3	100	20
189	AA912674	VE-JAM	vascular endothelial	0.3	90	18
			junction-associated
			molecule
190	L13288	VIPR1	vasoactive intestinal peptide	0.3	75	15
			receptor 1
191	X15218	SKI	v-ski avian sarcoma viral	0.3	75	15
			oncogene homolog
192	U12707	WAS	Wiskott-Aldrich syndrome	0.3	95	19
			(eczema-thrombocytopenia)
193	U66561	ZNF184	zinc finger protein 184	0.3	80	16
			(Kruppel-like)
194	U95044	ZNF230	zinc finger protein 230	0.3	80	16
195	U40462	ZNFN1A1	zinc finger protein, subfamily	0.3	80	16
			1A, 1 (Ikaros)
196	AA614419		EST	0.3	90	18
197	AA744242		EST	0.3	90	18
198	AA757990		EST	0.3	85	17
199	AA758080		EST	0.3	85	17
200	AA634552		EST	0.3	85	17
201	AA700554		EST	0.3	80	16
202	AA609289		EST	0.3	80	16
203	AA747958		EST	0.3	75	15
204	AA626369		EST	0.3	85	17
205	AA758302		EST	0.3	85	17
206	AA609343		EST	0.3	80	16
207	AA663323		EST	0.3	85	17
208	AA709224		EST	0.3	70	14
209	AA625955		EST	0.3	65	13
210	AA442345		ESTs	0.3	100	20
211	R10153		ESTs	0.3	95	19
212	AA759254		ESTs	0.3	95	19
213	AA829640		ESTs	0.3	95	19
214	AA034063		ESTs	0.3	90	18
215	W88544		ESTs	0.3	90	18
216	AA827701		ESTs	0.3	90	18
217	T79190		ESTs	0.3	85	17
218	H16240		ESTs	0.3	95	19
219	R44603		ESTs	0.3	85	17
220	AA694517		ESTs	0.3	85	17
221	AA620749		ESTs	0.3	85	17
222	W95087		ESTs	0.3	85	17
223	AA495917		ESTs	0.3	85	17
224	W39642		ESTs	0.3	85	17
225	N67031		ESTs	0.3	85	17
226	AA758209		ESTs	0.3	80	16
227	AA702399		ESTs	0.3	80	16
228	R41450		ESTs	0.3	90	18
229	AA634446		ESTs	0.3	90	18
230	R84284		ESTs	0.3	85	17
231	AA534321		ESTs	0.3	85	17
232	N63761		ESTs	0.3	85	17
233	AA427610		ESTs	0.3	85	17
234	R07651		ESTs	0.3	80	16
235	AA002191		ESTs	0.3	75	15
236	AA701558		ESTs	0.3	75	15
237	H70098		ESTs	0.3	80	16
238	H04150		ESTs	0.3	80	16
239	U55988		ESTs	0.3	75	15
240	R00186		ESTs	0.3	70	14
241	AI057128		ESTs	0.3	70	14
242	AA481948		ESTs	0.3	70	14
243	R19897		ESTs	0.3	65	13
244	AA804409		ESTs	0.3	75	15
245	AA602585		ESTs	0.3	75	15
246	AI078363		ESTs	0.3	70	14
247	AI299327		ESTs	0.3	65	13
248	H15165		ESTs	0.3	70	14
249	AA453726		ESTs	0.3	65	13
250	AA427737		ESTs	0.3	65	13
251	AA669139		ESTs	0.3	70	14
252	AA743399		ESTs	0.3	70	14
253	AA019167		ESTs	0.3	65	13
254	AI344053		ESTs	0.3	65	13
255	AI224893		ESTs, Highly similar to	0.3	75	15
			KJHUAB N-
			acetylgalactosamine-4-
			sulfatase [H. sapiens]
256	AA634543		ESTs, Moderately similar to	0.3	80	16
			IGF-II mRNA-binding protein
			3 [H. sapiens]
257	AI222465		ESTs, Moderately similar to	0.3	80	16
			JC1235 transcription factor
			BTF3a [H. sapiens]
258	AA478781		ESTs, Weakly similar to	0.3	65	13
			similar to yeast adenylate
			cyclase [H. sapiens]
259	AA612666		Homo sapiens BAC clone	0.3	95	19
			215O12 NG35, NG36, G9A,
			NG22, G9, HSP70-2,
			HSP70, HSP70-HOM,
			snRNP, G7A, NG37, NG23,
			and MutSH5 genes,
			complete cds
260	AA565741		Homo sapiens cDNA	0.3	95	19
			FLJ10131 fis, clone
			HEMBA1003041
261	N74014		Homo sapiens cDNA	0.3	80	16
			FLJ12229 fis, clone
			MAMMA1001181, weakly
			similar to ABC1 PROTEIN
			HOMOLOG PRECURSOR
262	D81580		Homo sapiens cDNA	0.3	85	17
			FLJ12782 fis, clone
			NT2RP2001869, moderately
			similar to ZINC FINGER
			PROTEIN 191
263	AA292001		Homo sapiens cDNA:	0.3	90	18
			FLJ22251 fis, clone
			HRC02686
264	AI123509		Homo sapiens cDNA:	0.3	85	17
			FLJ23107 fis, clone
			LNG07738
265	AF063725		Homo sapiens clone	0.3	70	14
			BCSynL38 immunoglobulin
			lambda light chain variable
			region mRNA, partial cds
266	AA430290		Homo sapiens mRNA; cDNA	0.3	90	18
			DKFZp434C1717 (from
			clone DKFZp434C1717);
			partial cds
267	H98096		Homo sapiens mRNA; cDNA	0.3	85	17
			DKFZp434M196 (from clone
			DKFZp434M196)
268	N48361		Homo sapiens mRNA; cDNA	0.3	85	17
			DKFZp564O1016 (from
			clone DKFZp564O1016)
269	AI365683		Homo sapiens PAC clone	0.3	80	16
			RP4-751H13 from 7q35-qter
270	N80334	DKFZP586O0223	hypothetical protein	0.3	85	17
271	AA788772	DKFZp762B226	hypothetical protein	0.3	70	14
			DKFZp762B226
272	R05487	FLJ10955	hypothetical protein	0.3	75	15
			FLJ10955
273	AA825485	FLJ13163	hypothetical protein	0.3	85	17
			FLJ13163
274	AA620802	FLJ20284	hypothetical protein	0.3	100	20
			FLJ20284
275	AA037467	KIAA1165	hypothetical protein	0.3	70	14
			KIAA1165
276	D13645	KIAA0020	KIAA0020 gene product	0.3	75	15
277	AF055995	KIAA0130	KIAA0130 gene product	0.3	75	15
278	AA354387	KIAA0285	KIAA0285 gene product	0.3	85	17
279	AI167403	KIAA0828	KIAA0828 protein	0.3	85	17
280	AI285498	KIAA0962	KIAA0962 protein	0.3	80	16
281	AA477862	KIAA0974	KIAA0974 protein	0.3	85	17
282	W84743	KIAA1203	KIAA1203 protein	0.3	70	14
283	AA234909	KIAA1306	KIAA1306 protein	0.3	80	16
284	AA503387	KIAA1357	KIAA1357 protein	0.3	85	17
285	U90919	LOC57862	clones 23667 and 23775	0.3	100	20
			zinc finger protein
286	AA426093	LOC57862	clones 23667 and 23775	0.3	95	19
			zinc finger protein
287	AA311912	DKFZP564A122	DKFZP564A122 protein	0.3	75	15
288	AI089622	LOC51025	CGI36 protein	0.3	85	17
289	AA040452	LOC51118	CGI-94 protein	0.3	70	14
290	X68487	ADORA2B	adenosine A2b receptor	0.4	80	16
291	H04112	ALG5	Alg5, S. cerevisiae, homolog	0.4	85	17
			of
292	AF070598	ABCB6	ATP-binding cassette, sub-	0.4	80	16
			family B (MDR/TAP),
			member 6
293	AA150869	ADIR	ATP-dependant interferon	0.4	65	13
			response protein 1
294	U61538	CHP	calcium binding protein P22	0.4	85	17
295	U07139	CACNB3	calcium channel, voltage-	0.4	85	17
			dependent beta 3 subunit
296	L19297	CA5A	carbonic anhydrase.VA,	0.4	60	12
			mitochondrial
297	X16354	CEACAM1	carcinoembryonic antigen-	0.4	90	18
			related cell adhesion
			molecule 1 (biliary
			glycoprotein)
298	L39211	CPT1A	carnitine	0.4	65	13
			palmitoyltransferase I, liver
299	X59350	CD22	CD22 antigen	0.4	75	15
300	D13305	CCKBR	cholecystokinin B receptor	0.4	65	13
301	D13900	ECHS1	enoyl Coenzyme A	0.4	75	15
			hydratase, short chain, 1,
			mitochondrial
302	U11690	FGD1	faciogenital dysplasia	0.4	85	17
			(Aarskog-Scott syndrome)
303	U10991	G2	G2 protein	0.4	75	15
304	U03486	GJA5	gap junction protein, alpha	0.4	75	15
			5, 40 kD (connexin 40)
305	U01156	GLP1R	glucagon-like peptide 1	0.4	80	16
			receptor
306	X92518	HMGIC	high-mobility group	0.4	75	15
			(nonhistone chromosomal)
			protein isoform I-C
307	AF039691	HDAC5	histone deacetylase 5	0.4	75	15
308	U79734	HIP1	huntingtin interacting protein 1	0.4	65	13
309	M65291	IL12A	interleukin 12A (natural killer	0.4	75	15
			cell stimulatory factor 1,
			cytotoxic lymphocyte
			maturation factor 1, p35)
310	U58917	IL17R	interleukin 17 receptor	0.4	65	13
311	AF005361	KPNA5	karyopherin alpha 5	0.4	65	13
			(importin alpha 6)
312	U59911	MADH2	MAD (mothers against	0.4	70	14
			decapentaplegic,
			Drosophila) homolog 2
313	U37248	MAN2C1	mannosidase, alpha, class	0.4	80	16
			2C, member 1
314	AF053551	MTX2	metaxin 2	0.4	90	18
315	X80199	MLN51	MLN51 protein	0.4	80	16
316	U88573	NBR2	NBR2	0.4	90	18
317	U22662	NR1H3	nuclear receptor subfamily	0.4	85	17
			1, group H, member 3
318	L25597	PAX2	paired box gene 2	0.4	85	17
319	AF069301	PECI	peroxisomal D3,D2-enoyl-	0.4	75	15
			CoA isomerase
320	AF014402	PPAP2A	phosphatidic acid	0.4	90	18
			phosphatase type 2A
321	K03021	PLAT	plasminogen activator,	0.4	70	14
			tissue
322	T84015	PLEC1	plectin 1, intermediate	0.4	65	13
			filament binding protein,
			500 kD
323	AI188134	POLA2	polymerase (DNA-directed),	0.4	65	13
			alpha (70 kD)
324	U10099	POMZP3	POM (POM121 rat homolog)	0.4	85	17
			and ZP3 fusion protein
325	Z11898	POU5F1	POU domain, class 5,	0.4	70	14
			transcription factor 1
326	R26785	PRSS8	protease, serine, 8	0.4	60	12
			(prostasin)
327	M83738	PTPN9	protein tyrosine	0.4	70	14
			phosphatase, non-receptor
			type 9
328	AA210846	TOM	putative mitochondrial outer	0.4	85	17
			membrane protein import
			receptor
329	AF007892	P2RY6	pyrimidinergic receptor P2Y,	0.4	85	17
			G-protein coupled, 6
330	X75593	RAB13	RAB13, member RAS	0.4	80	16
			oncogene family
331	L26584	RASGRF1	Ras protein-specific guanine	0.4	75	15
			nucleotide-releasing factor 1
332	AA040149	RRN3	RNA polymerase I	0.4	80	16
			transcription factor RRN3
333	AB012122	RUVBL1	RuvB (E coli homolog)-like 1	0.4	85	17
334	AA972254	SACM2L	SAC2 (suppressor of actin	0.4	65	13
			mutations 2, yeast,
			homolog)-like
335	U34044	SPS	SELENOPHOSPHATE	0.4	90	18
			SYNTHETASE; Human
			selenium donor protein
336	X05403	SHBG	sex hormone-binding	0.4	85	17
			globulin
337	AA366773	DKFZP566E144	small fragment nuclease	0.4	70	14
338	AF044197	SCYB13	small inducible cytokine B	0.4	80	16
			subfamily (Cys-X-Cys motif),
			member 13 (B-cell
			chemoattractant)
339	M24847	SLC5A1	solute carrier family 5	0.4	75	15
			(sodium/glucose
			cotransporter), member 1
340	J00306	SST	somatostatin	0.4	75	15
341	AJ001183	SOX10	SRY (sex determining region	0.4	90	18
			Y)-box 10
342	AB006202	SDHD	succinate dehydrogenase	0.4	75	15
			complex, subunit D, integral
			membrane protein
343	AF013591	SUDD	sudD (suppressor of bimD6,	0.4	65	13
			Aspergillus nidulans)
			homolog
344	L12350	THBS2	thrombospondin 2	0.4	80	16
345	U74611	TNFRSF12	tumor necrosis factor	0.4	85	17
			receptor superfamily,
			member 12 (translocating
			chain-association membrane
			protein)
346	U94788	TP53	tumor protein p53 (Li-	0.4	90	18
			Fraumeni syndrome)
347	D49677	U2AF1RS2	U2 small nuclear	0.4	90	18
			ribonucleoprotein auxiliary
			factor, small subunit 2
348	AA010724	LSM2	U6 snRNA-associated Sm-	0.4	80	16
			like protein
349	AI343722	UQCR	ubiquinol-cytochrome c	0.4	75	15
			reductase (6.4 kD) subunit
350	M19720	MYCL1	v-myc avian	0.4	80	16
			myelocytomatosis viral
			oncogene homolog 1, lung
			carcinoma derived
351	X98260	ZRF1	zuotin related factor 1	0.4	65	13
352	AA610700		EST	0.4	85	17
353	AA678375		EST	0.4	80	16
354	AA393442		ESTs	0.4	80	16
355	R40699		ESTs	0.4	90	18
356	H05961		ESTs	0.4	75	15
357	H89713		ESTs	0.4	80	16
358	R44995		ESTs	0.4	75	15
359	T03765		ESTs	0.4	70	14
360	AI241461		ESTs	0.4	75	15
361	N69098		ESTs	0.4	70	14
362	AA533505		ESTs	0.4	70	14
363	H72347		ESTs	0.4	70	14
364	R64448		ESTs	0.4	70	14
365	AI219995		ESTs, Weakly similar to	0.4	60	12
			Y961_HUMAN
			HYPOTHETICAL ZINC
			FINGER PROTEIN
			KIAA0961 [H. sapiens]
366	AA885710		Homo sapiens cDNA:	0.4	70	14
			FLJ20886 fis, clone
			ADKA03257
367	AI052376		Homo sapiens cDNA:	0.4	80	16
			FLJ22054 fis, clone
			HEP09634
368	AI332310	DKFZp762H1311	hypothetical protein	0.4	60	12
			DKFZp762H1311
369	AI341234	DKFZP762I166	hypothetical protein	0.4	85	17
			DKFZp762I166
370	AA286856	FLJ10466	hypothetical protein	0.4	70	14
			FLJ10466
371	AA569394	FLJ12716	hypothetical protein	0.4	70	14
			FLJ12716
372	AA536091	FLJ20151	hypothetical protein	0.4	80	16
			FLJ20151
373	H64396	FLJ20531	hypothetical protein	0.4	70	14
			FLJ20531
374	AI290636	FLJ22215	hypothetical protein	0.4	60	12
			FLJ22215
375	AA400457	KIAA0603	KIAA0603 gene product	0.4	90	18
376	AI266225	DKFZP564G202	DKFZP564G202 protein	0.4	70	14

When the present inventors focused on genes in clusters A and B (FIG. 3), they identified several that regulate bioenergetics. In cluster A, PGK1 and LDHA may be induced by hypoxia (Semenza et al., 1994). Proteasomes (PSMD7 and PSMB8) have been reported to accumulate in cancer cells due to glucose starvation and hypoxia (Ogiso et al., 1999). VDAC3 is one of the voltage-dependent anion-selective channel proteins that plays an important role in regulating mitochondrial homeostasis (Vander Heiden et al., 2000). GSS is a regulator of oxidative stress (Uhlig and Wendel, 1992). Some of the genes in cluster B encode proteins that have been reported to function in adaptation to low-oxygen conditions (GPX2, PP1A, GAPD, AXAM2, ALDH1 and ADAR) (Chu et al., 1993; Zhong and Simous, 1999; Hoeren et al., 1998; Denko et al., 2000), in energy consumption (ATP6A1, ATP]B1, and ATPSA1) (Wodopia et al., 2000) or in carbohydrate metabolism (GMDS).

Verification of Microarray Data By Quantitative-RT-PCR

To examine the reliability of the microarray data, six genes were selected for verification. TGFB1 and L4P18 were up-regulated in both adenomas and carcinomas and the others (HECH, NME1, TCEA1 and PSMA7) were differently expressed between adenomas and carcinomas. Their expression was examined in 13 additional paired aRNA samples (7 adenomas and 6 carcinomas) by quantitative RT-PCR (QRT-PCR). The results confirmed the microarray data for all six genes (FIGS. 4A-B). These data verified the reliability and rationale of the strategy to identify genes that are commonly up-regulated or differently expressed during development and progression of colorectal cancer.

Comparison of Expression Analysis Data in Colon Cancers

The data was compared with two sets of data reported previously. First, information of gene expression profiles in two colon cancer tissues and two non-cancerous colonic mucosae analyzed by means of Serial Analysis of Gene Expression was provided by National Center for Biotechnology Information fttp://www.ncbi.nlm.nih.gov/SAGE/). Among the 100 tags of genes expressed most differently between the cancer and non-cancerous tissues, 50 tags corresponded to independent unique genes in UniGene database. Among the 50 genes corresponding to these 50 tags, four up-regulated genes and 24 down-regulated genes in cancer were contained in the microarray. One of the four up-regulated gene, TGFBI (transforming growth factor, beta-induced, 68 kD) also showed elevated expression (FIG. 2). 18 of the 24 down-regulated genes including TSPAN-1 (tetraspan1), GPA33 (glycoprotein A33), CA1 (carbonic anhydrase 1), MT2A (metallothionein 2A), CEACAM1 (carcinoembryonic antigen-related cell adhesion molecule 1), YF13H12 (protein expressed in thyroid), MUC13 (mucin 13), HLAB (major histocompatibility complex class 1B), DUSP1 (dual specificity phosphatase 1), GSN(gelsolin), LGALS4 (galectin 4), CKB (creatinine kinase, brain type), KRT19 (keratin 19), RVASE1 (RNase A family 1), LFI27 (interferon, alpha-inducible protein 27), PP1201, EPS8R2 (FLJ21935), and an EST(Hs.107139) revealed decreased expression in more than half cases examined.

Next, genes highly expressed in colon cancer tissues were compared to matched non-cancerous tissues, which was reported by Notterman et al. using the Affymetrix Human 6500 GeneChip Set Results showed that only two genes, GTF3A (general transcription factor IIIA) and AHCY (adenosylhomocysteine hydrolase), were in the list of frequently up-regulated genes in cancer (FIG. 5A). However, among the ten other genes that were highly expressed in their cancer tissues and spotted on the array slides, eight genes, such as KIAA0101, PYCR1 (pyrroline 5-carboxylate reductase), HSPE1 (heat shock 10 kD protein 1), CDC25B (cell division cycle 25B), CSE1L (chromosome segregation 1-like), CKS2 (CDC28 protein kinase 2), MMP1 (metalloprotenase 1), and CLNS1A (chloride channel, nucleotide-sensitive, 1A), also showed enhanced expression in more than half of cancer tissues.

Development of a “Molecular Diagnosis Score” (MDS) System

Among the genes expressed differently between adenomas and carcinomas, 50 genes whose expression showed statistically significant differences between the two types of tumors were identified (P ≦0.01, Mann-Whitney U test; FIG. 5A). Table 3 shows a list of genes up-regulated in colorectal adenoma as compared to normal tissues, and as can be seen, no significant difference was observed between carcinoma and normal tissues. Table 4 shows a list of genes up-regulated in colorectal carcinoma as compared to normal tissues, and as can be seen, no significant difference was observed between adenoma and normal tissues.

TABLE 3
Marker genes up-regulated in adenoma
	ACCESSION
No.	No.	GENE	DESCRIPTION	P	SIGN
1	L02326	IGLL2	immunoglobulin lambda-like	0.01	−1
			polypeptide 2
2	X55543	XBP1	X-box binding protein	0.004	−1
3	AI743134	TNRC3	trinucleotide repeart containing 3	0.002	−1
4	X53586	ITGA6	integrin, alpha 6	<0.001	−1
5	U41635	OS-9	amplified in osteosarcoma	<0.001	−1
6	X04299	ADH3	alcohol dehydrogenase 3 (class I),	0.003	−1
			gamma polypeptide
7	M12963	ADH1	alcohol dehydrogenase 3 (class I),	0.002	−1
			alpha polypeptide
8	M57899	UGT1A1	UDP glycosyltransferase 1 family,	<0.001	−1
			polypeptide A1
9	L15203	TFF3	trefoil factor 3 (intestinal)	0.001	−1
10	N34138	GABARAP	GABA(A) recepter-associated	0.002	−1
			protein
11	AF065388	TSPAN1	tetraspan 1	0.002	−1
12	L42176	FHL2	four and a half LIM domeins 2	<0.001	−1
13	AA665097	LOC51323	hypothetical protein	0.001	−1
14	U60808	CDS1	CDP-diacylglycerol synthase	0.008	−1
15	AA447849	SPUVE	protease, serine, 23	0.01	−1
16	AA226073	ITM2C	integral membrane protein 2C	<0.001	−1
17	AI167917	KIAA0826	KIAA0826 protein	<0.001	−1
18	AA443786	FLJ20163	hypothetical protein FLJ20163	<0.001	−1
19	AA532514	ESTs	ESTs	<0.001	−1
20	AA327452	MUC2	mucin 2, intestinal/tracheal	<0.001	−1
21	AA573905	FCGBP	Fc fragment of IgG binding protein	<0.001	−1
22	AA393152	KIF13B	kinesin 13B	<0.001	−1
23	AI338165	HEF1	enhancer of filamentation 1	<0.001	−1
24	Y00815	PTPRF	protein tyrosine phosphatase,	<0.001	−1
			receptor type, F
25	AU149434	RBMX	RNA binding motif protein, X	<0.001	−1
			chromosome
26	AA531016	ESTs	ESTs	0.001	−1
27	AI190293	TIF1B	KRAB-associated protein 1	0.01	−1
28	AA256650	HMAT1	beta, 4 mannosyltransferase	<0.001	−1
29	AF038440	PLD2	phospholipase D2	<0.001	−1
30	AI340150	SQSTM1	sequestome 1	0.005	−1
31	D13900	ECHS1	enoyl Coenzyme A hydratase,	0.003	−1
			short chain, 1
32	AA910550	LEFTB	left-right determination, factor B	0.005	−1

TABLE 4
Marker genes up-regulated in carcinoma
No.	ACCESSION No.	GENE	DESCRIPTION	P	SIGN
1	A977821	COL1A1	collagen, type 1, alpha 1	<0.001	1
2	NM_016587	CBX3	chromobox homolog 3	0.01	1
3	U20272	GTF3A	general transcription facter IIIA	0.002	1
4	J03250	TOP1	topoisomerase(DNA) 1	0.003	1
5	M81601	TCEA1	transcription elongation factor A	<0.001	1
			(SII), 1
6	X02152	LDHA	lactate dehydrogenase A	<0.001	1
7	AA148874	PGAM1	phosphoglycerate mutase 1	<0.001	1
			(brain)
8	AI017668	NDUFS6	NADH dehydrogenase	<0.001	1
			(ubiquinone) Fe—S protein 6
9	X17620	NME1	non-metastatic cells 1, protein	<0.001	1
			(NM23A) expressed in
10	U38846	CCT4	chaperonin containing TCP1,	0.001	1
			subunit 4 (delta)
11	M94083	CCT6A	chaperonin containing TCP1,	0.001	1
			subunit 6A (zeta 1)
12	X52882	TCP1	t-complex 1	<0.001	1
13	M29536	EIF2S2	eukaryotic translation initiation	<0.001	1
			factor 2, subunit 2
14	J03464	COL1A2	collagen, type 1, alpha 2	<0.001	1
15	AA576779	DJ-1	RNA-binding protein regulatory	0.001	1
			subunit
16	AF022815	PSMA7	proteasome	0.002	1
			(prosome, macropain) subunit,
			alpha type 7
17	M61831	AHCY	S-adenosylhomocysteine	0.01	1
			hydrolase
18	U55206	GGH	gamma-glutamyl hydrolase	0.002	1

Based on expression profiles of these 50 genes, a “Molecular Diagnosis Score” (MDS) system was developed as a way to apply that information to clinical diagnosis. The mean score of the 1 1 carcinomas was 77.4±11.6, while that of the 9 adenomas was −5.9±14.4 (mean±SD, P <0.0001, Mann-Whitney U test; FIG. 5B). The cut-off value for discriminating adenocarcinoma from adenoma was defined as 35, an average of the mean values of the two groups.

Five additional tumors were analyzed to verify the reliability of the MDS system. Among the five samples tested, three that showed scores greater than 35 (73.5, 63.2, and 10 64.6); all turned out to be carcinomas by- histological examination. The two samples with scores of less than 35 (10.3 and -1.4, respectively) were both adenomas (FIG. 5B). Since the distribution of MDSs for 14 carcinomas ranging from 57.7 to 94.1 were completely separated from that for 11 adenomas ranging from −33.4 to 16.7, both sensitivity and specificity of the MDS system were 100% on the basis of this cut-off value. In addition, a hierarchical clustering analysis of all 25 samples correctly separated adenomas from carcinomas based on the expression profiles of the 50 selected genes (FIG. 5A).

Characterization of Colon Cancers By Genome Wide Expression Profiling

Defining characteristics of adenoma and adenocarcinoma of the colon were determined through the analysis of genome-wide expression profiles of patient-derived tissue samples. The 51 genes commonly up-regulated in both adenomas and carcinomas included 19 involved in RNA/protein processing; e.g. ribosomes, translation elongation/initiation factors, and chaperoning. Ribosomes are the molecular machines that manufacture proteins according to blueprints of mRNAs that encode them. Interactions of the ribosome with mRNAs, tRNAs, and a number of non-ribosomal protein cofactors such as translation initiation/elongation factors guarantee that polypeptide chains are initiated, elongated and terminated. After translation, polypeptides emerge from the ribosomes and enter the endoplasmic reticulum where chaperonins may remodel the polypeptides. The data indicate that accelerated protein synthesis appears to be a common feature of adenomas and carcinomas and reflects a heavy proliferative burden in both tumor types. In addition, the data suggest that activation of oncogenes, aberrant transduction of signals, deregulation of the cell cycle, impaired growth control, and remodeling of cytoskeletal structures are general features of tumor cells. The genes (and/or the molecules encoded by the genes) are therapeutic targets for the prevention, diagnosis, and treatment of colorectal cancer.

The down-regulated genes defined herein included a number of genes associated with cell death, which indicates that broad repression of programmed cell-death pathways is a crucial step for colorectal tumorigenesis. In addition, the list of commonly down-regulated genes suggests that reduction of growth-suppressive signals and/or tumor-suppressive functions may confer continuous proliferative properties to neoplastic cells. Increasing the expression of genes categorized in this cluster (e.g., by stimulating expression of the endogenous gene or introducing additional copies of the gene using in vivo or ex vivo gene therapy) may be used to prevent the development of cancer in patients at risk of developing these cancers or treat patients suffering from cancers.

A number of genes which discriminate carcinoma from adenoma were identified and found to be relevant to hypoxia Carcinoma cells are likely to be more exposed to starved and hypoxic conditions, where carbohydrate/oxygen homeostasis is impaired, than are adenoma cells. The data indicate that cancer cells change their expression profiles in response to low-nutrient and hypoxic conditions. Since hypoxia is a prognostic indicator in a number of tumors, targeting the genes in this category allows identification of micro-environmental changes during malignant transformation, and defines prognostic predictors for colon cancer.

Consideration of the nature of the genes described above leads us to conclude that activation of oncogenes, augmentation of proliferation signals, attenuation of anti-proliferative signals, avoidance of self-destruction machinery, alteration of cell structure, and adaptation to microenvironmental changes, are of great importance for the development and progression of normal colonic mucosal cells to adenocarcinomas. These six features suggest that adenoma and carcinoma cells share several genetic characteristics but have unique expression profiles, and the genes identified using the methods described herein represent targets for blocking malignant transformation.

INDUSTRIAL APPLICABILITY

The gene-expression analysis of colorectal adenomas and carcinomas described herein, obtained through a combination of laser-capture dissection and genome-wide cDNA microarray, has identified specific genes as targets for cancer prevention and therapy. Based on the expression of a subset of these differentially expressed genes, the present invention provides a molecular diagnosis scoring (MDS) system for identifying colorectal tumors. The MDS system of the present invention is a sensitive, reliable and powerful tool that facilitates sensitive, specific and precise diagnosis of such tumors. This system can be specifically utilized in distinguishing adenomas from carcinomas.

The methods described herein are also useful in the identification of additional molecular targets for prevention, diagnosis and treatment of colorectal tumors. The data reported herein add to a comprehensive understanding of colorectal carcinogenesis, facilitate development of novel diagnostic strategies, and provide clues for identification of molecular targets for therapeutic drugs and preventative agents. Such information contributes to a more profound understanding of colorectal tumorigenesis, particularly adenoma-carcinoma progression, and provide indicators for developing novel strategies for diagnosis, treatment, and ultimately prevention of colorectal carcinomas.

All patents, patent applications, and publications cited herein are incorporated by reference in their entirety. Furthermore, while the invention has been described in detail and with reference to specific embodiments thereof, it will be apparent to one skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention.

Claims

1. A method of diagnosing colorectal tumors in a subject, the method comprising the steps of: (a) detecting an expression level of one or more marker genes in a specimen collected from a subject to be diagnosed, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 1 and the genes listed in Table 2; and (b) comparing the expression level of the one or more marker genes to that of a control, wherein high expression level of a marker gene from Table 1 or a low expression level of a marker gene from Table 2, as compared to control, is indicative of colorectal tumor.

2. The method of claim 1, wherein the expression level of the one or more marker genes is determined by following steps of: synthesizing aRNA or cDNA of the marker genes from a specimen; hybridizing the aRNA or cDNA with probes for marker genes; and detecting the hybridized aRNA or cDNA with the probes quantifying the amount of mRNA thereof.

3. The method of claim 2, wherein the probes are fixed on a DNA array.

4. A method of screening for a therapeutic agent useful in treating or preventing colorectal tumors, said method comprising the steps of: contacting a candidate compound with a cell expressing one or more marker genes, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 1, Table 2, Table 3, and Table 4; and selecting a compound that reduces the expression level of one or more marker genes selected from Table 1, Table 3, and Table 4, as compared to a control, or enhances the expression of one or more marker genes selected from Table 2, as compared to a control.

5. A method of screening for a therapeutic agent usefuil in treating colorectal tumors, said method comprising the steps of: administering a candidate compound to a test animal; measuring the expression level of one or more marker genes in a biological sample from the test animal, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 1, Table 2, Table 3, and Table 4; selecting a compound that reduces the expression level of one or more marker genes selected from Table 1, Table 3, and Table 4, as compared to a control, or enhances the expression of one or more marker genes selected from Table 2, as compared to a control.

6. A method of screening for a therapeutic agent useful in treating colorectal tumors, said method comprising the steps of: contacting a candidate compound with a cell into which a vector comprising the transcriptional regulatory region of one or more marker genes and a reporter gene that is expressed under the control of the transcriptional regulatory region has been introduced, wherein the one or more marker genes are selected from the group consisting of the genes listed in Table 1, Table 2, Table 3, and Table 4; measuring the activity of said reporter gene; and selecting a compound that reduces the expression level of said reporter gene when said marker gene is selected from Table 1, Table 3, and Table 4 or that enhances the expression level of said reporter gene when said marker gene is selected from Table 2, as compared to a control.

7. A method of screening for a therapeutic agent useful in treating colorectal tumors, said method comprising the steps of: contacting a candidate compound with a protein encoded by a marker gene, wherein the marker gene is selected from the group consisting of the genes listed in Table 1, Table 2, Table 3, and Table 4; measuring the activity of said protein; and selecting a compound that reduces the activity of said protein when said marker gene is selected from Table 1, Table 3, and Table 4 or that enhances the activity of said protein when said marker gene is selected from Table 2.

8. The method of any one of claims 4, 5, 6 and 7, wherein the marker gene is selected from the group consisting of the genes listed in Table 3, and wherein colorectal tumor is colorectal adenoma.

9. The method of any one of claims 4, 5, 6 and 7, wherein the marker gene is selected from the group consisting of the genes listed in Table 4, and wherein colorectal tumor is colorectal carcinoma.

10. A method for treating or preventing colorectal tumors, said method comprising the step of administering a compound that is obtained by the method according to any one of claims 4, 5, 6 and 7 .

11. A method for treating or preventing colorectal tumors in a subject, said method comprising the step of administering to the subject an antisense nucleic acids against a marker gene, wherein said marker gene is selected from the group consisting of the genes listed in Table 1, Table 3, and Table 4.

12. A method for treating or preventing colorectal tumors in an subject, said method comprising the step of administering to the subject an antibody or fragment thereof that binds to a protein encoded by a marker gene, wherein said marker gene is selected from the group consisting of the genes listed in Table 1, Table 3, and Table 4.

13. The method of claim 11 or 12, wherein said marker gene is selected from the group consisting of the genes listed in Table 3, and wherein colorectal tumor is colorectal adenoma.

14. The method of claim 11 or 12, wherein said marker gene is selected from the group consisting of the genes listed in Table 4, and wherein colorectal tumor is colorectal carcinoma.

15. A method of treating colorectal tumors in a subject, said method comprising the step of administering to the subject a protein encoded by a marker gene, wherein said marker gene is selected from the group consisting of genes listed in Table 2.

16. A method for vaccinating a subject against colorectal tumors, the method comprising the step of administering: (a) a DNA corresponding to one or more marker genes selected from the group consisting of the genes listed in Table 1, Table 3, and Table 4., (b) a protein encoded by a marker gene, or (c) an antigenic fragment of a protein encoded by a marker gene either alone, or in combination.

17. The method of claim 16, wherein said marker gene is selected from the group consisting of the genes listed in Table 3, and wherein colorectal tumor is colorectal adenoma.

18. The method of claim 16, wherein said marker gene is selected from the group consisting of the genes listed in Table 4, and wherein colorectal tumor is colorectal carcinoma.

19. A vaccine composition for treating or preventing a colorectal tumor, wherein the vaccine composition comprises one or more components selected from the group consisting of: (a) DNA corresponding to one or more marker genes selected from the group consisting of the genes listed in Table 1, Table 3, and Table 4., (b) a protein encoded by a marker gene, and (c) an antigenic fragment of a protein encoded by a marker gene.

20. A method of diagnosing adenoma, the method comprising the steps of: (a) detecting an expression level of one or more marker genes in a specimen collected from a subject to be diagnosed, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 3; and (b) comparing the expression level of the one or more marker genes to that of a control, wherein high expression level of a marker gene selected from Table 3, as compared to the control, is indicative of adenoma.

21. A method of diagnosing carcinoma, the method comprising the steps of: (a) detecting an expression level of one or more marker genes in a specimen collected from a subject to be diagnosed, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 4; and (b) comparing the expression level of the one or more marker genes to that of a control, wherein high expression level of a marker gene selected from Table 4, as compared to the control, is indicative of carcinoma.

22. A method of diagnosing adenoma and carcinoma, the method comprising the steps of (a) detecting an expression level of one or more marker genes in a specimen collected from a subject to be diagnosed, wherein the one or more marker genes is selected from the group consisting of the genes listed in Table 3 and Table 4 ; and (b) comparing the expression level of the one or more marker genes to that of a control, wherein a high expression level of a marker gene selected from Table 3, as compared to the control, is indicative of adenoma, and wherein a high expression level of a marker gene selected from Table 4, as compared to the control, is indicative of carcinoma.

23. The method of claim 22, wherein the marker genes comprise all of the marker genes set forth in Table 3 and Table 4.

24. The method of claim 23, wherein step (b) further comprises the steps of determining a function of the log ratios of the expression profiles over the selected genes comprising summing the weighted log ratios of the expression profiles over the selected genes, wherein the weight for each gene is a first value when the average log ratio is higher for carcinomas than for adenomas and a second value when the average log ratio is lower for carcinomas than for adenomas.