Patent Application
20090227464
The present invention relates to a method for assessing prognosis in cancer patients. More specifically, the invention disclosed hereinbelow provides a genetic analysis technique that may be used to assess the prognosis of patients with Ewing Sarcoma.
Ewing's Sarcoma (ES) is the second most common primary malignant bone tumor in children and adolescents and it belongs to a group of neuroectodermal tumors known as Ewing's Sarcoma Family of Tumors (EFT). This is an aggressive tumor with a high propensity for recurrence and distant metastases [Ginsberg, J. P. et al. “Ewing sarcoma family of tumors: Ewing's sarcoma of bone and soft tissue and the peripheral primitive neuroectodermal tumors.” In: Principles and Practice of Pediatric Oncology, (eds.: Pizzo, P. A. & Poplack) 4th edition, 973-1016, Philadelphia, Pa., 2002].
All EFT share specific translocations resulting in the fusion of the EWS gene on chromosome 22q12 with different ETS oncogenes on different chromosomes; the most frequent (˜95%) is FLI1 on chromosome 11. These translocations are considered distinct diagnostic features of ES tumors [Delattre, O. et al., New Eng. J. Med. 331, 294-299 (1994)].
Both the primary site of the tumor, and the initial response to therapy (assessed histologically as the degree of tumor necrosis following surgery), have become accepted valid prognostic factors in localized tumors. In spite of advances in multimodal therapy, including combination of aggressive chemotherapy, radiotherapy and surgery, about 50% of patients eventually relapse, even after 5 years [Terrier, P. et al., Semin. Diagn. Pathol. 13, 250-257
Current clinical and biological characteristics fail to accurately classify ES patients according to their clinical behavior, and it is therefore essential to search for novel reliable prognostic parameters, already at diagnosis.
It is therefore a purpose of the present invention to provide a genetic profiling method for prognosis assessment of patients presenting with ES.
It is another purpose of the invention to provide materials and kits for performing the aforementioned method.
Further objects and advantages of the present invention will become apparent as the description proceeds.
It has now been found that it is possible to distinguish between ES patients having a good prognosis and those having a poor prognosis by means of comparing gene expression patterns in nucleic acid material isolated from the tumors of said patients. Furthermore, it has been found that this prognosis determination may be performed very early on, during initial diagnosis.
The present invention is primarily directed to a method for assessing the prognosis of ES patients comprising determining the expression pattern of a defined set of genes in tumor material obtained from said patients, and assigning said expression pattern to either a good prognosis or poor prognosis group.
The term “good prognosis” is used herein to indicate that the patients are not expected to show ES-related signs, symptoms or evidence for a period of time compatible with the usual clinical meaning of the term. In many cases, this may be taken to mean that the patient is expected to be free from ES-related symptoms for at least five years from assessment. The term “poor prognosis” is similarly used to indicate that the patients are expected to relapse during treatment or within the first few years following treatment.
The term “expression pattern” is used herein to refer to the overall profile of results obtained when the expression of a defined set of genes is determined. Such a pattern is advantageous since it facilitates the use of both quantitative, statistical analytical techniques as well as permitting rapid visual inspection and comparison of results. Preferably (but not exclusively) such a pattern is obtained by the use of a matrix method, such as a high density microarray method.
Although any suitable technique may be used to determine the expression of the aforementioned defined set of genes, in one preferred embodiment of the method, this technique is a nucleic acid hybridization technique.
In a particularly preferred embodiment, the nucleic acid hybridization technique comprises the steps of extracting total RNA from the ES-patient tumor material, generating double-stranded cDNA from said total RNA, performing in vitro transcription of said cDNA, labeling the RNA transcript obtained thereby, preparing a hybridization mix comprising said labeled RNA transcript together with irrelevant and control nucleic acid sequences, hybridization of said hybridization mix to a solid-state human genome microarray and generating and amplifying a hybridization signal. This hybridization signal provides a visual expression pattern which may then be assigned to one of the good or poor prognosis groups.
In another preferred embodiment, the hybridization technique used is selected from the group consisting of northern blotting and western blotting.
In other preferred embodiments of the invention, gene expression may be determined by the use of a technique other than a hybridization technique. In a particularly preferred embodiment, the technique is selected from the group consisting of RT-PCR, semi-quantitative RT-PCR, quantitative real time RT-PCR, immunohistochemistry and ELISA.
In one particularly preferred embodiment of the method of the invention, the assignment of the gene expression pattern to one of the good or poor prognosis groups is performed by means of a hierarchical clustering technique.
In one preferred embodiment of the method of the invention, the aforementioned defined set of genes comprises genes selected from the group of 818 genes listed in table 1, hereinbelow.
In another preferred embodiment, the defined set of genes consists of between 1 and 100 genes selected from the aforementioned group of 818 genes.
In another preferred embodiment, the defined set of genes consists of between 101 and 200 genes selected from the aforementioned group of 818 genes.
In another preferred embodiment, the defined set of genes consists of between 201 and 300 genes selected from the aforementioned group of 818 genes.
In another preferred embodiment, the defined set of genes consists of between 301 and 400 genes selected from the aforementioned group of 818 genes.
In another preferred embodiment, the defined set of genes consists of between 401 and 500 genes selected from the aforementioned group of 818 genes.
In another preferred embodiment, the defined set of genes consists of between 501 and 600 genes selected from the aforementioned group of 818 genes.
In another preferred embodiment, the defined set of genes consists of between 601 and 700 genes selected from the aforementioned group of 818 genes.
In another preferred embodiment, the defined set of genes consists of between 701 and 818 genes selected from the aforementioned group of 818 genes.
In another aspect, the present invention is also directed to a solid-state nucleic acid microarray comprising at least two nucleic acids affixed to a substrate, wherein each of said at least two nucleic acids consists of a partial sequence of one of the genes present in the aforementioned group of 818 genes.
In one preferred embodiment, the microarray of the present invention comprises between 2 and 100 nucleic acid sequences, wherein each of said sequences consists of a partial sequence of one of the genes present in the aforementioned group of 818 genes.
In another preferred embodiment, the microarray of the present invention comprises between 101 and 200 nucleic acid sequences, wherein each of said sequences consists of a partial sequence of one of the genes present in the aforementioned group of 818 genes.
In another preferred embodiment, the microarray of the present invention comprises between 201 and 300 nucleic acid sequences, wherein each of said sequences consists of a partial sequence of one of the genes present in the aforementioned group of 818 genes.
In another preferred embodiment, the microarray of the present invention comprises between 301 and 400 nucleic acid sequences, wherein each of said sequences consists of a partial sequence of one of the genes present in the aforementioned group of 818 genes.
In another preferred embodiment, the microarray of the present invention comprises between 401 and 500 nucleic acid sequences, wherein each of said sequences consists of a partial sequence of one of the genes present in the aforementioned group of 818 genes.
In another preferred embodiment, the microarray of the present invention comprises between 501 and 600 nucleic acid sequences, wherein each of said sequences consists of a partial sequence of one of the genes present in the aforementioned group of 818 genes.
In another preferred embodiment, the microarray of the present invention comprises between 601 and 700 nucleic acid sequences, wherein each of said sequences consists of a partial sequence of one of the genes present in the aforementioned group of 818 genes.
In another preferred embodiment, the microarray of the present invention comprises between 701 and 818 nucleic acid sequences, wherein each of said sequences consists of a partial sequence of one of the genes present in the aforementioned group of 818 genes.
In a particularly preferred embodiment, the microarray of the present invention comprises all of the 818 genes present in the aforementioned group of genes.
In addition to the aforementioned at least two nucleic acids, the microarray may also comprise one or more control nucleic acid sequences.
The substrate present in the microarray may consist of any suitable material or combination of materials. Preferably, however, the substrate is selected from the group consisting of ceramics, glasses, metal oxides, nitrocellulose and nylon.
In a further aspect, the present invention also provides a kit comprising a solid-state nucleic acid microarray as defined and described herein together with an instruction sheet.
Kits based on the other gene expression technologies used in the method of the invention (as described hereinabove) are also within the scope of the present invention. Thus, in one embodiment, the kit of the present invention comprises a set of relevant primers suitable for use in real time RT-PCR together with control solutions and an instruction sheet. In another embodiment, the kit comprises micro-well plates or similar vessels suitable for use in an ELISA assay, together with antibodies specific for isotopes present on the peptides and polypeptides expressed from the aforementioned defined set of genes, suitable reagents for signal detection and amplification and an instruction sheet. In yet another embodiment, the kit comprises antibodies specific for isotopes present on the peptides and polypeptides expressed from the aforementioned defined set of genes, together with reagents suitable for signal detection and amplification using standard immunochemical methods and an instruction sheet.
All the above and other characteristics and advantages of the present invention will be further understood from the following illustrative and non-limitative examples of preferred embodiments thereof.
a, Illustration of the two sided0 clusters dendogram, distinctly defining poor prognosis (1st 8 columns from left to right) vs. good prognosis (6 right-most columns) groups of ES patients and the differentially expressed genes. Each column represents a patient and each row represents a gene.
b, Kaplan-Meier progression free survival analysis presents a significant correlation between poor prognosis vs. good prognosis patients, according to the microarray classification.
c, The 2 major gene clusters and the 6 subclusters, formed on the basis of the similarities of the 818 genes measured over the 14 tumor samples. The 2 gene clusters consist of differentially expressed genes: over-expressed in the poor prognosis group and down-regulated in the good prognosis group, and vice versa.
a, Expression mean log value of cadherin-11 in poor prognosis patients was significantly higher than the expression mean value in good prognosis patients by both analyses.
b, Gene expression pattern in the poor and good prognosis patients, was also significantly correlated by both analyses, for the MTA1 gene.
As mentioned, hereinabove, ES is the second most common primary malignant bone tumor in children and adolescents. In spite of advances in multimodal therapy, about 50% of patients eventually relapse, even after 5 years or more. Currently accepted clinical prognostic factors, fail to classify ES patients' risk to relapse at diagnosis.
The recent development of DNA microarrays provides an opportunity to take a genome-wide approach to extend biological insights into all aspects of the study of disease: pathogenesis, disease development, staging, prognosis and treatment response. Gene expression profiling using oligonucleotide high-density arrays has provided an additional tool for elucidating tumor biology as well as the potential for molecular classification of cancer.
In the method of the present invention, oligonucleotide high-density array analysis of material derived from primary tumors is used to identify two distinct gene expression profiles distinguishing ES patients with poor and good prognosis. The results obtained with this method (including the results presented in the Example hereinbelow) indicate the existence of a specific gene expression signature of outcome in ES, already at diagnosis thereby providing a strategy, based upon gene expression patterns, for selecting patients who would benefit from risk adapted improved therapy. The gene expression patterns used in this strategy are based on data sets containing a minimum of 1 significant gene out of the 818 genes to a maximum of 818 genes. Intermediate-sized datasets containing up to 100 genes, 200 genes, 300 genes, 400 genes, 500 genes, 600 genes, 700 genes and 800 genes, may also be usefully defined and used in said selection and prognostic strategy. The present invention also encompasses nucleic acid bearing microarrays for use in the method disclosed herein, as well as kits containing all of the necessary materials and instructions for performing the abovementioned strategy or method, as disclosed and described in more detail hereinbelow.
The details of the aforementioned group of 818 genes for use in accordance with a particularly preferred embodiment of the present invention are listed in Table 1:
H. sapiens hsr1 mRNA (partial)
Homo sapiens mRNA; cDNA DKFZp434M162 (from
Homo sapiens mRNA full length insert cDNA clone
Homo sapiens mRNA; cDNA DKFZp434A012 (from
Homo sapiens clone 24487 mRNA sequence
Homo sapiens mRNA; cDNA DKFZp434M245 (from
Homo sapiens mRNA; cDNA DKFZp586K2322 (from
Homo sapiens retinoic acid-inducible endogenous
C. elegans)”
Homo sapiens clone 24507 mRNA sequence
Homo sapiens mRNA; cDNA DKFZp667O1814 (from
Homo sapiens clone 24468 mRNA sequence
Homo sapiens clone 23821 mRNA sequence
Homo sapiens mRNA; cDNA DKFZp586I1319 (from
Homo sapiens mRNA; cDNA DKFZp686N1377 (from
Homo sapiens mRNA; cDNA DKFZp586F2224 (from
Homo sapiens clone 23718 mRNA sequence
Drosophila)”
Homo sapiens mRNA; cDNA DKFZp564O0122 (from
Homo sapiens mRNA; cDNA DKFZp434M162 (from
Homo sapiens mRNA; cDNA DKFZp586H201 (from
Homo sapiens mRNA; cDNA DKFZp451N147 (from
Recent technical developments have now facilitated the analysis of large numbers of genes by means of the use of high density microarrays or “chips”. Each location on such a chip contains a sequence related to a specific sequence, such that when a signal (such as a visual color, produced by the use of suitable colored conjugate) is present, it can be readily related to the binding of sequences specific for a particular gene, the identity of which is determined by the position of the signal in the array. Suitable computer programs may then be used to analyze and present (in graphical and/or tabular form) the data extracted from the microarray signals. In addition to providing information relating to the expression of specific genes, high density microarrays may also be used to generate “fingerprints” which are characteristic of, for example, a particular disease, treatment response or (as in the case of the invention disclosed herein) prognostic group. The fingerprint thus obtained may be subjected to analysis by any of a number of statistical techniques (including cluster analysis, as described in the illustrative example, hereinbelow), in order to assign said fingerprint to a discrete results group. The results group may be one of a binary pair (such as the good prognosis/poor prognosis pair of the present invention), or it may be one of a more complex series of groups (such as in the case of the differential diagnosis of several pathological possibilities.)
Suitable high density microarrays may either be purchased “off-the-shelf”, pre-loaded with an array of oligonucleotide sequences (for example the Genechip Human Genome arrays produced by Affymetrix, Santa Clara, Calif., USA), or alternatively may be custom-produced such that they bear a subset of the total genome, wherein said subset is relevant for the desired diagnostic, prognostic or drug discovery application of the microarray. Many different materials and techniques may be used in the construction of high density microarrays, the details of which appear in many publications including U.S. Pat. No. 6,344,316, which is in its entirety incorporated herein by reference.
The techniques used to obtain, purify and hybridize RNA and other nucleic acids are varied and well known to all skilled artisans in the field. Details of many such suitable techniques are to be found in standard reference works such as the book “Molecular cloning: a laboratory manual” by Sambrook, J., Fritsch, E. F. & Maniatis, T., Cold Spring Harbor, N.Y., 2nd ed., 1989 (and all later editions), which is incorporated herein by reference in its entirety.
In addition, Methods of isolating total mRNA are described in detail in Chapter 3 of Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization with Nucleic Acid Probes, Part I. Theory and Nucleic Acid Preparation, P. Tijssen, ed. Elsevier, N.Y. (1993). More specific information related to the use of polymerase chain reaction (PCR) techniques may be gleaned from “Innis et al. eds., PCR Protocols: A guide to method and applications”, which is incorporated herein by reference.
Following isolation of the nucleic acids sequences and their purification and hybridization to a suitable high density chip, binding is determined by means of a suitable detection method. In a preferred embodiment, the hybridized nucleic acids are detected by detecting one or more labels attached to the sample nucleic acids. The labels may be incorporated by any of a number of means well known to those of skill in the art. Labels may be introduced either during the course of the synthesis of the nucleic acid sequences (e.g. during a PCR reaction) or as a discrete post-synthetic step. Detectable labels suitable for use in the present invention include any composition detectable by spectroscopic, photochemical, biochemical, immunochemical, electrical, optical or chemical means. Particularly preferred are labels such as biotin for staining with labeled streptavidin conjugate, magnetic beads (e.g., Dynabeads™), fluorescent dyes (e.g., fluorescein, texas red, rhodamine, green fluorescent protein, and the like (obtainable from Molecular Probes, Eugene, Oreg., USA). However, other label types, including radiolabels and enzymes may also be usefully employed.
Several different types of microarray may be used or produced in order to work the present invention. Thus, a variety of different substrate types, including (but not limited to) metal oxides, nylon, ceramic material and glasses may be used to construct the microarray. In a commonly-used configuration, the microarray is constructed such it has a surface area less than 6.25 cm2, preferably in the range of about 1.6 cm2 to 6.25 cm2. Details of the construction of microarrays suitable for use in the present invention are now well known in the art, and may be obtained from a variety of publications including the aforementioned U.S. Pat. No. 6,344,316, U.S. Pat. No. 6,232,068 and U.S. Pat. No. 5,510,270, all of which are incorporated herein in their entirety.
The following example is provided for illustrative purposes and in order to more particularly explain and describe the present invention. The present invention, however, is not limited to the particular embodiments disclosed in the example.
Fourteen primary tumor specimens and six metastases were obtained from 18 ES patients with non-metastatic disease. In the case of one patient, both primary and recurrent tumors were analyzed (SA37 and SA43), and two metastases were taken from another patient, six years apart (SA45 and SA46). All patients were admitted to the Pediatric Hematology Oncology Department at Schneider Children's Medical Center, Petach Tikva, Israel. Informed consent was obtained from the patients or their guardians, and the local and National Ethics Committees approved the research project. All patients were treated with a combination of aggressive chemotherapy, radiotherapy and surgery. Median age at diagnosis was 15 years (range 7-27). Five patients were females and 13 were males. Response to therapy was defined by histopathological response and assessed by percentage of tumor necrosis at the time of surgery (limb salvage procedure) following neoadjuvant chemotherapy and radiotherapy. Median follow up was 72.5 months (range 7-171). Tumors were snap-frozen in liquid nitrogen immediately after surgery and stored at −80° C. until use.
Ten μg of total RNA was extracted from each tumor using Tri Reagent (Molecular Research Center, Inc. Cincinnati, Ohio). Double stranded cDNA was generated from 10 ug of total RNA using the SuperScript Choice System from Gibco Brl (Rockville, Md., USA), using an oligo(dT)24 primer containing a T7 promoter site at the 3′ end (Genset, La Jolla, Calif.). cDNAs were purified via a phenol-chloroform extraction followed by an ethanol precipitation. Purified cDNA was used as template for In vitro transcription (IVT), which was performed with T7 RNA polymerase and biotin-labeled ribonucleotides, using the ENZO BioArray High Yield RNA Transcript Labeling Kit (Enzo Diagnostics, New York, N.Y.). Labeled in vitro transcripts were purified over RNeasy mini columns (Qiagen, Valencia, Calif.) according to manufacturer's instructions. The labeled cRNA was fragmented at 94° C. for 35 min in fragmentation buffer (40 mM Tris-acetate, pH 8.1/100 mM potassium acetate, 30 mM magnesium acetate), and a hybridization mix was generated by addition of herring sperm DNA (0.1 mg/ml), acetylated BSA (0.5 mg/ml, Invitrogen), sodium chloride (1 M), Tris-acetate (10 mM), and Tween-20 (0.0001%). A mixture of four control bacterial and phage cRNA (1.5 pM BioB, 5 pM BioC, 25 pM BioD, and 100 pM Cre) was included to serve as an internal control for hybridization efficiency.
Aliquots of each sample (12 μg cRNA in 200 μl hybridization mix) were hybridized to a Genechip Human Genome U95Av2 array (Affymetrix, Santa Clara, Calif., USA). After hybridization, each array was washed according to procedures developed by the manufacturer (Affymetrix), and stained with streptavidin-phycoerythrin conjugate (Molecular Probes, Eugene, Oreg.). The hybridization signal was amplified by using biotinylated anti-streptavidin antibodies (Vector Laboratories, Burlingame, Calif.), followed by restaining with streptavidin phycoerythrin. Arrays were scanned by the GeneArray scanner G2500A (Hewlett Packard, Palo Alto, Calif.), and scanned images were visually inspected for hybridization imperfections. Arrays were analyzed using Genechip 4.1 software (Affymetrix). The expression value for each gene was determined by calculating the average differences of the probe pairs in use for that gene.
Two samples were analyzed in duplicate and results were reproducible.
The microarray results were analyzed using the GeneSpring Software®. Normalization was performed by setting expression values lower than zero to zero and than each measurement was divided by the median of all measurements in that sample.
In order to filter out genes that are not expressed in any of the groups, Affymetrix absolute call (MAS 4.0: P, M—expressed genes, A—not expressed) was used. Genes that were expressed in one group were defined as genes expressed in at least 3 samples.
A Student's t-test was applied for each gene, and genes with an adjusted P-value less then 0.01 were selected as differentially expressed genes. P-values were corrected to reduce false positive using Benjamini and Hochberg False Discovery Rate (Benjamini, Y. et al. J. Roy. Stat. Soc. B., 57, 289-300 (1995)].
Divisive hierarchical clustering [Everitt, B. S. Cluster analysis. 3rd edition, 62-65 (Arnold, London, 1993)) was performed as described by Eiesen et al. [Eisen, M. B. et al. Proc. Natl. Acad. Sci. USA 95, 14863-14868 (1998], using centered correlation as the measurement distance.
Kaplan-Meier progression free survival analysis, using the log rank test, was performed in order to correlate the microarray classification results with patients' clinical outcome.
The microarray derived expression data was evaluated for the cadherin-11 and MTA1 genes using quantitative PCR by the LightCycler system (Roche Diagnostics, Manheim, Germany). cDNA was prepared using the Reverse Transcription System (Promega Corporation, Madison, Wis.) and purified with GFX PCR DNA and Gel. Band Purification kit (Amersham Biosciences, Piscataway, N.J.). 5 μl was amplified in a 20 μl reaction containing 4 mM MgCL2, 5 μM of each primer and LightCycler—FastStart DNA Master SYBR Green I mix (Roche Diagnostics).
Cadherin-11 primers: sense 5′-AGAGGCCTACATTCTGAACG-3′ and
antisense 5′-TTCTTTCTTTTGCCTTCTCAGG-3′. MTA1 primers:
sense 5′-AGCTACGAGCAGCACAACGGGGT-3′ and
antisense 5′-CACGCTTGGTTTCCGAGGAT-3′.
All examinations were performed in duplicate and data analysis was done using the LightCycler Software.
The study included 14 tumor samples from localized ES patients. The gene expression profile of 7 tumors from patients who had progressed between 5 months up to 5 years from diagnosis (defined as High Risk—HR) was compared with 7 tumors from patients who were disease free for a long period of follow up (median 92 months; range 66-171) (defined as Low Risk—LR).
In brief, RNA was isolated from each tumor and hybridized to Affymetrix oligonucleotide high-density arrays U95Av2. A subset of genes that distinguish between the two groups (HR and LR) by two steps was identified. Firstly, 8098 genes that were expressed in one of the groups, in at least 3 samples, were selected. Subsequently, 818 genes differentially expressed in either the HR or the LR groups (t-test; P<0.01) were studied. These 818 most significant genes are listed in Table 1, hereinabove.
In order to control false positive results as a consequence of multiple comparisons, the P values were adjusted using the False Discovery Rate (FDR) method [Everitt, B. S. Cluster analysis. 3rd edition, 62-65 (Arnold, London, Benjamin, Y. et al., J. Roy. Stat. Soc. B, 57, 289-300 (1995)].
Using hierarchical clustering, based on the 818 genes, for prognosis profile, two distinct clusters could be determined: poor and good prognosis signatures (
Kaplan-Meier life table analysis indicated that the patients predicted to have a good prognosis signature had a significantly improved progression free survival (PFS) compared with those predicted to have a poor prognosis signature (
Additionally, the genes were reordered into 2 major clusters that were divided into 6 sub-clusters, by performing hierarchical clustering of all signature genes (
Two genes that were significantly over expressed in the poor prognosis signature group (p<0.01) are of particular interest; both are associated with invasion and metastasis. The first one is cadherin11 (OB-cadherin), a homophilic calcium-dependent cell adhesion molecule, and the second is MTA1, tumor metastasis-associated gene. Cadherins modulate calcium ion-dependent cell-cell adhesion and are important in cell aggregation, migration and sorting. Defective cell-cell and cell-matrix adhesion are among the hallmarks of cancer. Disruption of the cadherin-catenin complex has been demonstrated in carcinomas arising in several tissues including prostate, gastric and breast carcinomas, and has been correlated with various pathologic and clinical features, such as tumor differentiation, proliferation and a poor patient prognosis.
The MTA1 gene is a novel, highly conserved gene that encodes a nuclear protein product. Examination of the MTA1 protein suggests that it is a histone deacetylase and may serve multiple functions in cellular signaling, chromosome remodeling and transcription processes that are important in the progression, invasion and growth of metastatic cells. The gene has been found to be over-expressed in a variety of human cell lines (breast, ovarian, lung, gastric and colorectal) and cancerous tissues (breast, esophageal, colorectal, gastric and pancreatic cancer).
To validate the microarray data, these two over-expressed genes were analyzed in further detail using reverse transcriptase—quantitative Real Time PCR (RQ-PCR). Microarray-based expression and RQ-PCR based expression data correlated significantly (
Six metastases from localized patients who progressed were further tested, using the unsupervised learning methodology, whether the poor and good prognosis signature set of genes can classify metastatic tissues to one of the prognostic groups, or as a distinct group.
While specific embodiments of the invention have been described for the purpose of illustration, it will be understood that the invention may be carried out in practice by skilled persons with many modifications, variations and adaptations, without departing from its spirit or exceeding the scope of the claims.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/IL04/00578 | 6/30/2004 | WO | 00 | 4/23/2007 |
| Number | Date | Country | |
|---|---|---|---|
| 60483626 | Jul 2003 | US |
