Gene expression markers for colorectal cancer prognosis

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DESCRIPTION

Gene expression markers for colorectal cancer prognosis

5 Field of the Invention

The present invention provides a BGN, whose expression levels are useful for predicting the outcome of colorectal cancer.

Description of the related technique

Colorectal cancer is the number two cause of cancer-related death in the United States and the European Union, representing 10% of all cancer-related deaths. Although colon cancer and cancer may represent a disease identical or similar to the molecular level, surgery for rectal cancer is

fifteen complicated by anatomical issues. Possibly for this reason, the local recurrence rate for rectal cancer is significantly higher than for colon cancer, and therefore the treatment approach is significantly different. Approximately 100,000 new cases of colon cancer are diagnosed each year in the United States, with approximately 65% ​​of these diagnosed as stage II / III colorectal cancer as discussed below.

Refinement of a diagnosis of colorectal cancer involves assessing the state of cancer progression using conventional classification criteria. Two classification systems in colorectal cancer have been widely used, the modified Astler-Coller or Duke staging system (AD stages) (Astler VB, Coller FA., Ann Surg 1954; 139: 846-52), and more recently the TNM staging (stages I-IV) developed by the American

25 Joint Committee on Cancer (AJCC Cancer Staging Manual, 6th edition, Springer-Verlag, New York, 2002). Both systems apply measures of the spread of the primary tumor through the layers of the wall of the rectum or colon to adjacent organs, lymph nodes, and distant sites to assess tumor progression. Estimates of the risk of recurrence and treatment decisions in colon cancer are currently based primarily on the stage of the tumor.

There are approximately 33,000 newly diagnosed stage II colorectal cancers each year in the United States. Almost all of these patients are treated by surgical resection of the tumor and, in addition, approximately 40% are currently treated with 5-fluorouracil-based chemotherapy (5-FU). The decision of whether to administer adjuvant chemotherapy is not simple. The five-year survival rate for patients with colon cancer

35 Stage II treated with surgery alone is approximately 80%. Conventional adjuvant treatment with 5-FU + leucovorin (folinic acid) demonstrates an absolute benefit of only 2-4% in this population and shows significant toxicity, including a toxic chemotherapy death rate of up to 1%. Therefore, a large number of patients receive toxic therapy from which only a few benefit.

A test that can produce a prognosis after surgery in patients with stage II colorectal cancer would be of great benefit to guide treatment decisions for these patients.

The benefit of chemotherapy in stage III colon cancer is more evident than in stage II. A large proportion of the 31,000 patients who are diagnosed with stage III colon cancer annually receive

Four. Five adjuvant chemotherapy based on 5-FU, and the absolute benefit of 5-FU + leucovorin in this environment is around 18-24%, depending on the particular regimen used. The current reference chemotherapeutic treatment for patients with stage III colon cancer (5-FU + leucovorin or 5-FU + leucovorin + oxaliplatin) is moderately effective, achieving an improvement in the 5-year survival rate of approximately 50 % (surgery alone) up to approximately 65% ​​(5-FU + leucovorin) or 70% (5-FU + leucovorin + oxaliplatin). Treatment with 5-FU + leucovorin alone or in combination with oxaliplatin is accompanied by a range of adverse side effects, including toxic death in approximately 1% of treated patients. In addition, the three-year survival rate for patients with stage III colon cancer treated with surgery alone is approximately 47% and it has not been established whether there is a subset of stage III patients for whom the risk of recurrence is similar to that observed for stage II patients.

55 A test that quantifies the risk of recurrence based on molecular markers instead of tumor stage would only be useful to identify a subset of stage III patients who may not require adjuvant therapy to achieve acceptable outcomes.

Staging of rectal tumors is carried out based on similar criteria as for the staging of colon tumors, although there are some differences that result for example from differences in the arrangement of draining lymph nodes. As a result, stage II / III rectal tumors support a reasonable correlation with stage II / III colon tumors in terms of their progression status. As indicated above, the rate of local recurrence and other aspects of the prognosis differ between rectal cancer and colon cancer, 65 and these differences may arise from difficulties in achieving total resection of rectal tumors. However, there is no convincing evidence that there is a difference between colon cancer and rectal cancer in

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as for the molecular characteristics of the respective tumors. Prognostic tests for rectal cancer would have similar utility in nature as described for prognostic tests for colon cancer and the same prognostic markers could be applied to both types of cancer.

5 In addition, there is a clear need for safer and more effective drugs for the treatment of colon cancer. Current chemotherapy for colon cancer is based on the relatively rudimentary approach of administering drugs that generally interfere with the proliferation of dividing cells. Recent clinical studies have demonstrated the feasibility of developing improved drugs based on a detailed molecular understanding of particular types and subtypes of cancer. For example, the HER2 gene (ERBB2) is amplified and the HER2 protein is overexpressed in a subset of breast cancers; HERCEPTIN® (Genentech, Inc.), a drug selected to select as the HER2 target, is indicated only for patients who have a higher than normal HER2 copy number as demonstrated by fluorescent in situ hybridization (FISH) or a high level of HER2 expression as demonstrated by immunohistochemistry. Genes whose expression is associated with the clinical outcome in human cancer patients are a valuable resource for the selection of targets for

fifteen the examination of pharmacological compounds and additional drug development activities.

Molecularly directed drugs, such as HERCEPTIN® (Genentech, Inc.), can be developed and marketed in conjunction with a diagnostic test that can identify patients who are likely to benefit from the drug; One aspect of such a test is the identification of patients who are likely to have a positive outcome without any treatment other than surgery alone. For example, 80% of patients with stage II colon cancer survive five years or more when treated with surgery alone. Gene markers that identify patients who are more likely to be among the 20% whose cancer will experience recurrence without further treatment are useful in drug development, for example in the selection of patients for inclusion in a clinical trial.

25

Summary of the invention

According to a first aspect of the present invention, a method of predicting the clinical outcome is provided for a human subject who has been diagnosed with colorectal cancer after surgical resection of the cancer as specified in claim 1.

The clinical outcome of the method of the invention can be expressed, for example, in terms of recurrence free interval (ILR), overall survival (SG), disease free survival (SLE), or distance free recurrence interval (ILRD).

35 In one embodiment, the cancer is Duke B (stage II) or Duke C (stage III) colorectal cancer.

For all aspects of the method of the invention, the determination of the level of expression can be, for example, by a method of obtaining the gene expression profile. The method of obtaining the gene expression profile can be, for example, a PCR-based method.

For all aspects of the invention, expression levels can be normalized in relation to the expression levels of one or more reference genes, or their expression products.

Four. Five For all aspects of the invention, the method may further comprise the step of creating a report that summarizes said prediction.

It is contemplated that for each increase in an increase in the level of one or more predictive RNA transcripts or their expression products, it is identified that the patient shows an incremental increase in the clinical outcome.

The determination of expression levels can occur more than once. The determination of expression levels may occur before the patient undergoes any therapy after surgical resection.

According to a second aspect of the present invention, a method of determining whether a subject is provided

55 Human who has been diagnosed with colorectal cancer should undergo additional therapy after surgical resection of the cancer as specified in claim 9.

It is contemplated that if the probability of positive clinical outcome is predicted to decrease, said patient undergoes additional therapy after said surgical removal. It is further contemplated that the therapy is chemotherapy and / or radiotherapy.

Brief description of the drawings

Figure 1 shows a dendrogram representing the grouping of the expression of 142 genes that were

65 statistically significant related to the recurrence-free interval (tables 1.2A and 1.2B) in the analysis of proportional Cox risks of a variable. Clustering analysis used the method of

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average amalgamation of unweighted peer groups and 1 -r Pearson as a measure of distance. The identities of particular genes in groups of interest are indicated along the x-axis.

Detailed description of the preferred embodiment

5

A. DEFINITIONS

Unless otherwise defined, the technical and scientific terms used herein have the same meaning commonly understood by a person skilled in the art to which this invention pertains. Singleton et al., Dictionary of Microbiology and Molecular Biology 2nd ed., J. Wiley & Sons (New York, NY 1994), and March, Advanced Organic Chemistry Reactions, Mechanisms and Structure 4th ed., John Wiley & Sons (New York, NY 1992), provide a person skilled in the art with a general guide for many of the terms used in this application.

fifteen One skilled in the art will recognize many methods and materials similar or equivalent to those described herein, which can be used in the practice of the present invention.

In fact, the present invention is not limited in any way to the methods and materials described but is limited by the appended claims. For the purposes of the present invention, the following terms are defined below.

The term "tumor", as used herein, refers to any neoplastic cell growth and proliferation, either malignant or benign, and any precancerous and cancerous cell or tissue.

25 The terms "cancer" and "cancerous" refer to, or describe the, physiological state in mammals that is normally characterized by unregulated cell growth. Examples of cancer include, but are not limited to, breast cancer, ovarian cancer, colon cancer, lung cancer, prostate cancer, hepatocellular cancer, gastric cancer, pancreatic cancer, cervical cancer, liver cancer, Bladder cancer, urinary tract cancer, thyroid cancer, kidney cancer, carcinoma, melanoma and brain cancer.

The "pathology" of cancer includes all phenomena that compromise the patient's well-being. This includes, without limitation, abnormal or uncontrollable cell growth, metastasis, interference with the normal functioning of neighboring cells, release of cytokines or other secretory products at abnormal levels, suppression or aggravation of the inflammatory or immune response, neoplasia, premalignant tumor, tumor malignant tissue invasion or

35 surrounding or distant organs, such as lymph nodes, etc.

The term "colorectal cancer" is used in the broadest sense and refers to (1) all stages and all forms of cancer that arise from epithelial cells of the large and / or rectum intestine and / or (2) all stages and all forms of cancer that affect the lining of the large intestine and / or rectum. In staging systems used for the classification of colorectal cancer, the colon and rectum are treated as an organ.

According to the tumor staging system, ganglion, metastasis (TNM) of the American Joint Committee on Cancer (AJCC) (Greene et al. (Eds.), AJCC Cancer Staging Manual. 6th Ed. New York, NY: Springer; 2002) , the various stages of colorectal cancer are defined as follows:

Four. Five Tumor: T1: the tumor invades the submucosa; T2: the tumor invades the muscular layer itself; T3: the tumor invades through the muscular layer itself towards the subserosa, or towards the pericholic or perirectal tissues; T4: the tumor directly invades other organs or structure, and / or perforates.

Ganglion: N0: no regional lymph node metastasis; N1: metastasis in 1 to 3 regional lymph nodes; N2: metastasis in 4 or more regional lymph nodes.

Metastasis: M0: no distant metastasis; M1: distant metastasis present.

55 Stadium groupings: Stage I: T1 N0 M0; T2 N0 M0; Stage II: T3 N0 M0; T4 N0 M0; Stage III: any T, N1-2; M0; Stage IV: any T, any N, M1.

According to the modified Duke staging system, the various stages of colorectal cancer are defined as follows:

Stage A: The tumor penetrates the mucosa of the intestinal wall but not beyond. Stage B: the tumor penetrates into and through the muscular layer of the intestinal wall; stage C: the tumor penetrates into, but not through, the muscular layer of the intestinal wall, there is pathological evidence of colorectal cancer in the lymph nodes; or the tumor penetrates into and through the muscular layer of the intestinal wall, there is pathological evidence of cancer in

65 lymph nodes; stage D: the tumor has spread beyond the confines of the lymph nodes, to other organs, such as the liver, lung or bone.

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The prognostic factors are the variables related to the natural history of colorectal cancer, which influence recurrence rates and the outcome of patients once they have developed colorectal cancer. Clinical parameters that have been associated with a worse prognosis include, for example, node involvement

5 lymphatic, and high grade tumors. Prognostic factors are frequently used to classify patients into subgroups with different initial recurrence risks.

The term "prognosis" is used herein to refer to the prediction of the probability of death or progression attributable to cancer, including recurrence, metastatic spread and drug resistance, of a neoplastic disease, such as colon cancer.

The term "prediction" is used herein to refer to the probability that a patient has a particular clinical outcome, either positive or negative, after surgical removal of the primary tumor. The predictive methods of the present invention can be used clinically to make treatment decisions.

fifteen choosing the most appropriate treatment modalities for any particular patient. The predictive methods of the present invention are valuable tools in predicting whether a patient is likely to respond favorably to a treatment regimen, such as surgical intervention. The prediction may include prognostic factors.

The term "positive clinical outcome" means an improvement in any measure of the patient's condition, including measures commonly used in the art, such as an increase in the duration of the recurrence-free interval (ILR), an increase in survival time global (OS), an increase in disease-free survival time (SLE), an increase in the duration of the free recurrence-free interval (ILRD), and the like. An increase in the probability of positive clinical outcome corresponds to a decrease in the probability of

25 cancer recurrence

The term "risk classification" means the level of risk or the prediction that a subject experiences a particular clinical outcome. A subject can be classified into a risk group or classified at a risk level based on the predictive methods of the present invention. A "risk group" is a group of subjects or individuals with a similar level of risk for a particular clinical outcome.

The term "long-term survival" is used herein to refer to survival for at least 3 years, more preferably for at least 5 years.

35 The term "recurrence free interval (ILR)" is used herein to refer to the time in years until the first recurrence of colon cancer censoring for a second primary cancer as the first event or death without evidence of recurrence.

The term "overall survival (OS)" is used herein to refer to the time in years from surgery to death from any cause.

The term "disease-free survival (SLE)" is used herein to refer to the time in years until recurrence of colon cancer or death from any cause.

Four. Five The term "distance-free recurrence interval (ILRD)" is used herein to refer to the time (in years) from surgery to the first anatomically distant cancer recurrence.

The calculation of the measures listed above in practice may vary from study to study depending on the definition of events that are going to be censored or not considered.

The term "microalignment" refers to an ordered arrangement of hybridizable alignment elements, preferably polynucleotide probes, on a substrate.

The term "polynucleotide," when used in the singular or plural, generally refers to any

55 polyribonucleotide or polydeoxyribonucleotide, which can be RNA or unmodified DNA or modified RNA or DNA. Thus, for example, polynucleotides as defined herein include, without limitation, single and double stranded DNA, DNA that includes single and double stranded regions, single and double stranded RNA, and RNA that includes single and double stranded regions, hybrid molecules which comprise DNA and RNA that can be single stranded or, more usually, double stranded or include single and double stranded regions. In addition, the term "polynucleotide" as used herein refers to tricatenary regions that comprise RNA.

or DNA or both RNA and DNA. The strands in such regions may be of the same molecule or of different molecules. Regions may include all of one or more of the molecules, but more usually they involve only a region of some of the molecules. One of the molecules of a triple helix region is often an oligonucleotide. The term "polynucleotide" specifically includes cDNA. The term includes AND (including

65 CDNA) and RNA containing one or more modified bases. Therefore, DNA or RNA with major structures modified to achieve stability or for other reasons are "polynucleotides" as the term is provided in the

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present document In addition, DNA or RNA comprising uncommon bases, such as inosine, are included.

or modified bases, such as tritiated bases, within the term "polynucleotides" as defined herein. In general, the term "polynucleotide" encompasses all chemically, enzymatically and / or metabolically modified forms of unmodified polynucleotides, as well as the chemical forms of DNA and RNA.

5 virus and cell characteristics, including simple and complex cells.

The term "oligonucleotide" refers to a relatively short polynucleotide, which includes, without limitation, single stranded deoxyribonucleotides, single or double stranded ribonucleotides, RNA hybrids: double stranded DNA and DNA. Oligonucleotides, such as single-stranded DNA probe oligonucleotides, are often synthesized by chemical methods, for example using automated oligonucleotide synthesizers that are commercially available. However, oligonucleotides can be prepared by a variety of other methods, including recombinant DNA mediated techniques in vitro and by expression of DNA in cells and organisms.

fifteen The terms "differentially expressed gene", "differential gene expression" and its synonyms, which are used interchangeably, refer to a gene whose expression is activated at a higher or lower level in a subject suffering from a disease, specifically cancer, such as colon cancer, in relation to its expression in a normal or control subject. The terms also include genes whose expression is activated at a higher or lower level at different stages of the same disease. It is also understood that a differentially expressed gene can either be activated or inhibited at the level of nucleic acid or protein level, or it can be subjected to alternative splicing to result in a different polypeptide product. Such differences can be evidenced by a change in mRNA levels, surface expression, secretion or other distribution of a polypeptide, for example. Differential gene expression may include a comparison of the expression between two or more genes or their gene products, or a comparison of the reasons for the expression between two or more genes or

25 their gene products, or even a comparison of two products processed differently from the same gene, that differ between normal subjects and subjects suffering from a disease, specifically cancer, or between different stages of the same disease. Differential expression includes both quantitative and qualitative differences in the pattern of cellular or temporal expression in a gene or its expression products between, for example, diseased and normal cells, or between cells that have experienced different disease events or stages. of disease For the purpose of this invention, "differential gene expression" is considered to be present when there is a difference of at least about twice, preferably at least about four times; more preferably at least about six times, most preferably at least about ten times between the expression of a given gene in normal and diseased subjects, or at various stages of disease development in a diseased subject.

35 The term "overexpression" with respect to an RNA transcript is used to refer to the level of the transcript determined by normalization to the reference mRNA level, which could be all transcripts measured in the sample or a particular mRNA reference set.

The term "gene amplification" refers to a method by which multiple copies of a gene or gene fragment are formed in a particular cell line or cell. The duplicated region (a stretch of amplified DNA) is often referred to as "amplicon." Usually, the amount of messenger RNA (mRNA) produced, that is, the level of gene expression, also increases in the proportion of the number of copies produced of the particular expressed gene.

Four. Five The "stringency" of the hybridization reactions can easily be determined by a person skilled in the art, and is generally an empirical calculation dependent on the length of the probe, washing temperature and salt concentration. In general, longer probes require higher temperatures for proper mating, while shorter probes require lower temperatures. Hybridization generally depends on the ability of denatured DNA to mate again when complementary strands are present in an environment below their melting temperature. The higher the degree of homology desired between the probe and the hybridizable sequence, the higher the relative temperature that can be used. As a result, it follows that higher relative temperatures would tend to make the reaction conditions more stringent, while lower temperatures would make them less stringent. For additional details and explanation

55 for the rigor of hybridization reactions, see Ausubel et al., Current Protocols in Molecular Biology. Wiley Interscience Publishers, (1995).

"Rigorous conditions" or "high stringency conditions", as defined herein, typically: (1) employ low ionic strength and high temperature for washing, for example 0.015 M sodium chloride / sodium citrate 0, 0015 M / 0.1% sodium dodecyl sulfate at 50 ° C; (2) employ a denaturation agent during hybridization, such as formamide, for example, 50% formamide (v / v) in 0.1% bovine serum albumin / 0.1% Ficoll / 0.1% polyvinylpyrrolidone % / 50 mM sodium phosphate buffer at pH 6.5 with 750 mM sodium chloride, 75 mM sodium citrate at 42 ° C; or (3) employ 50% formamide, 5 x SSC (0.75 M NaCl, 0.075 M sodium citrate), 50 mM sodium phosphate (pH 6.8), 0.1% sodium pyrophosphate, 5 x Denhardt solution, DNA of

65 Sonic salmon sperm (50 µg / ml), 0.1% SDS and 10% dextran sulfate at 42 ° C, with washes at 42 ° C in 0.2 x SSC (sodium chloride / sodium citrate) and 50% formamide % at 55 ° C, followed by a high stringency wash

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consisting of 0.1 x SSC containing EDTA at 55 ° C.

"Moderately stringent conditions" can be identified as described by Sambrook et al., Molecular Cloning: A Laboratory Manual, New York: Cold Spring Harbor Press, 1989, and include the use of dissolution of

5 washing and hybridization conditions (e.g. temperature, ionic strength and% SDS) less stringent than those described above. An example of moderately stringent conditions is overnight incubation at 37 ° C in a solution comprising: 20% formamide, 5 x SSC (150 mM NaCl, 15 mM trisodium citrate), 50 mM sodium phosphate (pH 7.6 ), 5 x Denhardt solution, 10% dextran sulfate and denatured fragmented salmon sperm DNA 20 mg / ml, followed by washing the filters in 1 x SSC at approximately 3750 ° C. The expert will recognize how to adjust the temperature, ionic strength, etc. as necessary to adapt factors such as probe length and the like.

In the context of the present invention, the reference to "at least one," "at least two," "at least five," etc. of the genes listed in any particular set of genes means any one or any and all

fifteen combinations of the genes listed.

The term "ganglion negative" cancer, such as "ganglion negative" colon cancer, is used herein to refer to cancer that has not spread to lymph nodes.

The terms "splicing" and "RNA splicing" are used interchangeably and refer to the processing of RNA that removes introns and binds exons to produce mature mRNA with continuous coding sequence that is transferred to the cytoplasm of a eukaryotic cell .

In theory, the term "exon" refers to any segment of an interrupted gene that is represented in the

25 mature RNA product (B. Lewin. Genes IV Cell Press, Cambridge Mass. 1990). In theory, the term "intron" refers to any segment of DNA that is transcribed but removed from the transcript by cutting and splicing together the exons on either side of it. Operationally, exon sequences are produced in the mRNA sequence of a gene as defined by the numbers of Ref. Seq ID. Operationally, intron sequences are the intermediate sequences within the genomic DNA of a gene, in between the exon sequences and which have consensus splicing sequences GT and AG at their 5 'and 3' ends.

The term "expression grouping" is used herein to refer to a group of genes that demonstrate similar expression patterns when studied within samples of a defined set of patients. As used herein, genes within an expression cluster show

35 Similar expression patterns when studied within samples of patients with colon and / or rectal cancer in stage II and / or stage III.

B.1 GENERAL DESCRIPTION OF THE INVENTION

The practice of the present invention will employ, unless otherwise indicated, conventional techniques of molecular biology (including recombinant techniques), microbiology, cell biology and biochemistry, which are within the skill of the art. Such techniques are fully explained in the literature, such as, "Molecular Cloning: A Laboratory Manual", 2nd edition (Sambrook et al., 1989); "Oligonucleotide Synthesis" (MJ Gait, ed., 1984); “Animal Cell Culture” (RI Freshney, ed., 1987); "Methods in Enzymology" (Academic Press, Inc.);

Four. Five "Handbook of Experimental Immunology", 4th edition (DM Weir & CC Blackwell, eds., Blackwell Science Inc., 1987); "Gen Transfer Vectors for Mammalian Cells" (JM Miller & MP Calos, eds., 1987); "Current Protocols in Molecular Biology" (FM Ausubel et al., Eds., 1987); and "PCR: The Polymerase Chain Reaction", (Mullis et al., eds., 1994).

Based on tests of differential expression of RNA transcripts in normal and cancer cells, the present description provides prognostic gene markers for colorectal cancer. Therefore, in a particular aspect, the present description provides prognostic gene markers of stage II and / or stage III colorectal cancer, including markers that are specifically prognosis for the outcome of either stage II or stage III disease. and those with prognostic value in both stages,

55 reflecting underlying differences in tumor cells in both stages and / or in the degree of tumor progression. The prognostic markers and associated information provided by this description allow physicians to make smarter treatment decisions, and adapt the treatment of colorectal cancer to the needs of individual patients, thereby maximizing the benefit of treatment and minimizing the exposure of patients to unnecessary treatments, They do not provide any significant benefits and often carry serious risks due to toxic side effects.

Alterations in the normal functioning of various physiological processes, including proliferation, apoptosis, angiogenesis and invasion, have been implicated in cancer pathology. The relative contribution of dysfunctions in particular physiological processes to the pathology of particular types of cancer is not well characterized. 65 Any physiological process integrates the contributions of numerous gene products expressed by the various cells involved in the process. For example, invasion by tumor cells of adjacent normal tissue

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and the intravasation of the tumor cell in the circulatory system are affected by a series of proteins that mediate the various cellular characteristics, including cohesion between tumor cells, adhesion of tumor cells to normal cells and connective tissue, tumor cell capacity to alter its morphology first and then migrate through the surrounding tissues, and tumor cell's ability to degrade

5 surrounding connective tissue structures.

Multiple analyte gene expression tests can measure the level of expression of one or more genes involved in each of several relevant cell component characteristics or physiological processes. In some cases, the predictive power of the test, and therefore its usefulness, can be improved by using the expression values ​​obtained for individual genes to calculate a score that is more highly correlated with the outcome than the expression value of the individual genes. For example, the calculation of a quantitative score (recurrence score) that predicts the probability of recurrence in lymph node-negative breast cancer positive for estrogen receptor is described in the US patent application being processed along with the present (number of publication 20050048542). The equation used to calculate a score of

fifteen Recurrence of this type can group genes in order to maximize the predictive value of the recurrence score. Gene clustering can be done at least in part based on knowledge of its contribution to physiological functions or cellular component characteristics as discussed above. In addition, group formation can facilitate the mathematical weighting of the contribution of various expression values ​​to the recurrence score. The weighting of a group of genes that represent a physiological process or component cell characteristic may reflect the contribution of that process or characteristic to the pathology of the cancer and the clinical outcome. Therefore, in an important aspect, the present description also provides specific groups of the prognostic genes identified herein, which together are more reliable and powerful outcome prediction factors than individual genes or random combinations of the identified genes. .

25 Furthermore, based on the determination of a recurrence score, it may be chosen to distribute patients in subgroups at any particular value of the recurrence score, where all patients with values ​​in a given interval can be classified as belonging to a particular risk group. Therefore, the values ​​chosen will define subgroups of patients with risk respectively higher or lower.

The usefulness of a gene marker in predicting the outcome of colon cancer may not be unique for that marker. A test marker can be substituted for an alternative marker that has an expression pattern that is closely similar to a particular test marker or used in addition thereto and have little impact on the overall predictive utility of the test. The closely similar expression patterns of two genes

35 they may result from the involvement of both genes in a particular process and / or from being under a common regulatory control in colon tumor cells.

The prognostic marker and associated information provided by the present invention that predicts the clinical outcome in cancers of the colon and / or rectum in stage II and / or stage III have utility in the development of drugs for treating cancers of the colon and / or the rectum in stage II and / or stage III.

The prognostic marker and associated information provided by the present invention that predict the clinical outcome in cancers of the colon and / or rectum in stage II and / or stage III are also useful in the examination of patients for inclusion in clinical trials that test the efficacy of pharmacological compounds

Four. Five for the treatment of patients with cancers of the colon and / or rectum in stage II and / or stage III. In particular, the prognostic marker can be used in samples collected from patients in a clinical trial and the test results used in conjunction with the outcomes of patients in order to determine whether patient subgroups are more or less likely to show a response to drug than the whole group or other subgroups.

The prognostic marker and associated information provided by the present invention that predict the clinical outcome in cancers of the colon and / or rectum in stage II and / or stage III are useful as an inclusion criterion for a clinical trial. For example, a patient is more likely to be included in a clinical trial if the test results indicate a higher probability that the patient has a poor clinical outcome if

55 treats with surgery alone and a patient is less likely to be included in a clinical trial if the test results indicate a lower probability that the patient has a bad clinical outcome if treated with surgery alone.

Prognostic markers and associated information can be used to design or produce a reagent that modulates the level or activity of the gene transcript or its expression product. Such reagents may include but are not limited to an antisense RNA, a small inhibitory RNA, a ribozyme, a monoclonal or polyclonal antibody.

In a further aspect, said gene or its transcript, or more particularly, an expression product of said transcript is used in a test (test) to identify a pharmacological compound, wherein said compound

65 Pharmacological is used in the development of a drug to treat cancers of the colon and / or rectum in stage II and / or stage III.

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In various embodiments of the invention, various technological approaches are available for the determination of the levels of expression of the genes disclosed, including, without limitation, RT-PCR, microalignments, serial analysis of gene expression (SAGE) and analysis. of gene expression by signature sequencing

5 massive parallel (MPSS), which will be discussed in detail below. In particular embodiments, the level of gene expression can be determined in relation to various characteristics of gene expression products including exons, introns, protein epitopes and protein activity. In other embodiments, the level of expression of a gene can be deduced from the analysis of the structure of the gene, for example from the analysis of the methylation pattern of the promoter (s) of the gene.

B.2 OBTAINING THE GENE EXPRESSION PROFILE

Methods of obtaining the gene expression profile include methods based on polynucleotide hybridization analysis, methods based on polynucleotide sequencing and proteomic based methods. The

fifteen Most commonly used methods known in the art for quantification of mRNA expression in a sample include Northern blotting and in situ hybridization (Parker & Barnes, Methods in Molecular Biology 106: 247-283 (1999)); RNAse protection assays (Hod, Biotechniques 13: 852-854 (1992)); and polymerase chain reaction with reverse transcription (RT-PCR) (Weis et al., Trends in Genetics 8: 263-264 (1992)). Alternatively, antibodies that can recognize sequence-specific duplexes, including DNA duplexes, RNA duplexes and hybrid DNA-RNA duplexes or DNA-protein duplexes, can be employed. Representative methods for analysis of gene expression based on sequencing include serial analysis of gene expression (SAGE) and analysis of gene expression by parallel sequencing (MPSS).

25 to. PCR with reverse transcriptase (RT-PCR)

Of the techniques listed above, the most sensitive and most flexible quantitative method is RT-PCR, which can be used to compare mRNA levels in various samples. The results can be used to compare gene expression patterns between sets of samples, for example in normal and tumor tissues and in patients with or without drug treatment.

The first stage is mRNA isolation from a target sample. The starting material is normally total RNA isolated from human tumor cell lines or tumors, and the corresponding normal cell lines or tissues, respectively. Therefore, RNA can be isolated from a variety of primary tumors,

35 including tumor cell lines or tumor of the breast, lung, colon, prostate, brain, liver, kidney, pancreas, spleen, thymus, testis, ovary, uterus, etc., with combined DNA from healthy donors. If the source of mRNA is a primary tumor, mRNA can be extracted, for example, from samples of frozen tissue or embedded in archived and fixed paraffin (for example fixed with formalin).

General methods for mRNA extraction are well known in the art and are disclosed in conventional molecular biology textbooks, including Ausubel et al., Current Protocols of Molecular Biology, John Wiley and Sons (1997). Methods for the extraction of RNA from tissues embedded in paraffin are disclosed, for example, in Rupp and Locker, Lab Invest. 56: A67 (1987), and De Andrés et al., BioTechniques 18: 42044 (1995). In particular, RNA isolation can be performed using a purification kit, buffer assembly and

Four. Five Protease from commercial manufacturers, such as Qiagen, according to the manufacturer's instructions. For example, total RNA from cells in culture can be isolated using RNeasy mini-columns from Qiagen. Other commercially available RNA isolation kits include the MasterPure ™ complete RNA and DNA purification kit (EPICENTRE®, Madison, WI), and the paraffin block RNA isolation kit (Ambion, Inc.). Total RNA can be isolated from tissue samples using Stat-60 RNA (Tel-Test). RNA prepared from the tumor can be isolated, for example, by gradient centrifugation of cesium chloride density.

Since RNA cannot serve as a template for PCR, the first step in obtaining the gene expression profile by RT-PCR is the reverse transcription of the RNA template to give cDNA, followed by its exponential amplification in a PCR reaction. The two most commonly used reverse transcriptases are the

55 reverse transcriptase of avian myeloblastosis virus (VMA-RT) and reverse transcriptase of Moloney murine leukemia virus (VLMM-RT). The reverse transcription step is usually primed using specific primers, random hexamers or oligo-dT primers, depending on the circumstances and the objective of obtaining the expression profile. For example, the extracted RNA can be transcribed in reverse using a GeneAmp RNA PCR kit (Perkin Elmer, CA, USA), following the manufacturer's instructions. The derived cDNA can then be used as a template in the subsequent PCR reaction.

Although the PCR step can use a variety of thermostable DNA-dependent DNA polymerases, Taq DNA polymerase is normally employed, which has a 5'-3 'nuclease activity but lacks a 3'-5' endonuclease activity for proofreading. . Thus, TaqMan® PCR normally uses the 5 5 'nuclease activity of Tth or Taq polymerase to hydrolyse a hybridization probe bound to its target amplicon, but any enzyme with equivalent 5' nuclease activity can be used. Two oligonucleotide primers are used to generate a

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typical amplicon of a PCR reaction. A third oligonucleotide, or probe, is designed to detect the nucleotide sequence located between the two PCR primers. The probe cannot be extended by the Taq DNA polymerase enzyme, and is labeled with an indicator fluorescent dye and a quencher fluorescent dye. Any laser induced emission of the indicator dye is extinguished by the extinction dye when the two dyes are located

5 close to each other since they are in the probe. During the amplification reaction, the Taq DNA polymerase enzyme cleaves the probe in a mold dependent manner. The resulting probe fragments dissociate in solution, and the signal of the released indicator dye is free from the extinction effect of the second fluorophore. One molecule of indicator dye is released for each new synthesized molecule, and detection of the non-extinguished indicator dye provides the basis for quantitative interpretation of the data.

TaqMan® RT-PCR can be performed using commercially available equipment, such as, for example, ABI PRISM 7700 ™ Sequence Detection System ™ (Perkin-Elmer-Applied Biosystems, Foster City, CA, USA), or Lightcycler (Roche Molecular Biochemicals, Mannheim, Germany). In a preferred embodiment, the 5 'nuclease process is carried out in a real-time quantitative PCR device such as ABI PRISM 7700 ™ Sequence

fifteen Detection System ™. The system consists of a thermal cycler, a laser, a coupled charging device (CCD), a camera and a computer. The system amplifies samples in a 96-well format in a thermal cycler. During amplification, the laser-induced fluorescent signal is collected in real time through the 96-well fiber optic cables, and is detected in the CCD. The system includes software to operate the instrument and to analyze the data.

The 5 'nuclease assay data is initially expressed as Ct, or the threshold cycle. As discussed above, fluorescence values ​​are recorded during each cycle and represent the amount of product amplified at that point in the amplification reaction. The point at which the fluorescent signal is first recorded as statistically significant is the threshold cycle (Ct).

25 To minimize errors and the effect of sample-to-sample variation, RT-PCR is usually performed using an internal standard. The ideal internal pattern is expressed at a constant level between different tissues, and is not affected by experimental treatment. The most frequently used RNAs to normalize gene expression patterns are mRNAs for the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and -actin maintenance genes.

A more recent variation of the RT-PCR technique is real-time quantitative PCR, which measures the accumulation of PCR product through a double-labeled fluorogenic probe (i.e., TaqMan® probe). The real-time PCR is compatible with both the quantitative competitive PCR, in which an internal competitor is used for each target sequence for normalization, and with the quantitative comparative PCR using a gene of

35 normalization contained within the sample, or a maintenance gene for RT-PCR. For additional details see, for example Held et al., Genome Research 6: 986-994 (1996).

The steps of a representative protocol for obtaining the gene expression profile using fixed tissues, embedded in paraffin as a source of RNA, including mRNA isolation, purification, primer extension and amplification are provided in various published journal articles (for example: TE Godfrey et al. J. Molec. Diagnostics 2: 84-91 (2000); K. Specht et al., Am. J. Pathol. 158: 419-29 (2001)). In summary, a representative procedure begins with the cutting of approximately 10 µm thick sections of samples of tumor tissue embedded in paraffin. Then the RNA is extracted, the proteins and the DNA are removed. After analysis of the RNA concentration, RNA repair and / or amplification steps can be included, if necessary, and

Four. Five reverse transcribes RNA using gene specific promoters followed by RT-PCR.

b. MassARRAY system

In the method of obtaining the mass expression profile based on MassARRAY, developed by Sequenom, Inc. (San Diego, CA) after RNA isolation and reverse transcription, known additions of the cDNA obtained with a synthetic DNA molecule are made ( competitor), which matches the cDNA region selected as the target in all positions; except for a single base, and serves as an internal standard.

The cDNA / competitor mixture is amplified by PCR and subjected to an alkaline phosphatase enzyme treatment of

55 prawn (SAP) after PCR, which results in dephosphorylation of the remaining nucleotides. After inactivation of the alkaline phosphatase, the competitor's PCR products and the cDNA are subjected to primer extension, which generates different mass signals for competitor and cDNA derived PCR products. After purification, these products are dispensed on a chip alignment, which is preloaded with components necessary for analysis with time-of-flight mass spectrometry with matrix-assisted laser desorption-ionization (MALDI-TOF MS). The cDNA present in the reaction is then quantified by analyzing the ratios of the peak areas in the generated mass spectrum. For additional details see, for example, Ding and Cantor, Proc. Natl Acad. Sci. USA 100: 3059-3064 (2003).

c. Other PCR based methods

65 Additional PCR-based techniques include, for example, differential presentation (Liang and Pardee, Science

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257: 967-971 (1992)); amplified fragment length polymorphism (iAFLP) (Kawamoto et al., Genome Res. 12: 1305-1312 (1999)); BeadArray ™ technology (Illumina, San Diego, CA; Oliphant et al., Discovery of Markers for Disease (Biotechniques supplement), June 2002; Ferguson et al., Analytical Chemistry 72: 5618 (2000)); BeadsArray for gene expression detection (BADGE), using the available Luminex100 LabMAP system

5 commercially and multiple color-coded microspheres (Luminex Corp., Austin, TX) in a rapid assay to determine gene expression (Yang et al., Genome Res. 11: 1888-1898 (2001)); and analysis of obtaining the high coverage expression profile (HiCEP) (Fukumura et al., Nucl. Acids. Res. 31 (16) e94 (2003)).

d. Microalignments

Differential gene expression can also be identified, or confirmed, using the microalignment technique. Therefore, the expression profile of genes associated with colon cancer in tumor tissue, either embedded in paraffin or recent, can be measured using micro-alignment technology. In this method, the polynucleotide sequences of interest (including cDNA and oligonucleotides) are plated, or aligned, on a

fifteen microchip substrate The sequences aligned with DNA probes specific to cells or tissues of interest are then hybridized. Just as in the RT-PCR method, the source of mRNA is usually total RNA isolated from human tumors or tumor cell lines, and the corresponding normal cell lines or tissues. Therefore, RNA can be isolated from a variety of primary tumors or tumor cell lines. If the source of mRNA is a primary tumor, mRNA can be extracted, for example, from frozen or embedded tissue samples in archived and fixed paraffin (for example fixed with formalin), which are routinely prepared and practically preserved. daily clinic

In a specific embodiment of the micro-alignment technique, PCR amplified inserts of cDNA clones are applied to a substrate in a dense alignment. Preferably, at least 10,000 nucleotide sequences are applied to the substrate. The microaligned genes, immobilized on the microchip at 10,000 elements each, are suitable for hybridization under stringent conditions. Fluorescently labeled cDNA probes can be generated through the incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest. The labeled cDNA probes applied to the chip hybridize with specificity to each point of DNA in the alignment. After thorough washing to remove probes not specifically bound, the chip is scanned by confocal laser microscopy or by another detection method, such as a CCD camera. The quantification of the hybridization of each aligned element allows the evaluation of the corresponding abundance of mRNA. With double color fluorescence, separate labeled cDNA probes generated from two sources of RNA are aligned in pairs. Therefore, the relative abundance of transcripts is determined simultaneously from the two sources corresponding to each specified gene. The

35 Miniaturized hybridization scale allows a rapid and convenient evaluation of the expression pattern for large numbers of genes. It has been shown that such methods have the sensitivity required to detect rare transcripts, which are expressed at a few copies per cell, and to reproducibly detect differences of at least about twice in expression levels (Schena et al., Proc Natl. Acad. Sci. USA 93 (2): 106-149 (1996)). Microalignment analysis can be performed using commercially available equipment, following the manufacturer's protocols, such as using Affymetrix GenChip technology, or Incyte microalignment technology.

The development of microalignment methods for large-scale analysis of gene expression makes it possible to systematically search for molecular markers of cancer classification and outcome prediction in a

Four. Five variety of tumor types.

and. Serial analysis of gene expression (SAGE)

Serial gene expression analysis (SAGE) is a method that allows the quantitative and simultaneous analysis of a large number of gene transcripts, without the need to provide an individual hybridization probe for each transcript. First, a short sequence tag (approximately 10-14 bp) is generated that contains sufficient information to uniquely identify a transcript, provided the marker is obtained from a unique position within each transcript. Then, many transcripts join together to form long series molecules, which can be sequenced, revealing the identity of the multiple tags

55 simultaneously. The expression pattern of any population of transcripts can be quantitatively assessed by determining the abundance of individual tags and identifying the gene corresponding to each tag. For more details see, for example Velculescu et al., Science 270: 484-487 (1995); and Velculescu et al., Cell 88: 243-51 (1997).

F. Analysis of gene expression by parallel sequencing of massive signatures (MPSS)

This method, described by Brenner et al., Nature Biotechnology 18: 630-634 (2000), is a sequencing approach that combines non-gel based sequencing with in vitro cloning of millions of molds in 5 µm microbeads. separate diameter. First, a library of DNA mold microbeads is constructed by in vitro cloning. This is followed by the assembly of a flat alignment of the microbeads containing molds in a flow cell at a high density (normally greater than 3x106 microbeads / cm2). Are analyzed

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Simultaneously the free ends of the templates cloned into each microbead, using a fluorescence-based signature sequencing method that does not require separation of DNA fragments. It has been shown that this method simultaneously and accurately provides, in a single operation, hundreds of thousands of gene signature sequences from a yeast cDNA library.

5

g. Immunohistochemistry

Immunohistochemical methods are also suitable for detecting expression levels of the prognostic marker of the present invention. Therefore, antibodies or antisera, preferably polyclonal antisera, and most preferably monoclonal antibodies specific for the label are used to detect expression. The antibodies can be detected by direct labeling of the antibodies themselves, for example, with radioactive markers, fluorescent markers, hapten markers such as biotin, or an enzyme such as horseradish peroxidase or alkaline phosphatase. Alternatively, unlabeled primary antibody is used in conjunction with a labeled secondary antibody, comprising antisera, polyclonal antisera or a

fifteen monoclonal antibody specific for the primary antibody. Immunohistochemistry protocols and kits are well known in the art and are commercially available.

h. Proteomics

The term "proteome" is defined as the totality of the proteins present in a sample (for example tissue, organism or cell culture) at a certain point of time. Proteomics includes, among other things, the study of global changes in protein expression in a sample (also called "expression proteomics"). Proteomics normally includes the following steps: (1) separation of individual proteins in a sample by two-dimensional gel electrophoresis (2-D PAGE); (2) identification of individual proteins

25 recovered from the gel, for example by mass spectrometry or N-terminal sequencing and (3) data analysis using bioinformatics. Proteomics methods are valuable complements to other methods of obtaining the gene expression profile, and can be used, alone or in combination with other methods, to detect the prognostic marker products of the present invention.

i. Promoter methylation analysis

Several methods for quantifying RNA transcripts (gene expression analysis) or their protein translation products are discussed herein. The level of gene expression can also be deduced from information regarding the chromatin structure, such as the state of

35 methylation of gene promoters and other regulatory elements and the histone acetylation state.

In particular, the methylation status of a promoter influences the level of expression of the gene regulated by that promoter. Aberrant methylation of promoters of particular genes has been implicated in the regulation of expression, such as for example the silencing of tumor suppressor genes. Therefore, the methylation status of the promoter of a gene can be used as a substitute for the direct quantification of RNA levels.

Several approaches have been devised to measure the methylation status of particular DNA elements, including methylation-specific PCR (Herman JG et al. (1996) Metilation-specific PCR: a novel PCR assay for metilation

Four. Five status of CpG islands. Proc. Natl Acad. Sci. USA. 93, 9821-9826) and bisulfite DNA sequencing (Frommer M. et al. (1992) A genomic sequencing protocol that yields a positive display of 5-methylcytosine residues in individual DNA strands. Proc. Natl Acad. Sci. USA. 89, 1827-1831.). More recently, microalignment based technologies have been used to characterize the promoter's methylation status (Chen CM (2003) Metilation target array for rapid analysis of CpG island hypermetilation in multiple tissue genomes. Am. J. Pathol. 163, 37-45).

j. Gene coexpression

An additional aspect of the description is the identification of gene expression clusters. Gene expression clusters can be identified by analyzing expression data using analysis

55 Statistics known in the art, including pairwise correlation analysis based on Pearson's correlation coefficients (Pearson K. and Lee A. (1902) Biometrika 2, 357).

In one aspect, an expression cluster identified herein includes BGN, CALD1, COL1A1, COL1A2, SPARC, VIM, and other genes that are known to be predominantly synthesized by stromal cells and that are involved in remodeling the extracellular matrix. . This expression grouping is referred to herein as stromal clustering / extracellular matrix remodeling.

In another aspect, an expression cluster identified herein includes ANXA2, KLK6, KLK10, LAMA3, LAMC2, MASPIN, SLPI, and other genes encoding genes secreted by epithelial cells, the majority of which are predominantly secreted by epithelial cells but which can be secreted by other types of cells. This expression grouping is referred to herein as grouping.

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secreted / epithelial

Still in another aspect, an expression grouping identified herein includes DUSP1, EGR1, EGR3, FOS, NR4A1, RHOB, and other genes whose transcription is regulated by increase early

5 after exposure of cells to certain stimuli. A variety of stimuli trigger the transcription of early response genes, for example exposure to growth factors, allowing cells to rapidly increase their motility and their ability to transport nutrients such as glucose. This expression grouping is referred to herein as early response grouping.

10 In yet another aspect, an expression cluster identified herein includes MCP1, CD68, CTSB, OPN, and other genes encoding proteins commonly associated with cells of the immune system. This expression grouping is referred to herein as immune grouping.

In a further aspect, an expression grouping identified herein includes CCNE2,

fifteen CDC20, SKP2, CHK1, BRCA1, CSEL1 and other genes involved in cell cycle proliferation and regulation. This expression grouping is referred to herein as cell cycle / proliferation clustering.

k. Overview of mRNA isolation, purification and amplification

twenty The steps of a representative protocol for obtaining the gene expression profile using fixed tissues, embedded in paraffin as a source of RNA, including mRNA isolation, purification, primer extension and amplification (for example: TE Godfrey et al., J. Molec. Diagnostics 2: 84-91 (2000); K. Specht et al., Am. J. Pathol. 158: 419-29 (2001)). In summary, a representative procedure begins with the cutting of sections approximately 10 µm thick.

25 samples of tumor tissue embedded in paraffin. Then the RNA is extracted, and the proteins and DNA are removed. After analysis of the RNA concentration, RNA repair and / or amplification steps can be included, if necessary, and the RNA is transcribed in reverse using gene specific promoters followed by RT-PCR. Finally, the data is analyzed to identify the best treatment option (s) available to the patient based on the characteristic gene expression pattern identified in the examined tumor sample,

30 dependent on the predicted probability of cancer recurrence.

l. Set of colon cancer genes, subsets of genes tested and clinical application of gene expression data

35 An important aspect of the present invention is to use the measured expression of the BGN gene by colon cancer tissue to provide prognostic information. For this purpose it is necessary to correct (normalize) both the differences in the amount of RNA tested and the variability in the quality of the RNA used. Therefore, the assay normally measures and incorporates the expression of certain normalization genes, including well-known maintenance genes, such as GAPDH and Cyp1. Alternatively, normalization can be based on the

40 medium or medium signal (Ct) of all genes tested or a large subset of them (global standardization approach). On a gene-to-gene basis, the measured normalized amount of a patient's tumor mRNA is compared with the amount found in a reference set of colon cancer tissue. The number (N) of colon cancer tissues in this reference set must be high enough to ensure that different reference sets (as a whole) behave in essentially the same way. Yes

Four. Five If this condition is not met, the identity of the individual colon cancer tissues present in a particular set will not have a significant impact on the relative amounts of the genes tested. Typically, the colon cancer tissue reference set consists of at least about 30, preferably at least about 40 different FPE colon cancer tissue samples. Unless otherwise indicated, normalized expression levels for each mRNA / tumor subjected to

fifty test / patient will be expressed as a percentage of the level of expression measured in the reference set. More specifically, the reference set of a sufficiently high number (for example 40) of tumors produces a distribution of normalized levels of each mRNA species. The level measured in a particular tumor sample to be analyzed is in some percentile within this range, which can be determined by methods well known in the art. Then, unless otherwise indicated, the reference to

55 Expression levels of a gene implies normalized expression in relation to the reference set although it is not always explicitly established.

m. Design of intron-based PCR probes and primers

60 According to one aspect, PCR probes and primers are designed based on intron sequences present in the gene to be amplified. Therefore, the first stage in the design of probes / primers is the delineation of intron sequences within the genes. This can be done by publicly available software, such as DNA BLAT software developed by Kent, WJ, Genome Res. 12 (4): 656-64 (2002), or by BLAST software including its variations. Subsequent stages follow well established methods of probe design and

65 PCR primers.

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In order to avoid non-specific signals, it is important to mask repetitive sequences within introns when designing primers and probes. This can easily be achieved using the Repeat Masker program available online through the Bailor College of Medicine, which examines DNA sequences in front of a library of repetitive elements and returns a query sequence in which the repetitive elements are masked. The masked intron sequences can then be used to design probe and primer sequences using any commercially or otherwise available probe / primer design package, such as Primer Express (Applied Biosystems); MGB assay-by-design (Applied Biosystems); Primer3 (Steve Rozen and Helen J. Skaletsky (2000) Primer3 on the WWW for general users and for biologist programmers. In: Krawetz S, Misener S (eds) Bioinformatics Methods and Protocols: Methods in Molecular

10 Biology Humana Press, Totowa, NJ, p. 365-386).

The most important factors considered in the design of PCR primers include primer length, melting temperature (Tm) and G / C content, specificity, complementary primer sequences and 3 'end sequence. In general, optimal PCR primers are generally 17-30 bases in length, and

fifteen they contain about 20-80%, such as, for example, about 50-60% of G + C bases. Tm of between 50 and 80 ° C are normally preferred, for example about 50 to 70 ° C.

For additional guidelines for the design of PCR probes and primers see, for example, Dieffenbach, CW et al., "General Concepts for PCR Primer Design" in: PCR Primer, A Laboratory Manual, Cold Spring Harbor

twenty Laboratory Press, New York, 1995, p. 133-155; Innis and Gelfand, "Optimization of PCRs" in: PCR Protocols, A Guide to Methods and Applications, CRC Press, London, 1994, p. 5-11; and Plasterer, TN Primerselect: Primer and probe design. Methods Mol. Biol. 70: 520-527 (1997).

n. Kits

25 The materials for use in the methods of the present invention are suitable for the preparation of kits produced according to well known procedures. The kits comprise agents, which may include probes and / or gene-specific or gene-selective genes, to quantify the expression of the genes disclosed to predict the outcome of the prognosis or the response to treatment. Such kits may optionally contain

30 reagents for the extraction of RNA from tumor samples, in particular samples of tissue embedded in fixed paraffin and / or reagents for RNA amplification. In addition, the kits may optionally comprise the reagent (s) with an identification description or label or instructions regarding their use in the methods of the present invention. The kits may comprise packages (including microtiter plates suitable for use in an automated implementation of the method), each with one or more of the various reagents

35 (usually in concentrated form) used in the methods, including, for example, prefabricated microalignments, buffers, suitable nucleotide triphosphates (e.g., dATP, dCTP, dGTP and dTTP; or rATP, rCTP, rGTP and UTP), reverse transcriptase, DNA polymerase, RNA polymerase and one or more probes and primers (eg, random or poly (T) primers of appropriate length attached to a promoter reactive with RNA polymerase). Mathematical algorithms used to estimate or quantify the prognosis or predictive information are also

40 properly possible kit components.

or. Reports of the invention

The methods of this description, when implemented for commercial diagnostic purposes produce

Four. Five generally a report or summary of the normalized expression levels of one or more of the selected genes. The methods will produce a report that includes a prediction of the clinical outcome of a subject diagnosed with colorectal cancer after surgical resection of said cancer. Methods and reports may also include storing the report in a database. Alternatively, the method can also create a record in a database for the subject and fill in the record with data. In one embodiment the report

fifty it is a paper report, in another embodiment the report is an auditory report, in another embodiment the report is an electronic record. It is contemplated that the report be provided to a doctor and / or the patient. The recipient of the report may also include establishing a network connection with a server that includes the data and the report and requesting the data and the report from the server.

55 The methods provided by the present invention can also be automated in whole or in part.

All aspects of the present description can also be put into practice so as to include a limited number of additional genes that are co-expressed with the genes disclosed, for example, as demonstrated by high Pearson correlation coefficients, in a test. of prognosis or predictive in addition to and / or

60 instead of the genes released.

Having described the invention, it will be more readily understood through reference to the following example, which is provided by way of illustration, and is not intended to limit the invention in any way.

65 Examples

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A study to explore the relationships between genomic tumor expression profiles and the likelihood of recurrence in patients with Duke B and Duke C treated with colon resection

The primary objective of this study was to determine whether there is a significant relationship between the expression of each of 5,757 amplicons identified in Table B and the clinical outcome of patients with stage II and stage III colon cancer receiving colon resection ( surgery) without chemotherapy.

Study design

10 This was an exploratory study using tissue and outcome data from studies C-01 and C0-2 of the National Surgical Adjuvant Breast and Bowel Project (NSABP) in up to 400 patients with Duke B (stage II) and Duke C (stage III) who received colon resection (surgery) alone or postoperative surgery and bacillus Calmette-Guerin (BCG).

Inclusion criteria

fifteen Patients included in either the NSABP C-01 study: “A Clinical Trial To Evaluate Postoperative Immunotherapy And Postoperative Systemic Chemotherapy In The Management of Resectable Colon Cancer” or in the NSABP C-02 study: “A Protocol To Evaluate The Postoperative Portal Vein Infusion Of 5-Flourouracil And Heparin in Adenocarcinoma Of The Colon ”. Details of C-01 and C-02 can be found on the NSABP website at the

twenty following URL:

http://www.nsabp.pitt.edu/NSABPProtocols.htm#treatment%20closed

Tissue samples from the surgery alone and surgery + BCG postoperative branches of NSABP C01 and from the surgery alone surgery branch of NSABP C02 were combined to give a set of samples.

Exclusion criteria

Patients included in the NSABP C-01 study or the NSABP C-02 study were excluded from the present study if one or more of the following were applied:

No tumor block available from the initial diagnosis in the NSABP file.

■ Insufficient block tumor as assessed by examination of hematoxylin and eosin 35 slides (H&E)

■ Insufficient RNA (<700 ng) recovered from tissue sections for RT-PCR analysis.

Of 1943 patients included in the NSABP C-01 study or the NSABP C-02 study, 270 were available

40 patient samples after the application of the exclusion criteria and were used in the gene expression study disclosed herein. The overall clinical and demographic characteristics of the 270 samples included were similar to the combined NSABP cohorts.

Gene panel

Four. Five Seven hundred sixty-one genes, including seven reference genes, were chosen for expression analysis. These genes are listed in Table A together with the primer sequences and probes used in qRT-PCR to determine the level of expression.

fifty Materials and experimental methods

The expression of 750 cancer-related genes and 7 genes designated for use as reference genes for each patient was evaluated quantitatively using TaqMan® RT-PCR, which was performed individually with RNA introduction at 1 nanogram per reaction.

55 Data analysis methods

Normalization by reference

60 For the normalization of strange effects; threshold cycle (CT) measurements obtained by RT-PCR were normalized in relation to the mean expression of a set of six reference genes. The resulting standardized expression measurements by reference normally range from 0 to 15, where an increase of one unit reflects a 2-fold increase in the amount of RNA.

65 Comparison of the study cohort with the populations of the original NSABP studies

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The distribution of clinical and demographic variables for the current study cohort of evaluable tissue blocks was compared against the populations of the original C-01 and C-02 studies of the NSABP. There were no clinically significant differences in the distributions.

5 Analysis of a variable

For each of the 757 amplicons under study, the Cox proportional hazards model was used to examine the relationship between gene expression and recurrence-free interval (ILR). The probability ratio was used as evidence of statistical significance. The Benjamini and Hochberg method (Benjamini, Y. and Hochberg, Y. (1995) were applied. Controlling the false discovery rate: a practical and powerful approach to multiple testing. JR Statist. Soc. B 57, 289-300.), As well as resampling and permutation-based methods (Tusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA, 98: 51165121. ; Storey JD, Tibshirani R (2001) Estimating false discovery rates under dependence, with applications to DNA microarrays. Stanford: Stanford University, Department of Statistics; report #: Technical Report 2001-28 .; Korn EL,

fifteen Troendle J, McShane L, Simon R (2001) Controlling the number of false discoveries: Application to high-dimensional genomic data. Technical Report 003. 2001. National Cancer Institute) to the resulting set of p values ​​to estimate false discovery rates. All analyzes were repeated for each of the alternative assessment criteria: distance-free recurrence interval (ILRD), overall survival (OS) and disease-free survival (SLE).

Analysis of multiple variants

For each of the 757 amplicons under study, the Cox proportional hazards model was used to examine the relationship between gene expression and ILR, while controlling the effects of other clinical covariates.

25 conventional (including tumor location, type of surgery, tumor grade, number of lymph nodes examined and number of positive lymph nodes). The difference in logarithmic probabilities of the (reduced) model that includes only conventional clinical covariates and the (complete) model that includes conventional clinical covariates plus gene expression was used as evidence of statistical significance.

Nonlinear analysis

For each of the 757 amplicons under study, alternative functional relationships between gene expression and recurrence were explored using several different methods. For each amplicon, an ILR Cox proportional hazard model was adjusted as a gene expression function using a natural spline type curve of 2 35 degrees of freedom (GL) (Stone C, Koo C. (1985) In Proceedings of th and Statistical Computing Section ASA. Washington, DC, 45-48). Statistical significance was assessed using the probability ratio of 2 GL for the model. Functional relationships were also explored by examining the Martingale residual error pattern (smoothing) derived from Cox proportional hazard models of an ILR variable as a strictly linear function of gene expression (Gray RJ (1992) Flexible methods for analyzing survival data using splines, with applications to breast cancer prognosis. Journal of the American Statistical Asssociation, 87: 942-951; Gray RJ (1994) Spline-based tests in survival analysis. Biometrics, 50: 640-652 .; Gray RJ (1990) Some diagnostic methods for Cox regression models through hazard smoothing. Biometrics, 46: 93-102). Additionally, the cumulative sums of Martingale residual errors were used from each of the same Cox proportional hazards models to detect linearity deviations (Lin D, Wei'L, Ying Z. (1993) Checking the Cox

Four. Five Model with Cumulative Sums of Martingale-Based Residuals. Vol. 80, No. 3,557-572).

Interaction with the stadium

It was determined whether there is a significantly different relationship between gene expression and ILR in stage II and stage III patients. For each of the 757 amplicons, the hypothesis that there is a significant difference between the proportional hazards model (reduced) for gene expression and the tumor stage versus the proportional hazards model (complete) based on expression was tested. gene, stage of the tumor and its interaction. The difference in logarithmic probabilities of the reduced and complete models was used as evidence of statistical significance.

55 Table A shows sequences of qRT-PCR primers and probes for all genes included in the study described in the example.

Table B shows target amplicons for all genes included in the study described in the example.

Results of the first analysis study

The set of reference genes for the first analysis was CLTC, FZD6, NEDD8, RPLPO, RPS 13, UBB, UBC.

65 Table 1A shows associations for genes whose increased expression is predictive of a shorter recurrence free interval (ILR) based on the analysis of proportional hazards of a variable.

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Table 1B shows associations for genes whose increased expression is predictive of a longer recurrence free interval (ILR) based on the analysis of proportional hazards of a variable.

5 Table 2A shows associations for genes whose increased expression is predictive of a decreased overall survival rate (OS) based on the analysis of proportional hazards of a variable.

Table 2B shows associations for genes whose increased expression is predictive of an increased overall survival rate (OS) based on the analysis of proportional hazards of a variable.

10 Table 3A shows associations for genes whose increased expression is predictive of a decreased disease-free survival rate (SLE) based on the analysis of proportional hazards of a variable.

Table 3B shows associations for genes whose increased expression is predictive of an increased disease-free survival rate (SLE) based on the analysis of proportional hazards of a variable.

Table 4A shows associations for genes whose increased expression is predictive of a shorter distance-free recurrence interval (ILRD) based on the analysis of proportional hazards of a variable.

twenty Table 4B shows associations for genes whose increased expression is predictive of a longer distance-free recurrence interval (ILRD) based on the analysis of proportional hazards of a variable.

Table 5A shows associations between gene expression and ILR for genes whose increased expression is predictive of a shorter recurrence free interval (ILR), based on a multivariate analysis that controls particular demographic and clinical characteristics of patients included in the study. analysis.

Table 5B shows associations between gene expression and ILR for genes whose increased expression is predictive of a longer recurrence free interval (ILR), based on a multi-variable analysis that controls particular demographic and clinical characteristics of patients included in the analysis. .

30 Table 6 shows genes for which an association between gene expression and clinical outcome was identified based on a nonlinear proportional hazard analysis, using a natural spline curve of 2 degrees of freedom.

35 Table 7 shows all the genes that have an interaction (p value <0.05) with the tumor stage.

Table 1A shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio> 1.0 and for which p <0.1. Cox proportional hazards regression analysis of one variable was applied in stage II (Duke B) and stage III (Duke C) patients combined using ILR as a metric for

40 clinical outcome

Table 1A

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>RARB </dt><dd>2.13 0.0252 RARB NM_016152 </dd></dl>

<dl><dt>ITGB1 </dt><dd>1.94 0.0002 ITGB1 NM_002211 </dd></dl>

<dl><dt>ALDOA </dt><dd>1.92 0.0853 ALDOA NM_000034 </dd></dl>

<dl><dt>ANXA2 </dt><dd>1.90 &lt;0.0001 ANXA2 NM_004039 </dd></dl>

<dl><dt>CYP3A4 </dt><dd>1.81 0.0038 CYP3A4 NM_017460 </dd></dl>

<dl><dt>KRAS2 </dt><dd>1.64 0.0043 KRAS NM_004985 </dd></dl>

<dl><dt>COX2 </dt><dd>1.62 0.0521 PTGS2 NM_000963 </dd></dl>

<dl><dt>RhoC </dt><dd>1.61 0.0034 RHOC NM_175744 </dd></dl>

<dl><dt>TJP1 </dt><dd>1.60 0.0554 TJP1 NM_003257 </dd></dl>

<dl><dt>RhoB </dt><dd>1.57 0.0001 Rhob NM_004040 </dd></dl>

<dl><dt>KIAA0125 </dt><dd>1.56 0.0940 KIAA0125 NM_014792 </dd></dl>

<dl><dt>TIMP1 </dt><dd>1.52 &lt;0.0001 TIMP1 NM_003254 </dd></dl>

<dl><dt>UBC </dt><dd>1.49 0.0031 UBC NM_021009 </dd></dl>

<dl><dt>ANXA5 </dt><dd>1.49 0.0084 ANXA5 NM_001154 </dd></dl>

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<dl><dt>NTN1 </dt><dd>1.49 0.0386 NTN1 NM_004822 </dd></dl>

<dl><dt>AKT3 </dt><dd>1.47 &lt;0.0001 AKT3 NM_005465 </dd></dl>

<dl><dt>CALD1 </dt><dd>1.46 0.0007 CALD1 NM_004342 </dd></dl>

<dl><dt>IGFBP7 </dt><dd>1.46 0.0019 IGFBP7 NM_001553 </dd></dl>

<dl><dt>VEGFC </dt><dd>1.45 0.0092 VEGFC NM_005429 </dd></dl>

<dl><dt>BGN </dt><dd>1.44 0.0002 BGN NM_001711 </dd></dl>

<dl><dt>CYP1B1 </dt><dd>1.44 0.0180 CYP1B1 NM_000104 </dd></dl>

<dl><dt>DLC1 </dt><dd>1.43 0.0012 DLC1 NM_006094 </dd></dl>

<dl><dt>S1 </dt><dd>1.43 0.0063 YES NM_001041 </dd></dl>

<dl><dt>CCNE2 variant 1 </dt><dd>1.43 0.0506 CCNE2 NM_057749 </dd></dl>

<dl><dt>LAMC2 </dt><dd>1.42 0.0003 LAMC2 NM_005562 </dd></dl>

<dl><dt>TIMP2 </dt><dd>1.42 0.0018 TIMP2 NM_003255 </dd></dl>

<dl><dt>CDC42BPA </dt><dd>1.42 0.0029 CDC42BPA NM_003607 </dd></dl>

<dl><dt>p21 </dt><dd>1.41 0.0062 CDKN1A NM_000389 </dd></dl>

<dl><dt>HB-EGF </dt><dd>1.40 0.0105 HBEGF NM_001945 </dd></dl>

<dl><dt>TLN1 </dt><dd>1.40 0.0260 TLN1 NM_006289 </dd></dl>

<dl><dt>DUSP1 </dt><dd>1.39 &lt;0.0001 DUSP1 NM_004417 </dd></dl>

<dl><dt>ROCK1 </dt><dd>1.39 0.0121 ROCK1 NM_005406 </dd></dl>

<dl><dt>CTSB </dt><dd>1.39 0.0307 CTSB NM_001908 </dd></dl>

<dl><dt>ITGAV </dt><dd>1.38 0.0020 ITGAV NM_002210 </dd></dl>

<dl><dt>HSPG2 </dt><dd>1.38 0.0215 HSPG2 NM_005529 </dd></dl>

<dl><dt>GADD45B </dt><dd>1.37 0.0002 GADD45B NM_015675 </dd></dl>

<dl><dt>VCL </dt><dd>1.37 0.0201 VCL NM_003373 </dd></dl>

<dl><dt>SBA2 </dt><dd>1.37 0.0250 WSB2 NM_018639 </dd></dl>

<dl><dt>Maspina </dt><dd>1.36 &lt;0.0001 SERPINB5 NM_002639 </dd></dl>

<dl><dt>CGB </dt><dd>1.36 0.0018 CGB NM_000737 </dd></dl>

<dl><dt>TIMP3 </dt><dd>1.36 00024 TIMP3 NM_000362 </dd></dl>

<dl><dt>VIM </dt><dd>1.36 0.0073 VIM NM_003380 </dd></dl>

<dl><dt>S100A1 </dt><dd>1.36 0.0247 S100A1 NM_006271 </dd></dl>

<dl><dt>INHBA </dt><dd>1.35 0.0008 INHBA NM_002192 </dd></dl>

<dl><dt>SIR2 </dt><dd>1.35 0.0039 SIRT1 NM_012238 </dd></dl>

<dl><dt>TMSB10 </dt><dd>1.35 0.0469 TMSB10 NM_021103 </dd></dl>

<dl><dt>CD68 </dt><dd>1.34 0.0036 CD68 NM_001251 </dd></dl>

<dl><dt>RBX1 </dt><dd>1.34 0.0469 RBX1 NM_014248 </dd></dl>

<dl><dt>INHBB </dt><dd>1.34 0.0514 INHBB NM_002193 </dd></dl>

<dl><dt>PKR2 </dt><dd>1.34 0.0628 PKM2 NM_002654 </dd></dl>

<dl><dt>FOS </dt><dd>1.33 0.0006 FOS NM_005252 </dd></dl>

<dl><dt>FYN </dt><dd>1.33 0.0036 FYN NM_002037 </dd></dl>

<dl><dt>LOXL2 </dt><dd>1.33 0.0064 LOXL2 NM_002318 </dd></dl>

<dl><dt>STC1 </dt><dd>1.33 0.0101 STC1 NM_003155 </dd></dl>

<dl><dt>DKK1 </dt><dd>1.33 0.0208 DKK1 NM_012242 </dd></dl>

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<dl><dt>IGFBP5 </dt><dd>1.32 0.0064 IGFBP5 NM_000599 </dd></dl>

<dl><dt>EPAS1 </dt><dd>1.32 0.0270 EPAS1 NM_001430 </dd></dl>

<dl><dt>UNC5C </dt><dd>1.32 0.0641 UNC5C NM_003728 </dd></dl>

<dl><dt>FAP </dt><dd>1.31 0.0017 FAP NM_004460 </dd></dl>

<dl><dt>IGFBP3 </dt><dd>1.31 0.0041 IGFBP3 NM_000598 </dd></dl>

<dl><dt>SNAI2 </dt><dd>1.31 0.0055 SNAI2 NM_003068 </dd></dl>

<dl><dt>PRKCA </dt><dd>1.31 0.0065 PRKCA NM_002737 </dd></dl>

<dl><dt>FST </dt><dd>1.31 0.0399 FST NM_006350 </dd></dl>

<dl><dt>KCNH2 iso a / b </dt><dd>1.31 0.0950 KCNH2 NM_000238 </dd></dl>

<dl><dt>CTHRC1 </dt><dd>1.30 0.0017 CTHRC1 NM_138455 </dd></dl>

<dl><dt>PDGFC </dt><dd>1.30 0.0034 PDGFC NM_016205 </dd></dl>

<dl><dt>EGR1 </dt><dd>1.30 0.0048 EGR1 NM_001964 </dd></dl>

<dl><dt>TAGLN </dt><dd>1.30 0.0058 TAGLN NM_003186 </dd></dl>

<dl><dt>SPARC </dt><dd>1.30 0.0104 SPARC NM_003118 </dd></dl>

<dl><dt>KLF6 </dt><dd>1.30 0.0514 KLF6 NM_001300 </dd></dl>

<dl><dt>GRIK1 </dt><dd>1.30 0.0753 GRIK1 NM_000830 </dd></dl>

<dl><dt>CYR61 </dt><dd>1.29 0.0018 CYR61 NM_001554 </dd></dl>

<dl><dt>SLPI </dt><dd>1.29 0.0026 SLPI NM_003064 </dd></dl>

<dl><dt>COL1A2 </dt><dd>1.29 0.0076 COL1A2 NM_000089 </dd></dl>

<dl><dt>MAPK14 </dt><dd>1.29 0.0916 MAPK14 NM_139012 </dd></dl>

<dl><dt>LAMA3 </dt><dd>1.28 0.0020 LAMA3 NM_000227 </dd></dl>

<dl><dt>THBS1 </dt><dd>1.28 0.0053 THBS1 NM_003246 </dd></dl>

<dl><dt>NRP2 </dt><dd>1.28 0.0120 NRP2 NM_003872 </dd></dl>

<dl><dt>LOX </dt><dd>1.27 0.0028 LOX NM_002317 </dd></dl>

<dl><dt>S100A4 </dt><dd>1.27 0.0067 S100A4 NM_002961 </dd></dl>

<dl><dt>CXCR4 </dt><dd>1.27 0.0083 CXCR4 NM_003467 </dd></dl>

<dl><dt>CEBPB </dt><dd>1.27 0.0943 CEBPB NM_005194 </dd></dl>

<dl><dt>AKAP12 </dt><dd>1.26 0.0044 AKAP12 NM_005100 </dd></dl>

<dl><dt>ADAMTS12 </dt><dd>1.26 0.0100 ADAMTS12 NM_030955 </dd></dl>

<dl><dt>CRYAB </dt><dd>1.25 0.0038 CRYAB NM_001885 </dd></dl>

<dl><dt>Grb10 </dt><dd>1.25 0.0108 GRB10 NM_005311 </dd></dl>

<dl><dt>MCP1 </dt><dd>1.25 0.0118 CCL2 NM_002982 </dd></dl>

<dl><dt>COL1A1 </dt><dd>1.25 0.0167 COL1A1 NM_000088 </dd></dl>

<dl><dt>EFNB2 </dt><dd>1.25 0.0241 EFNB2 NM_004093 </dd></dl>

<dl><dt>ANXA1 </dt><dd>1.25 0.0292 ANXA1 NM_000700 </dd></dl>

<dl><dt>ANGPT2 </dt><dd>1.25 0.0485 ANGPT2 NM_001147 </dd></dl>

<dl><dt>EphB6 </dt><dd>1.25 0.0825 EPHB6 NM_004445 </dd></dl>

<dl><dt>HSPA1A </dt><dd>1.24 0.0018 HSPA1A NM_005345 </dd></dl>

<dl><dt>TGFB3 </dt><dd>1.24 0.0081 TGFB3 NM_003239 </dd></dl>

<dl><dt>PTGER3 </dt><dd>1.24 0.0306 PTGER3 NM_000957 </dd></dl>

<dl><dt>FXYD5 </dt><dd>1.24 0.0367 FXYD5 NM_014164 </dd></dl>

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<dl><dt>CAPG </dt><dd>1.24 0.0604 CAPG NM_001747 </dd></dl>

<dl><dt>PDGFB </dt><dd>1.23 0.0157 PDGFB NM_002608 </dd></dl>

<dl><dt>ANTXR1 </dt><dd>1.23 0.0164 ANTXR1 NM_032208 </dd></dl>

<dl><dt>TGFBI </dt><dd>1.23 0.0191 TGFBI NM_000358 </dd></dl>

<dl><dt>CTGF </dt><dd>1.23 0.0233 CTGF NM_001901 </dd></dl>

<dl><dt>PDGFA </dt><dd>1.23 0.0274 NM_002607 </dd></dl>

<dl><dt>P14ARF </dt><dd>1.23 0.0362 S78535 </dd></dl>

<dl><dt>KLK10 </dt><dd>1.22 0.0005 KLK10 NM_002776 </dd></dl>

<dl><dt>ITGA5 </dt><dd>1.22 0.0178 ITGA5 NM_002205 </dd></dl>

<dl><dt>GBP2 </dt><dd>1.22 0.0201 GBP2 NM_004120 </dd></dl>

<dl><dt>SIAT4A </dt><dd>1.22 0.0231 ST3GAL1 NM_003033 </dd></dl>

<dl><dt>GJB2 </dt><dd>1.22 0.0271 GJB2 NM_004004 </dd></dl>

<dl><dt>THE T </dt><dd>1.22 0.0306 THE T NM_014387 </dd></dl>

<dl><dt>CTSL </dt><dd>1.22 0.0331 CTSL NM_001912 </dd></dl>

<dl><dt>DAPK1 </dt><dd>1.22 0.0384 DAPK1 NM_004938 </dd></dl>

<dl><dt>SKP1A </dt><dd>1.22 0.0542 SKP1A NM_006930 </dd></dl>

<dl><dt>NDRG1 </dt><dd>1.22 0.0712 NDRG1 NM_006096 </dd></dl>

<dl><dt>ITGB5 </dt><dd>1.22 0.0991 ITGB5 NM_002213 </dd></dl>

<dl><dt>KLK6 </dt><dd>1.21 0.0034 KLK6 NM_002774 </dd></dl>

<dl><dt>SFRP2 </dt><dd>1.21 0.0037 SFRP2 NM_003013 </dd></dl>

<dl><dt>TMEPAI </dt><dd>1.21 0.0173 TMEPAI NM_020182 </dd></dl>

<dl><dt>ID4 </dt><dd>1.21 0.0530 ID4 NM_001546 </dd></dl>

<dl><dt>SFRP4 </dt><dd>1.20 0.0077 SFRP4 NM_003014 </dd></dl>

<dl><dt>HOXB7 </dt><dd>1.20 0.0274 HOXB7 NM_004502 </dd></dl>

<dl><dt>GJA1 </dt><dd>1.20 0.0311 GJA1 NM_000165 </dd></dl>

<dl><dt>CDH11 </dt><dd>1.20 0.0662 CDH11 NM_001797 </dd></dl>

<dl><dt>PAI1 </dt><dd>1.19 0.0060 SERPINE1 NM_000602 </dd></dl>

<dl><dt>S100P </dt><dd>1.19 0.0119 S100P NM_005980 </dd></dl>

<dl><dt>EGR3 </dt><dd>1.19 0.0164 EGR3 NM_004430 </dd></dl>

<dl><dt>EMP1 </dt><dd>1.19 0.0460 EMP1 NM_001423 </dd></dl>

<dl><dt>ABCC5 </dt><dd>1.19 0.0536 ABCC5 NM_005688 </dd></dl>

<dl><dt>FZD1 </dt><dd>1.19 0.0701 FZD1 NM_003505 </dd></dl>

<dl><dt>MAD </dt><dd>1.19 0.0811 MXD1 NM_002357 </dd></dl>

<dl><dt>EFNA1 </dt><dd>1.19 0.0920 EFNA1 NM_004428 </dd></dl>

<dl><dt>OPN_osteopontina </dt><dd>1.18 0.0028 SPP1 NM_000582 </dd></dl>

<dl><dt>ALDH1A1 </dt><dd>1.18 0.0246 ALDH1A1 NM_000689 </dd></dl>

<dl><dt>NR4A1 </dt><dd>1.18 0.0277 NR4A1 NM_002135 </dd></dl>

<dl><dt>SIAT7B </dt><dd>1.18 0.0301 ST6GALNAC2 NM_006456 </dd></dl>

<dl><dt>p16-INK4 </dt><dd>1.18 0.0439 L27211 </dd></dl>

<dl><dt>TUBB </dt><dd>1.18 0.0761 TUBB2 NM_001069 </dd></dl>

<dl><dt>IL6 </dt><dd>1.18 0.0939 IL6 NM_000600 </dd></dl>

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<dl><dt>RAB32 </dt><dd>1.18 0.0948 RAB32 NM_006834 </dd></dl>

<dl><dt>TULP3 </dt><dd>1.18 0.0953 TULP3 NM_003324 </dd></dl>

<dl><dt>F3 </dt><dd>1.17 0.0561 F3 NM_001993 </dd></dl>

<dl><dt>PLK3 </dt><dd>1.16 0.0792 PLK3 NM_004073 </dd></dl>

<dl><dt>EPHA2 </dt><dd>1.16 0.0962 EPHA2 NM_004431 </dd></dl>

<dl><dt>SLC2A1 </dt><dd>1.15 0.0745 SLC2A1 NM_006516 </dd></dl>

<dl><dt>CXCL12 </dt><dd>1.14 0.0911 CXCL12 NM_000609 </dd></dl>

<dl><dt>S100A2 </dt><dd>1.13 0.0287 S100A2 NM_005978 </dd></dl>

<dl><dt>FABP4 </dt><dd>1.13 0.0340 FABP4 NM_001442 </dd></dl>

<dl><dt>STMY3 </dt><dd>1.13 0.0517 MMP11 NM_005940 </dd></dl>

<dl><dt>BCAS1 </dt><dd>1.13 0.0939 BCAS1 NM_003657 </dd></dl>

<dl><dt>REG4 </dt><dd>1.11 0.0026 REG4 NM_032044 </dd></dl>

<dl><dt>pS2 </dt><dd>1.09 0.0605 TFF1 NM_003225 </dd></dl>

<dl><dt>MUC2 </dt><dd>1.06 0.0626 MUC2 NM_002457 </dd></dl>

Table 1B shows the associations between clinical outcome and gene expression for genes that demonstrated a risk ratio &lt;1.0 and for which p &lt;0.1. Cox proportional hazards regression analysis of one variable was applied in stage II (Duke B) and stage III (Duke C) patients combined using ILR as a metric for the clinical outcome

Table 1B

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>ORC1L </dt><dd>0.42 0.0728 ORC1L NM_004153 </dd></dl>

<dl><dt>HSPA8 </dt><dd>0.62 0.0430 HSPA8 NM_006597 </dd></dl>

<dl><dt>E2F1 </dt><dd>0.64 0.0009 E2F1 NM_005225 </dd></dl>

<dl><dt>RAD54L </dt><dd>0.65 0.0026 RAD54L NM_003579 </dd></dl>

<dl><dt>RPLPO </dt><dd>0.67 0.0150 RPLP0 NM_001002 </dd></dl>

<dl><dt>BRCA1 </dt><dd>0.68 0.0001 BRCA1 NM_007295 </dd></dl>

<dl><dt>DHFR </dt><dd>0.69 0.0096 DHFR NM_000791 </dd></dl>

<dl><dt>SLC25A3 </dt><dd>0.69 0.0110 SLC25A3 NM_213611 </dd></dl>

<dl><dt>PPM1D </dt><dd>0.71 0.0033 PPMID NM_003620 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.71 0.0098 SKP2 NM_005983 </dd></dl>

<dl><dt>FASN </dt><dd>0.72 0.0071 FASN NM_004104 </dd></dl>

<dl><dt>HNRPD </dt><dd>0.72 0.0686 HNRPD NM_031370 </dd></dl>

<dl><dt>ENO1 </dt><dd>0.73 0.0418 ENO1 NM_001428 </dd></dl>

<dl><dt>RPS13 </dt><dd>0.75 0.0786 RPS13 NM_001017 </dd></dl>

<dl><dt>DDB1 </dt><dd>0.75 0.0804 DDB1 NM_001923 </dd></dl>

<dl><dt>C20 orf1 </dt><dd>0.76 0.0122 TPX2 NM_012112 </dd></dl>

<dl><dt>KIF22 </dt><dd>0.76 0.0137 KIF22 NM_007317 </dd></dl>

<dl><dt>Chk1 </dt><dd>0.76 0.0174 CHEK1 NM_001274 </dd></dl>

<dl><dt>TCF-1 </dt><dd>0.77 0.0021 TCF1 NM_000545 </dd></dl>

<dl><dt>ST14 </dt><dd>0.77 0.0446 ST14 NM_021978 </dd></dl>

<dl><dt>RRM1 </dt><dd>0.77 0.0740 RRM1 NM_001033 </dd></dl>

<dl><dt>BRCA2 </dt><dd>0.77 0.0800 BRCA2 NM_000059 </dd></dl>

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<dl><dt>LMNB1 </dt><dd>0.78 0.0513 LMNB1 NM_005573 </dd></dl>

<dl><dt>CMYC </dt><dd>0.79 0.0086 MYC NM_002467 </dd></dl>

<dl><dt>CDC20 </dt><dd>0.79 0.0290 CDC20 NM_001255 </dd></dl>

<dl><dt>CSEL1 </dt><dd>0.79 0.0344 CSE1L NM_001316 </dd></dl>

<dl><dt>Bax </dt><dd>0.79 0.0662 BAX NM_004324 </dd></dl>

<dl><dt>NME1 </dt><dd>0.79 0.0742 NME1 NM_000269 </dd></dl>

<dl><dt>c-myb (official MYB) </dt><dd>0.80 0.0077 MY B NM_005375 </dd></dl>

<dl><dt>CDCA7 v2 </dt><dd>0.80 0.0159 CDCA7 NM_145810 </dd></dl>

<dl><dt>EFP </dt><dd>0.80 0.0405 TRIM25 NM_005082 </dd></dl>

<dl><dt>UBE2M </dt><dd>0.80 0.0437 UBE2M NM_003969 </dd></dl>

<dl><dt>RRM2 </dt><dd>0.81 0.0168 RRM2 NM_001034 </dd></dl>

<dl><dt>ABCC6 </dt><dd>0.81 0.0373 ABCC6 NM_001171 </dd></dl>

<dl><dt>SURV </dt><dd>0.81 0.0584 BIRCS NM_001168 </dd></dl>

<dl><dt>CKS2 </dt><dd>0.81 0.0753 CKS2 NM_001827 </dd></dl>

<dl><dt>RAF1 </dt><dd>0.81 0.0899 RAF1 NM_002880 </dd></dl>

<dl><dt>EPHB2 </dt><dd>0.82 0.0190 EPHB2 NM_004442 </dd></dl>

<dl><dt>NOTCH1 </dt><dd>0.82 0.0232 NOTCH1 NM_017617 </dd></dl>

<dl><dt>UMPS </dt><dd>0.82 0.0456 UMPS NM_000373 </dd></dl>

<dl><dt>CCNE2 </dt><dd>0.82 0.0544 CCNE2 NM_057749 </dd></dl>

<dl><dt>PI3KC2A </dt><dd>0.82 0.0916 PIK3C2A NM_002645 </dd></dl>

<dl><dt>CD80 </dt><dd>0.82 0.0954 CD80 NM_005191 </dd></dl>

<dl><dt>AREG </dt><dd>0.83 0.0014 AREG NM_001657 </dd></dl>

<dl><dt>EREG </dt><dd>0.83 0.0062 EREG NM_001432 </dd></dl>

<dl><dt>MYBL2 </dt><dd>0.83 0.0259 MYBL2 NM_002466 </dd></dl>

<dl><dt>ABCB1 </dt><dd>0.83 0.0322 ABCB1 NM_000927 </dd></dl>

<dl><dt>HRAS </dt><dd>0.83 0.0760 HRAS NM_005343 </dd></dl>

<dl><dt>SLC7A5 </dt><dd>0.84 0.0585 SLC7A5 NM_003486 </dd></dl>

<dl><dt>MAD2L1 </dt><dd>0.84 0.0590 MAD2L1 NM_002358 </dd></dl>

<dl><dt>Ki-67 </dt><dd>0.85 0.0620 MKI67 NM_002417 </dd></dl>

<dl><dt>MCM2 </dt><dd>0.85 0.0700 MCM2 NM_004526 </dd></dl>

<dl><dt>ING5 </dt><dd>0.85 0.0947 ING5 NM_032329 </dd></dl>

<dl><dt>Cdx2 </dt><dd>0.88 0.0476 CDX2 NM_001265 </dd></dl>

<dl><dt>PTPRO </dt><dd>0.89 0.0642 PTPRO NM_030667 </dd></dl>

<dl><dt>crypto (official TDGF1) </dt><dd>0.90 0.0803 TDGF1 NM_003212 </dd></dl>

Table 2A shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio> 1.0 and for which p <0.1. A Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using OS as a metric for the clinical outcome.

Table 2A

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>RARB </dt><dd>1.75 0.0820 RARB NM_016152 </dd></dl>

<dl><dt>RhoC </dt><dd>1.70 0.0001 RHOC NM_175744 </dd></dl>

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<dl><dt>ANXA2 </dt><dd>1.64 0.0002 ANXA2 NM_004039 </dd></dl>

<dl><dt>CYP3A4 </dt><dd>1.58 0.0064 CYP3A4 NM_017460 </dd></dl>

<dl><dt>p21 </dt><dd>1.54 &lt;0.0001 CDKN1A NM_000389 </dd></dl>

<dl><dt>ITGB1 </dt><dd>1.54 0.0058 ITGB1 NM_002211 </dd></dl>

<dl><dt>UBC </dt><dd>1.50 0.0003 UBC NM_021009 </dd></dl>

<dl><dt>TNF </dt><dd>1.46 0.0859 TNF NM_000594 </dd></dl>

<dl><dt>VEGFC </dt><dd>1.44 0.0049 VEGFC NM_005429 </dd></dl>

<dl><dt>HMLH </dt><dd>1.44 0.0435 MLH1 NM_000249 </dd></dl>

<dl><dt>RhoB </dt><dd>1.37 0.0015 Rhob NM_004040 </dd></dl>

<dl><dt>TGFBR1 </dt><dd>1.37 0.0127 TGFBR1 NM_004612 </dd></dl>

<dl><dt>SPINT2 </dt><dd>1.37 0.0235 SPINT2 NM_021102 </dd></dl>

<dl><dt>NFP1 </dt><dd>1.37 0.0842 NFP1 NM_005022 </dd></dl>

<dl><dt>HSPG2 </dt><dd>1.36 0.0115 HSPG2 NM_005529 </dd></dl>

<dl><dt>TIMP1 </dt><dd>1.35 0.0008 TIMP1 NM_003254 </dd></dl>

<dl><dt>INHBB </dt><dd>1.35 0.0190 INHBB NM_002193 </dd></dl>

<dl><dt>VCL </dt><dd>1.34 0.0099 VCL NM_003373 </dd></dl>

<dl><dt>KCNH2 iso a / b </dt><dd>1.33 0.0362 KCNH2 NM_000238 </dd></dl>

<dl><dt>LAMC2 </dt><dd>1.32 0.0005 LAMC2 NM_005562 </dd></dl>

<dl><dt>FXYD5 </dt><dd>1.31 0.0021 FXYD5 NM_014164 </dd></dl>

<dl><dt>HLA-G </dt><dd>1.31 0.0458 HLA-G NM_002127 </dd></dl>

<dl><dt>GADD45B </dt><dd>1.30 0.0002 GADD45B NM_015675 </dd></dl>

<dl><dt>CDC42 </dt><dd>1.30 0.0120 CDC42 NM_001791 </dd></dl>

<dl><dt>LAMB3 </dt><dd>1.30 0.0163 LAMB3 NM_000228 </dd></dl>

<dl><dt>DKK1 </dt><dd>1.30 0.0209 DKK1 NM_012242 </dd></dl>

<dl><dt>UNC5C </dt><dd>1.30 0.0452 UNC5C NM_003728 </dd></dl>

<dl><dt>UBL1 </dt><dd>1.29 0.0171 SUMO1 NM_003352 </dd></dl>

<dl><dt>HB-EGF </dt><dd>1.29 0.0262 HBEGF NM_001945 </dd></dl>

<dl><dt>KRAS2 </dt><dd>1.29 0.0726 KRAS NM_004985 </dd></dl>

<dl><dt>ID3 </dt><dd>1.28 0.0023 ID3 NM_002167 </dd></dl>

<dl><dt>LOXL2 </dt><dd>1.28 0.0039 LOXL2 NM_002318 </dd></dl>

<dl><dt>EphB6 </dt><dd>1.28 0.0322 EPHB6 NM_004445 </dd></dl>

<dl><dt>DUSP1 </dt><dd>1.27 0.0003 DUSP1 NM_004417 </dd></dl>

<dl><dt>BGN </dt><dd>1.27 0.0040 BGN NM_001711 </dd></dl>

<dl><dt>CALD1 </dt><dd>1.27 0.0119 CALD1 NM_004342 </dd></dl>

<dl><dt>CDC42BPA </dt><dd>1.27 0.0151 CDC42BPA NM_003607 </dd></dl>

<dl><dt>SBA2 </dt><dd>1.27 0.0373 WSB2 NM_018639 </dd></dl>

<dl><dt>INHBA </dt><dd>1.26 0.0018 INHBA NM_002192 </dd></dl>

<dl><dt>NRP1 </dt><dd>1.26 0.0113 NRP1 NM_003873 </dd></dl>

<dl><dt>TIMP2 </dt><dd>1.26 0.0123 TIMP2 NM_003255 </dd></dl>

<dl><dt>KLF6 </dt><dd>1.26 0.0444 KLF6 NM_001300 </dd></dl>

<dl><dt>KLK10 </dt><dd>1.25 &lt;0.0001 KLK10 NM_002776 </dd></dl>

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<dl><dt>TIMP3 </dt><dd>1.25 0.0083 TIMP3 NM_000362 </dd></dl>

<dl><dt>CAPG </dt><dd>1.25 0.0170 CAPG NM_001747 </dd></dl>

<dl><dt>IGFBP7 </dt><dd>1.25 0.0249 IGFBP7 NM_001553 </dd></dl>

<dl><dt>S100A1 </dt><dd>1.25 0.0529 S100A1 NM_006271 </dd></dl>

<dl><dt>SHC1 </dt><dd>1.25 0.0605 SHC1 NM_003029 </dd></dl>

<dl><dt>CTSB </dt><dd>1.25 0.0766 CTSB NM_001908 </dd></dl>

<dl><dt>ANXA5 </dt><dd>1.25 0.0787 ANXA5 NM_001154 </dd></dl>

<dl><dt>PKR2 </dt><dd>1.25 0.0800 PKM2 NM_002654 </dd></dl>

<dl><dt>HSPA1A </dt><dd>1.24 0.0003 HSPA1A NM_005345 </dd></dl>

<dl><dt>CGB </dt><dd>1.24 0.0148 CGB NM_000737 </dd></dl>

<dl><dt>DLC1 </dt><dd>1.24 0.0231 DLC1 NM_006094 </dd></dl>

<dl><dt>TMSB10 </dt><dd>1.24 0.0890 TMSB10 NM_021103 </dd></dl>

<dl><dt>LAMA3 </dt><dd>1.23 0.0017 LAMA3 NM_000227 </dd></dl>

<dl><dt>FOS </dt><dd>1.23 0.0028 FOS NM_005252 </dd></dl>

<dl><dt>SNAI2 </dt><dd>1.23 0.0123 SNAI2 NM_003068 </dd></dl>

<dl><dt>SPARC </dt><dd>1.23 0.0134 SPARC NM_003118 </dd></dl>

<dl><dt>SIR2 </dt><dd>1.23 0.0173 SIRT1 NM_012238 </dd></dl>

<dl><dt>KRT19 </dt><dd>1.23 0.0217 KRT19 NM_002276 </dd></dl>

<dl><dt>CTSD </dt><dd>1.23 0.0395 CTSD NM_001909 </dd></dl>

<dl><dt>EPAS1 </dt><dd>1.23 0.0409 EPAS1 NM_001430 </dd></dl>

<dl><dt>GAGE4 </dt><dd>1.23 0.0468 GAGE4 NM_001474 </dd></dl>

<dl><dt>BMP4 </dt><dd>1.22 0.0024 BMP4 NM_001202 </dd></dl>

<dl><dt>PLK3 </dt><dd>1.22 0.0056 PLK3 NM_004073 </dd></dl>

<dl><dt>Grb10 </dt><dd>1.22 0.0059 GRB10 NM_005311 </dd></dl>

<dl><dt>FYN </dt><dd>1.22 0.0120 FYN NM_002037 </dd></dl>

<dl><dt>STC1 </dt><dd>1.22 0.0409 STC1 NM_003155 </dd></dl>

<dl><dt>G-Catenin </dt><dd>1.22 0.0661 JUP NM_002230 </dd></dl>

<dl><dt>HK1 </dt><dd>1.22 0.0872 HK1 NM_000188 </dd></dl>

<dl><dt>MADH4 </dt><dd>1.22 0.0956 SMAD4 NM_005359 </dd></dl>

<dl><dt>KLK6 </dt><dd>1.21 0.0011 KLK6 NM_002774 </dd></dl>

<dl><dt>CTHRC1 </dt><dd>1.21 0.0065 CTHRC1 NM_138455 </dd></dl>

<dl><dt>THE T </dt><dd>1.21 0.0146 THE T NM_014387 </dd></dl>

<dl><dt>IGFBP3 </dt><dd>1.21 0.0149 IGFBP3 NM_000598 </dd></dl>

<dl><dt>AKT3 </dt><dd>1.21 0.0212 AKT3 NM_005465 </dd></dl>

<dl><dt>HSPA1B </dt><dd>1.21 0.0262 HSPA1B NM_005346 </dd></dl>

<dl><dt>THY1 </dt><dd>1.21 0.0278 THY1 NM_006288 </dd></dl>

<dl><dt>ANXA1 </dt><dd>1.21 0.0322 ANXA1 NM_000700 </dd></dl>

<dl><dt>LOX </dt><dd>1.20 0.0067 LOX NM_002317 </dd></dl>

<dl><dt>CD68 </dt><dd>1.20 0.0223 CD68 NM_001251 </dd></dl>

<dl><dt>EFNB2 </dt><dd>1.20 0.0268 EFNB2 NM_004093 </dd></dl>

<dl><dt>DYRK1B </dt><dd>1.20 0.0473 DYRK1B NM_004714 </dd></dl>

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<dl><dt>PTK2 </dt><dd>1.20 0.0889 PTK2 NM_005607 </dd></dl>

<dl><dt>THBS1 </dt><dd>1.19 0.0203 THBS1 NM_003246 </dd></dl>

<dl><dt>TAGLN </dt><dd>1.19 0.0263 TAGLN NM_003186 </dd></dl>

<dl><dt>TULP3 </dt><dd>1.19 0.0334 TULP3 NM_003324 </dd></dl>

<dl><dt>SR-A1 </dt><dd>1.19 0.0387 SR-A1 NM_021228 </dd></dl>

<dl><dt>APC </dt><dd>1.19 0.0433 APC NM_000038 </dd></dl>

<dl><dt>ERK1 </dt><dd>1.19 0.0488 Z11696 </dd></dl>

<dl><dt>VIM </dt><dd>1.19 0.0661 VIM NM_003380 </dd></dl>

<dl><dt>CREBBP </dt><dd>1.19 0.0802 CREBBP NM_004380 </dd></dl>

<dl><dt>ANGPT2 </dt><dd>1.19 0.0860 ANGPT2 NM_001147 </dd></dl>

<dl><dt>Maspina </dt><dd>1.18 0.0029 SERPINB5 NM_002639 </dd></dl>

<dl><dt>PDGFB </dt><dd>1.18 0.0252 PDGFB NM_002608 </dd></dl>

<dl><dt>S100A4 </dt><dd>1.18 0.0270 S100A4 NM_002961 </dd></dl>

<dl><dt>EGR1 </dt><dd>1.18 0.0334 EGR1 NM_001964 </dd></dl>

<dl><dt>IGFBP5 </dt><dd>1.18 0.0526 IGFBP5 NM_000599 </dd></dl>

<dl><dt>NOTCH2 </dt><dd>1.18 0.0527 NOTCH2 NM_024408 </dd></dl>

<dl><dt>PAI1 </dt><dd>1.17 0.0036 SERPINE1 NM_000602 </dd></dl>

<dl><dt>NR4A1 </dt><dd>1.17 0.0110 NR4A1 NM_002135 </dd></dl>

<dl><dt>BCAS1 </dt><dd>1.17 0.0137 BCAS1 NM_003657 </dd></dl>

<dl><dt>BRK </dt><dd>1.17 0.0137 PTK6 NM_005975 </dd></dl>

<dl><dt>AKAP12 </dt><dd>1.17 0.0195 AKAP12 NM_005100 </dd></dl>

<dl><dt>EMP1 </dt><dd>1.17 0.0291 EMP1 NM_001423 </dd></dl>

<dl><dt>SIAT4A </dt><dd>1.17 0.0304 ST3GAL1 NM_003033 </dd></dl>

<dl><dt>MRP3 </dt><dd>1.17 0.0334 ABCC3 NM_003786 </dd></dl>

<dl><dt>COL1A </dt><dd>1.17 0.0399 COL1A1 NM_000088 </dd></dl>

<dl><dt>Upa </dt><dd>1.17 0.0588 PLAU NM_002658 </dd></dl>

<dl><dt>UNC5B </dt><dd>1.17 0.0986 UNC5B NM_170744 </dd></dl>

<dl><dt>PDGFC </dt><dd>1.16 0.0355 PDGFC NM_016205 </dd></dl>

<dl><dt>MCP1 </dt><dd>1.16 0.0449 CCL2 NM_002982 </dd></dl>

<dl><dt>CTGF </dt><dd>1.16 0.0576 CTGF NM_001901 </dd></dl>

<dl><dt>COL1A2 </dt><dd>1.16 0.0612 COL1A2 NM_000089 </dd></dl>

<dl><dt>RAB32 </dt><dd>1.16 0.0645 RAB32 NM_006834 </dd></dl>

<dl><dt>SIN3A </dt><dd>1.16 0.0787 SIN3A NM_015477 </dd></dl>

<dl><dt>SKP1A </dt><dd>1.16 0.0837 SKP1A NM_006930 </dd></dl>

<dl><dt>EFNA1 </dt><dd>1.16 0.0957 EFNA1 NM_004428 </dd></dl>

<dl><dt>S100A2 </dt><dd>1.15 0.0040 S100A2 NM_005978 </dd></dl>

<dl><dt>MMP7 </dt><dd>1.15 0.0374 MMP7 NM_002423 </dd></dl>

<dl><dt>HOXB7 </dt><dd>1.15 0.0405 HOXB7 NM_004502 </dd></dl>

<dl><dt>FAP </dt><dd>1.15 0.0455 FAP NM_004460 </dd></dl>

<dl><dt>ANTXR1 </dt><dd>1.15 0.0482 ANTXR1 NM_032208 </dd></dl>

<dl><dt>TGFBI </dt><dd>1.15 0.0553 TGFBI NM_000358 </dd></dl>

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<dl><dt>TMEPAI </dt><dd>1.14 0.0435 TMEPAI NM_020182 </dd></dl>

<dl><dt>CYR61 </dt><dd>1.14 0.0490 CYR61 NM_001554 </dd></dl>

<dl><dt>SLPI </dt><dd>1.14 0.0724 SLPI NM_003064 </dd></dl>

<dl><dt>TP53I3 </dt><dd>1.14 0.0831 TP53I3 NM_004881 </dd></dl>

<dl><dt>PDGFA </dt><dd>1.14 0.0845 NM_002607 </dd></dl>

<dl><dt>SFRP2 </dt><dd>1.13 0.0255 SFRP2 NM_003013 </dd></dl>

<dl><dt>S100A8 </dt><dd>1.13 0.0693 S100A8 NM_002964 </dd></dl>

<dl><dt>F3 </dt><dd>1.13 0.0708 F3 NM_001993 </dd></dl>

<dl><dt>Bcl2 </dt><dd>1.13 0.0962 BCL2 NM_000633 </dd></dl>

<dl><dt>OPN_osteopontina </dt><dd>1.12 0.0097 SPP1 NM_000582 </dd></dl>

<dl><dt>FZD6 </dt><dd>1.12 0.0692 FZD6 NM_003506 </dd></dl>

<dl><dt>OSM </dt><dd>1.11 0.0744 OSM NM_020530 </dd></dl>

<dl><dt>EGLN3 </dt><dd>1.11 0.0884 EGLN3 NM_022073 </dd></dl>

<dl><dt>SIAT7B </dt><dd>1.11 0.0938 ST6GALNAC2 NM_006456 </dd></dl>

<dl><dt>FABP4 </dt><dd>1.10 0.0454 FABP4 NM_001442 </dd></dl>

<dl><dt>EFNA3 </dt><dd>1.10 0.0958 EFNA3 NM_004952 </dd></dl>

<dl><dt>MMP2 </dt><dd>1.10 0.0969 MMP2 NM_004530 </dd></dl>

<dl><dt>GSTT1 </dt><dd>1.09 0.0737 GSTT1 NM_000853 </dd></dl>

<dl><dt>REG4 </dt><dd>1.07 0.0286 REG4 NM_032044 </dd></dl>

Table 2B shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio &lt;1.0 and for which p &lt;0.1. A Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using OS as a metric for the clinical outcome.

Table 2B

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>HSPA8 </dt><dd>0.62 0.0145 HSPA8 NM_006597 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.70 0.0010 SKP2 NM_005983 </dd></dl>

<dl><dt>DHFR </dt><dd>0.74 0.0085 DHFR NM_000791 </dd></dl>

<dl><dt>PRDX4 </dt><dd>0.74 0.0197 PRDX4 NM_006406 </dd></dl>

<dl><dt>RRM1 </dt><dd>0.75 0.0162 RRM1 NM_001033 </dd></dl>

<dl><dt>SLC25A3 </dt><dd>0.75 0.0342 SLC25A3 NM_213611 </dd></dl>

<dl><dt>RPLPO </dt><dd>0.75 0.0416 RPLP0 NM_001002 </dd></dl>

<dl><dt>E2F1 </dt><dd>0.78 0.0190 E2F1 NM_005225 </dd></dl>

<dl><dt>SURV </dt><dd>0.79 0.0086 BIRC5 NM_001168 </dd></dl>

<dl><dt>c-myb (official MYB) </dt><dd>0.80 0.0020 MY B NM_005375 </dd></dl>

<dl><dt>BRCA1 </dt><dd>0.80 0.0077 BRCA1 NM_007295 </dd></dl>

<dl><dt>Chk1 </dt><dd>0.80 0.0186 CHEK1 NM_001274 </dd></dl>

<dl><dt>ST14 </dt><dd>0.80 0.0407 ST14 NM_021978 </dd></dl>

<dl><dt>TCF-1 </dt><dd>0.81 0.0045 TCF1 NM_000545 </dd></dl>

<dl><dt>CCNE2 </dt><dd>0.81 0.0112 CCNE2 NM_057749 </dd></dl>

<dl><dt>PPM1D </dt><dd>0.81 0.0194 PPM1D NM_003620 </dd></dl>

<dl><dt>CDC20 </dt><dd>0.81 0.0213 CDC20 NM_001255 </dd></dl>

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<dl><dt>IE24 </dt><dd>0.81 0.0585 IE24 NM_004879 </dd></dl>

<dl><dt>C20 orf1 </dt><dd>0.82 0.0348 TPX2 NM_012112 </dd></dl>

<dl><dt>DUT </dt><dd>0.83 0.0396 DUT NM_001948 </dd></dl>

<dl><dt>CD44E </dt><dd>0.83 0.0439 X55150 </dd></dl>

<dl><dt>KIF22 </dt><dd>0.83 0.0506 KIF22 NM_007317 </dd></dl>

<dl><dt>PPID </dt><dd>0.83 0.0615 PPID NM_005038 </dd></dl>

<dl><dt>UBE2M </dt><dd>0.83 0.0805 UBE2M NM_003969 </dd></dl>

<dl><dt>LMNB1 </dt><dd>0.83 0.0868 LMNB1 NM_005573 </dd></dl>

<dl><dt>MCM2 </dt><dd>0.84 0.0207 MCM2 NM_004526 </dd></dl>

<dl><dt>CDC6 </dt><dd>0.84 0.0218 CDC6 NM_001254 </dd></dl>

<dl><dt>MRPL40 </dt><dd>0.84 0.0769 MRPL40 NM_003776 </dd></dl>

<dl><dt>EPHB2 </dt><dd>0.85 0.0253 EPHB2 NM_004442 </dd></dl>

<dl><dt>CMYC </dt><dd>0.85 0.0371 MYC NM_002467 </dd></dl>

<dl><dt>AURKB </dt><dd>0.85 0.0375 AURKB NM_004217 </dd></dl>

<dl><dt>CDCA7 v2 </dt><dd>0.85 0.0421 CDCA7 NM_145810 </dd></dl>

<dl><dt>ABCB1 </dt><dd>0.86 0.0390 ABCB1 NM_000927 </dd></dl>

<dl><dt>SMARCA3 </dt><dd>0.86 0.0601 SMARCA3 NM_003071 </dd></dl>

<dl><dt>Cdx2 </dt><dd>0.88 0.0166 CDX2 NM_001265 </dd></dl>

<dl><dt>PPARG </dt><dd>0.88 0.0645 PPARG NM_005037 </dd></dl>

<dl><dt>MYBL2 </dt><dd>0.88 0.0647 MYBL2 NM_002466 </dd></dl>

<dl><dt>EREG </dt><dd>0.89 0.0411 EREG NM_001432 </dd></dl>

<dl><dt>AREG </dt><dd>0.90 0.0235 AREG NM_001657 </dd></dl>

Table 3A shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio> 1.0 and for which p <0.1. A Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using SLE as a metric for the clinical outcome.

Table 3A

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>ANXA2 </dt><dd>1.74 &lt;0.0001 ANXA2 NM_004039 </dd></dl>

<dl><dt>CYP3A4 </dt><dd>1.69 0.0020 CYP3A4 NM_017460 </dd></dl>

<dl><dt>RhoC </dt><dd>1.53 0.0009 RHOC NM_175744 </dd></dl>

<dl><dt>TJP1 </dt><dd>1.45 0.0787 TJP1 NM_003257 </dd></dl>

<dl><dt>UBC </dt><dd>1.43 0.0007 UBC NM_021009 </dd></dl>

<dl><dt>p21 </dt><dd>1.42 0.0004 CDKN1A NM_000389 </dd></dl>

<dl><dt>HB-EGF </dt><dd>1.39 0.0032 HBEGF NM_001945 </dd></dl>

<dl><dt>SPINT2 </dt><dd>1.37 0.0154 SPINT2 NM_021102 </dd></dl>

<dl><dt>HMLH </dt><dd>1.36 0.0711 MLH1 NM_000249 </dd></dl>

<dl><dt>VEGFC </dt><dd>1.35 0.0157 VEGFC NM_005429 </dd></dl>

<dl><dt>PKR2 </dt><dd>1.34 0.0187 PKM2 NM_002654 </dd></dl>

<dl><dt>LAMC2 </dt><dd>1.33 0.0002 LAMC2 NM_005562 </dd></dl>

<dl><dt>ITGB1 </dt><dd>1.33 0.0499 ITGB1 NM_002211 </dd></dl>

<dl><dt>TIMP1 </dt><dd>1.32 0.0007 TIMP1 NM_003254 </dd></dl>

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<dl><dt>VCL </dt><dd>1.31 0.0114 VCL NM_003373 </dd></dl>

<dl><dt>INHBB </dt><dd>1.31 0.0302 INHBB NM_002193 </dd></dl>

<dl><dt>GADD45B </dt><dd>1.30 &lt;0.0001 GADD45B NM_015675 </dd></dl>

<dl><dt>RhoB </dt><dd>1.30 0.0053 Rhob NM_004040 </dd></dl>

<dl><dt>DUSP1 </dt><dd>1.28 &lt;0.0001 DUSP1 NM_004417 </dd></dl>

<dl><dt>HK1 </dt><dd>1.28 0.0297 HK1 NM_000188 </dd></dl>

<dl><dt>GRIK1 </dt><dd>1.28 0.0364 GRIK1 NM_000830 </dd></dl>

<dl><dt>FOS </dt><dd>1.27 0.0002 FOS NM_005252 </dd></dl>

<dl><dt>CGB </dt><dd>1.27 0.0126 CGB NM_000737 </dd></dl>

<dl><dt>KLF6 </dt><dd>1.27 0.0288 KLF6 NM_001300 </dd></dl>

<dl><dt>ANXA5 </dt><dd>1.27 0.0504 ANXA5 NM_001154 </dd></dl>

<dl><dt>KRAS2 </dt><dd>1.27 0.0724 KRAS NM_004985 </dd></dl>

<dl><dt>INHBA </dt><dd>1.26 0.0009 INHBA NM_002192 </dd></dl>

<dl><dt>DLC1 </dt><dd>1.26 0.0096 DLC1 NM_006094 </dd></dl>

<dl><dt>IGFBP7 </dt><dd>1.26 0.0116 IGFBP7 NM_001553 </dd></dl>

<dl><dt>BGN </dt><dd>1.25 0.0039 BGN NM_001711 </dd></dl>

<dl><dt>LOXL2 </dt><dd>1.25 0.0076 LOXL2 NM_002318 </dd></dl>

<dl><dt>STC1 </dt><dd>1.25 0.0135 STC1 NM_003155 </dd></dl>

<dl><dt>CTSD </dt><dd>1.25 0.0208 CTSD NM_001909 </dd></dl>

<dl><dt>HSPG2 </dt><dd>1.25 0.0485 HSPG2 NM_005529 </dd></dl>

<dl><dt>KCNH2 iso a / b </dt><dd>1.25 0.0832 KCNH2 NM_000238 </dd></dl>

<dl><dt>TIMP3 </dt><dd>1.24 0.0057 TIMP3 NM_000362 </dd></dl>

<dl><dt>FXYD5 </dt><dd>1.24 0.0070 FXYD5 NM_014164 </dd></dl>

<dl><dt>A-Catenin </dt><dd>1.24 0.0447 CTNNA1 NM_001903 </dd></dl>

<dl><dt>LOX </dt><dd>1.23 0.0013 LOX NM_002317 </dd></dl>

<dl><dt>EGR1 </dt><dd>1.23 0.0037 EGR1 NM_001964 </dd></dl>

<dl><dt>CAPG </dt><dd>1.23 0.0191 CAPG NM_001747 </dd></dl>

<dl><dt>LAMB3 </dt><dd>1.23 0.0377 LAMB3 NM_000228 </dd></dl>

<dl><dt>GAGE4 </dt><dd>1.23 0.0402 GAGE4 NM_001474 </dd></dl>

<dl><dt>SHC1 </dt><dd>1.23 0.0640 SHC1 NM_003029 </dd></dl>

<dl><dt>MVP </dt><dd>1.23 0.0726 MVP NM_01745 </dd></dl>

<dl><dt>VEGF </dt><dd>1.22 0.0250 VEGF NM_003376 </dd></dl>

<dl><dt>UNC5B </dt><dd>1.22 0.0256 UNC5B NM_170744 </dd></dl>

<dl><dt>CDC42BPA </dt><dd>1.22 0.0297 CDC42BPA NM_003607 </dd></dl>

<dl><dt>SBA2 </dt><dd>1.22 0.0614 WSB2 NM_018639 </dd></dl>

<dl><dt>DKK1 </dt><dd>1.22 0.0689 DKK1 NM_012242 </dd></dl>

<dl><dt>EphB6 </dt><dd>1.22 0.0763 EPHB6 NM_004445 </dd></dl>

<dl><dt>IGFDP3 </dt><dd>1.21 0.0078 IGFBP3 NM_000598 </dd></dl>

<dl><dt>HSPA1B </dt><dd>1.21 0.0167 HSPA1B NM_005346 </dd></dl>

<dl><dt>CALD1 </dt><dd>1.21 0.0277 CALD1 NM_004342 </dd></dl>

<dl><dt>TIMP2 </dt><dd>1.21 0.0309 TIMP2 NM_003255 </dd></dl>

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<dl><dt>NR4A1 </dt><dd>1.20 0.0023 NR4A1 NM_002135 </dd></dl>

<dl><dt>LAMA3 </dt><dd>1.20 0.0028 LAMA3 NM_000227 </dd></dl>

<dl><dt>SIAT4A </dt><dd>1.20 0.0082 ST3GAL1 NM_003033 </dd></dl>

<dl><dt>PDGFB </dt><dd>1.20 0.0084 PDGFB NM_002608 </dd></dl>

<dl><dt>EMP1 </dt><dd>1.20 0.0107 EMP1 NM_001423 </dd></dl>

<dl><dt>THBS1 </dt><dd>1.20 0.0126 THBS1 NM_003246 </dd></dl>

<dl><dt>CD68 </dt><dd>1.20 0.0143 CD68 NM_001251 </dd></dl>

<dl><dt>FYN </dt><dd>1.20 0.0151 FYN NM_002037 </dd></dl>

<dl><dt>TULP3 </dt><dd>1.20 0.0213 TULP3 NM_003324 </dd></dl>

<dl><dt>EFNA1 </dt><dd>1.20 0.0254 EFNA1 NM_004428 </dd></dl>

<dl><dt>SIR2 </dt><dd>1.20 0.0255 SIRT1 NM_012238 </dd></dl>

<dl><dt>G-Catenin </dt><dd>1.20 0.0689 JUP NM_002230 </dd></dl>

<dl><dt>S100A1 </dt><dd>1.20 0.0998 S100A1 NM_006271 </dd></dl>

<dl><dt>Maspina </dt><dd>1.19 0.0013 SERPINB5 NM_002639 </dd></dl>

<dl><dt>HSPA1A </dt><dd>1.19 0.0013 HSPA1A NM_005345 </dd></dl>

<dl><dt>SPARC </dt><dd>1.19 0.0359 SPARC NM_003118 </dd></dl>

<dl><dt>PTHR1 </dt><dd>1.19 0.0801 PTHR1 NM_000316 </dd></dl>

<dl><dt>SNAI2 </dt><dd>1.18 0.0353 SNAI2 NM_003068 </dd></dl>

<dl><dt>KRT19 </dt><dd>1.18 0.0419 KRT19 NM_002276 </dd></dl>

<dl><dt>ERK1 </dt><dd>1.18 0.0459 Z11696 </dd></dl>

<dl><dt>KLK10 </dt><dd>1.17 0.0007 KLK10 NM_002776 </dd></dl>

<dl><dt>BMP4 </dt><dd>1.17 0.0121 BMP4 NM_001202 </dd></dl>

<dl><dt>CYR61 </dt><dd>1.17 0.0127 CYR61 NM_001554 </dd></dl>

<dl><dt>Grb10 </dt><dd>1.17 0.0216 GRB10 NM_005311 </dd></dl>

<dl><dt>PLK3 </dt><dd>1.17 0.0242 PLK3 NM_004073 </dd></dl>

<dl><dt>EFNB2 </dt><dd>1.17 0.0403 EFNB2 NM_004093 </dd></dl>

<dl><dt>P14ARF </dt><dd>1.17 0.0439 S78535 </dd></dl>

<dl><dt>ID3 </dt><dd>1.17 0.0446 ID3 NM_002167 </dd></dl>

<dl><dt>IGFBP5 </dt><dd>1.17 0.0503 IGFBP5 NM_000599 </dd></dl>

<dl><dt>THY1 </dt><dd>1.17 0.0574 THY1 NM_006288 </dd></dl>

<dl><dt>VIM </dt><dd>1.17 0.0858 VIM NM_003380 </dd></dl>

<dl><dt>EPAS1 </dt><dd>1.17 0.0897 EPAS1 NM_001430 </dd></dl>

<dl><dt>PAI1 </dt><dd>1.16 0.0039 SERPINE1 NM_000602 </dd></dl>

<dl><dt>F3 </dt><dd>1.16 0.0172 F3 NM_001993 </dd></dl>

<dl><dt>CTHRC1 </dt><dd>1.16 0.0181 CTHRC1 NM_138455 </dd></dl>

<dl><dt>ANTXR1 </dt><dd>1.16 0.0237 ANTXR1 NM_032208 </dd></dl>

<dl><dt>FAP </dt><dd>1.16 0.0289 FAP NM_004460 </dd></dl>

<dl><dt>ADAMTS12 </dt><dd>1.16 0.0350 ADAMTS12 NM_030955 </dd></dl>

<dl><dt>CTGF </dt><dd>1.16 0.0424 CTGF NM_001901 </dd></dl>

<dl><dt>PTGER3 </dt><dd>1.16 0.0569 PTGER3 NM_000957 </dd></dl>

<dl><dt>ANXA1 </dt><dd>1.16 0.0699 ANXA1 NM_000700 </dd></dl>

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<dl><dt>NRP1 </dt><dd>1.16 0.0797 NRP1 NM_003873 </dd></dl>

<dl><dt>NDRG1 </dt><dd>1.16 0.0856 NDRG1 NM_006096 </dd></dl>

<dl><dt>KLK6 </dt><dd>1.15 0.0092 KLK6 NM_002774 </dd></dl>

<dl><dt>EGR3 </dt><dd>1.15 0.0153 EGR3 NM_004430 </dd></dl>

<dl><dt>HOXB7 </dt><dd>1.15 0.0345 HOXB7 NM_004502 </dd></dl>

<dl><dt>PDGFC </dt><dd>1.15 0.0363 PDGFC NM_016205 </dd></dl>

<dl><dt>Herstatin </dt><dd>1.15 0.0403 AF177761 </dd></dl>

<dl><dt>MCP1 </dt><dd>1.15 0.0409 CCL2 NM_002982 </dd></dl>

<dl><dt>TGFBI </dt><dd>1.15 0.0437 TGFBI NM_000358 </dd></dl>

<dl><dt>TP53I3 </dt><dd>1.15 0.0438 TP53I3 NM_004881 </dd></dl>

<dl><dt>SLPI </dt><dd>1.15 0.0457 SLPI NM_003064 </dd></dl>

<dl><dt>PLAUR </dt><dd>1.15 0.0471 PLAUR NM_002659 </dd></dl>

<dl><dt>GJB2 </dt><dd>1.15 0.0610 GJB2 NM_004004 </dd></dl>

<dl><dt>COL1A1 </dt><dd>1.15 0.0647 COL1A1 NM_000088 </dd></dl>

<dl><dt>IL6 </dt><dd>1.15 0.0790 IL6 NM_000600 </dd></dl>

<dl><dt>APC </dt><dd>1.15 0.0821 APC NM_000038 </dd></dl>

<dl><dt>S100A2 </dt><dd>1.14 0.0048 S100A2 NM_005978 </dd></dl>

<dl><dt>TMEPAI </dt><dd>1.14 0.0300 TMEPAI NM_020182 </dd></dl>

<dl><dt>PDGFA </dt><dd>1.14 0.0644 NM_002607 </dd></dl>

<dl><dt>S100A4 </dt><dd>1.14 0.0680 S100A4 NM_002961 </dd></dl>

<dl><dt>TAGLN </dt><dd>1.14 0.0820 TAGLN NM_003186 </dd></dl>

<dl><dt>Upa </dt><dd>1.14 0.0823 PLAU NM_002658 </dd></dl>

<dl><dt>COL1A2 </dt><dd>1.14 0.0856 COL1A2 NM_000089 </dd></dl>

<dl><dt>OSM </dt><dd>1.13 0.0299 OSM NM_020530 </dd></dl>

<dl><dt>BRK </dt><dd>1.13 0.0479 PTK6 NM_005975 </dd></dl>

<dl><dt>SEMA3B </dt><dd>1.13 0.0525 SEMA3B NM_004636 </dd></dl>

<dl><dt>OPN_osteopontina </dt><dd>1.12 0.0084 SPP1 NM_000582 </dd></dl>

<dl><dt>S100P </dt><dd>1.12 0.0283 S100P NM_005980 </dd></dl>

<dl><dt>SFRP2 </dt><dd>1.12 0.0291 SFRP2 NM_003013 </dd></dl>

<dl><dt>EGLN3 </dt><dd>1.12 0.0465 EGLN3 NM_022073 </dd></dl>

<dl><dt>SIAT7B </dt><dd>1.12 0.0570 ST6GALNAC2 NM_006456 </dd></dl>

<dl><dt>MMP7 </dt><dd>1.12 0.0743 MMP7 NM_002423 </dd></dl>

<dl><dt>FABP4 </dt><dd>1.11 0.0195 FABP4 NM_001442 </dd></dl>

<dl><dt>AKAP12 </dt><dd>1.11 0.0899 AKAP12 NM_005100 </dd></dl>

<dl><dt>EFNA3 </dt><dd>1.10 0.0684 EFNA3 NM_004952 </dd></dl>

<dl><dt>SFRP4 </dt><dd>1.10 0.0684 SFRP4 NM_003014 </dd></dl>

<dl><dt>CRYAB </dt><dd>1.10 0.0987 CRYAB NM_001885 </dd></dl>

<dl><dt>GSTT1 </dt><dd>1.09 0.0457 GSTT1 NM_000853 </dd></dl>

<dl><dt>REG4 </dt><dd>1.08 0.0074 REG4 NM_032044 </dd></dl>

<dl><dt>pS2 </dt><dd>1.08 0.0302 TFF1 NM_003225 </dd></dl>

<dl><dt>MUC5B </dt><dd>1.08 0.0401 MUC5B XM_039877 </dd></dl>

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<figref>image 1</figref>

Table 3B shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio &lt;1.0 and for which p &lt;0.1. Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using SLE as a metric for the clinical outcome.

Table 3B

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>HSPA8 </dt><dd>0.70 0.0487 HSPA8 NM_006597 </dd></dl>

<dl><dt>SLC25A3 </dt><dd>0.71 0.0084 SLC25A3 NM_213611 </dd></dl>

<dl><dt>E2F1 </dt><dd>0.73 0.0019 E2F1 NM_005225 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.73 0.0038 SKP2 NM_005983 </dd></dl>

<dl><dt>PPM1D </dt><dd>0.75 0.0008 PPM1D NM_003620 </dd></dl>

<dl><dt>RRM1 </dt><dd>0.76 0.0161 RRM1 NM_001033 </dd></dl>

<dl><dt>RPLPO </dt><dd>0.76 0.0388 RPLP0 NM_001002 </dd></dl>

<dl><dt>NPM1 </dt><dd>0.78 0.0223 NPM1 NM_002520 </dd></dl>

<dl><dt>DDB1 </dt><dd>0.78 0.0673 DDB1 NM_001923 </dd></dl>

<dl><dt>PRDX4 </dt><dd>0.79 0.0526 PRDX4 NM_006406 </dd></dl>

<dl><dt>BRCA21 </dt><dd>0.80 0.0051 BRCA1 NM_007295 </dd></dl>

<dl><dt>Chk1 </dt><dd>0.80 0.0114 CHEK1 NM_001274 </dd></dl>

<dl><dt>SURV </dt><dd>0.81 0.0155 BIRC5 NM_001168 </dd></dl>

<dl><dt>C20orf1 </dt><dd>0.81 0.0195 TPX2 NM_012112 </dd></dl>

<dl><dt>IE24 </dt><dd>0.81 0.0382 IE24 NM_004879 </dd></dl>

<dl><dt>RAD54L </dt><dd>0.81 0.0501 RAD54L NM_003579 </dd></dl>

<dl><dt>DHFR </dt><dd>0.81 0.0530 DHFR NM_000791 </dd></dl>

<dl><dt>c-myb (official MYB) </dt><dd>0.82 0.0029 MY B NM_005375 </dd></dl>

<dl><dt>CCNE2 </dt><dd>0.82 0.0109 CCNE2 NM_057749 </dd></dl>

<dl><dt>KIF22 </dt><dd>0.82 0.0235 KIF22 NM_007317 </dd></dl>

<dl><dt>HMGB1 </dt><dd>0.82 0.0849 HMGB1 NM_002128 </dd></dl>

<dl><dt>LMNB1 </dt><dd>0.83 0.0665 LMNB1 NM_005573 </dd></dl>

<dl><dt>CDCA7 v2 </dt><dd>0.84 0.0224 CDCA7 NM_145810 </dd></dl>

<dl><dt>CDC20 </dt><dd>0.84 0.0461 CDC20 NM_001255 </dd></dl>

<dl><dt>FASN </dt><dd>0.84 0.0797 FASN NM_004104 </dd></dl>

<dl><dt>ABCB1 </dt><dd>0.85 0.0157 ABCB1 NM_000927 </dd></dl>

<dl><dt>MCM2 </dt><dd>0.85 0.0183 MCM2 NM_004526 </dd></dl>

<dl><dt>DUT </dt><dd>0.85 0.0469 DUT NM_001948 </dd></dl>

<dl><dt>KIF2C </dt><dd>0.85 0.0786 KIF2C NM_006845 </dd></dl>

<dl><dt>MCM6 </dt><dd>0.85 0.0791 MCM6 NM_005915 </dd></dl>

<dl><dt>EIF4E </dt><dd>0.85 0.0863 EIF4E NM_001968 </dd></dl>

<dl><dt>EPHB2 </dt><dd>0.86 0.0271 EPHB2 NM_004442 </dd></dl>

<dl><dt>RCC1 </dt><dd>0.86 0.0444 RCC1 NM_001269 </dd></dl>

<dl><dt>EFP </dt><dd>0.86 0.0760 TRIM25 NM_005082 </dd></dl>

<dl><dt>AREG </dt><dd>0.87 0.0029 AREG NM_001657 </dd></dl>

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<dl><dt>CMYC </dt><dd>0.87 0.0483 MYC NM_002467 </dd></dl>

<dl><dt>GCLC </dt><dd>0.87 0.0824 GCLC NM_001498 </dd></dl>

<dl><dt>TCF-1 </dt><dd>0.88 0.0520 TCF1 NM_000545 </dd></dl>

<dl><dt>MYBL2 </dt><dd>0.88 0.0527 MYBL2 NM_002466 </dd></dl>

<dl><dt>EREG </dt><dd>0.89 0.0237 EREG NM_001432 </dd></dl>

<dl><dt>Cdx2 </dt><dd>0.90 0.0353 CDX2 NM_001265 </dd></dl>

<dl><dt>PTPRO </dt><dd>0.92 0.0896 PTPRO NM_030667 </dd></dl>

<dl><dt>crypto (official TDGF1) </dt><dd>0.92 0.0913 TDGF1 NM_003212 </dd></dl>

<dl><dt>HLA-DRB1 </dt><dd>0.93 0.0536 HLA-DRB1 NM_002124 </dd></dl>

Table 4A shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio> 1.0 and for which p <0.1. A Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using ILRD as a metric for the clinical outcome.

Table 4A

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>ALDOA </dt><dd>3.37 0.0106 ALDOA NM_000034 </dd></dl>

<dl><dt>DCK </dt><dd>2.74 0.0130 DCK NM_000788 </dd></dl>

<dl><dt>ITGB1 </dt><dd>2.50 &lt;0.0001 ITGB1 NM_002211 </dd></dl>

<dl><dt>COX2 </dt><dd>2.15 0.0128 PTGS2 NM_000963 </dd></dl>

<dl><dt>TJP1 </dt><dd>2.12 0.0072 TJP1 NM_003257 </dd></dl>

<dl><dt>STAT3 </dt><dd>1.98 0.0062 STAT3 NM_003150 </dd></dl>

<dl><dt>HMLH </dt><dd>1.93 0.0087 MLH1 NM_000249 </dd></dl>

<dl><dt>CYP3A4 </dt><dd>1.90 0.0092 CYP3A4 NM_017460 </dd></dl>

<dl><dt>RhoC </dt><dd>1.89 0.0033 RHOC NM_175744 </dd></dl>

<dl><dt>ANXA2 </dt><dd>1.87 0.0025 ANXA2 NM_004039 </dd></dl>

<dl><dt>TIMP1 </dt><dd>1.83 &lt;0.0001 TIMP1 NM_003254 </dd></dl>

<dl><dt>WWOX </dt><dd>1.81 0.0288 WWOX NM_016373 </dd></dl>

<dl><dt>ANXA5 </dt><dd>1.80 0.0029 ANXA5 NM_001154 </dd></dl>

<dl><dt>FUS </dt><dd>1.79 0.0179 FUS NM_004960 </dd></dl>

<dl><dt>PADI4 </dt><dd>1.78 0.0168 PADI4 NM_012387 </dd></dl>

<dl><dt>RBX1 </dt><dd>1.71 0.0082 RBX1 NM_014248 </dd></dl>

<dl><dt>CRIP2 </dt><dd>1.71 0.0343 CRIP2 NM_001312 </dd></dl>

<dl><dt>HB-EGF </dt><dd>1.69 0.0013 HBEGF NM_001945 </dd></dl>

<dl><dt>KCNH2 iso a / b </dt><dd>1.69 0.0070 KCNH2 NM_000238 </dd></dl>

<dl><dt>SBA2 </dt><dd>1.68 0.0066 WSB2 NM_018639 </dd></dl>

<dl><dt>RhoB </dt><dd>1.67 0.0010 Rhob NM_004040 </dd></dl>

<dl><dt>VIM </dt><dd>1.66 0.0010 VIM NM_003380 </dd></dl>

<dl><dt>LILRB3 </dt><dd>1.66 0.0227 LILRB3 NM_006864 </dd></dl>

<dl><dt>UBC </dt><dd>1.64 0.0051 UBC NM_021009 </dd></dl>

<dl><dt>p21 </dt><dd>1.63 0.0032 CDKN1A NM_000389 </dd></dl>

<dl><dt>CCNE2 variant 1 </dt><dd>1.62 0.0363 CCNE2 NM_057749 </dd></dl>

<dl><dt>RAB6C </dt><dd>1.61 0.0107 RAB6C NM_032144 </dd></dl>

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<dl><dt>MSH3 </dt><dd>1.61 0.0213 MSH3 NM_002439 </dd></dl>

<dl><dt>AKT3 </dt><dd>1.59 0.0003 AKT3 NM_005465 </dd></dl>

<dl><dt>PI3K </dt><dd>1.58 0.0552 PIK3C2B NM_002646 </dd></dl>

<dl><dt>RAPIDS1 </dt><dd>1.57 0.0154 RAPIGDS1 NM_021159 </dd></dl>

<dl><dt>CTSB </dt><dd>1.57 0.0250 CTSB NM_001908 </dd></dl>

<dl><dt>PRDX6 </dt><dd>1.57 0.0770 PRDX6 NM_004905 </dd></dl>

<dl><dt>NRP2 </dt><dd>1.56 0.0005 NRP2 NM_003872 </dd></dl>

<dl><dt>DLC1 </dt><dd>1.56 0.0026 DLC1 NM_006094 </dd></dl>

<dl><dt>BGN </dt><dd>1.55 0.0006 BGN NM_001711 </dd></dl>

<dl><dt>SIR2 </dt><dd>1.55 0.0016 SIRT1 NM_012238 </dd></dl>

<dl><dt>CALD1 </dt><dd>1.53 0.0046 CALD1 NM_004342 </dd></dl>

<dl><dt>YWHAH </dt><dd>1.53 0.0429 YWHAH NM_003405 </dd></dl>

<dl><dt>CDC42 </dt><dd>1.52 0.0207 CDC42 NM_001791 </dd></dl>

<dl><dt>ITGA5 </dt><dd>1.51 0.0004 ITGA5 NM_002205 </dd></dl>

<dl><dt>KLF6 </dt><dd>1.51 0.0197 KLF6 NM_001300 </dd></dl>

<dl><dt>TLN1 </dt><dd>1.51 0.0414 TLN1 NM_006289 </dd></dl>

<dl><dt>LAMC2 </dt><dd>1.49 0.0017 LAMC2 NM_005562 </dd></dl>

<dl><dt>STC1 </dt><dd>1.49 0.0040 STC1 NM_003155 </dd></dl>

<dl><dt>CDC42HPA </dt><dd>1.49 0.0109 CDC42BPA NM_003607 </dd></dl>

<dl><dt>RBM5 </dt><dd>1.49 0.0184 RBM5 NM_005778 </dd></dl>

<dl><dt>INHBB </dt><dd>1.49 0.0310 INHBB NM_002193 </dd></dl>

<dl><dt>TGFBR1 </dt><dd>1.49 0.0502 TGFBR1 NM_004612 </dd></dl>

<dl><dt>ADAM10 </dt><dd>1.49 0.0819 ADAM10 NM_001110 </dd></dl>

<dl><dt>CEBPB </dt><dd>1.48 0.0399 CEBPB NM_005194 </dd></dl>

<dl><dt>AKT1 </dt><dd>1.48 0.0846 AKT1 NM_005163 </dd></dl>

<dl><dt>FYN </dt><dd>1.47 0.0036 FYN NM_002037 </dd></dl>

<dl><dt>ARG </dt><dd>1.47 0.0067 ABL2 NM_005158 </dd></dl>

<dl><dt>HIF1A </dt><dd>1.47 0.0221 HIF1A NM_001530 </dd></dl>

<dl><dt>S100A1 </dt><dd>1.47 0.0293 S100A1 NM_006271 </dd></dl>

<dl><dt>KRAS2 </dt><dd>1.47 0.0958 KRAS NM_004985 </dd></dl>

<dl><dt>CTHRC1 </dt><dd>1.46 0.0008 CTHRC1 NM_138455 </dd></dl>

<dl><dt>IGFBP7 </dt><dd>1.46 0.0173 IGFBP7 NM_001553 </dd></dl>

<dl><dt>ROCK1 </dt><dd>1.46 0.0326 ROCK1 NM_005406 </dd></dl>

<dl><dt>VEGFC </dt><dd>1.46 0.0516 VEGFC NM_005429 </dd></dl>

<dl><dt>EPAS1 </dt><dd>1.45 0.0316 EPAS1 NM_001430 </dd></dl>

<dl><dt>DUSP1 </dt><dd>1.44 0.0008 DUSP1 NM_004417 </dd></dl>

<dl><dt>FST </dt><dd>1.44 0.0340 FST NM_006350 </dd></dl>

<dl><dt>GADD45B </dt><dd>1.43 0.0013 GADD45B NM_015675 </dd></dl>

<dl><dt>FLT4 </dt><dd>1.43 0.0663 FLT4 NM_002020 </dd></dl>

<dl><dt>PTEN </dt><dd>1.43 0.0760 PTEN NM_000314 </dd></dl>

<dl><dt>FAP </dt><dd>1.42 0.0017 FAP NM_004460 </dd></dl>

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<dl><dt>PDGFC </dt><dd>1.42 0.0033 PDGFC NM_016205 </dd></dl>

<dl><dt>LOXL2 </dt><dd>1.42 0.0115 LOXL2 NM_002318 </dd></dl>

<dl><dt>Pak1 </dt><dd>1.42 0.0846 PAK1 NM_002576 </dd></dl>

<dl><dt>Grb10 </dt><dd>1.41 0.0020 GRB10 NM_005311 </dd></dl>

<dl><dt>INHBA </dt><dd>1.41 0.0036 INHBA NM_002192 </dd></dl>

<dl><dt>GJA1 </dt><dd>1.41 0.0039 GJA1 NM_000165 </dd></dl>

<dl><dt>CTGF </dt><dd>1.41 0.0053 CTGF NM_001901 </dd></dl>

<dl><dt>COL1A2 </dt><dd>1.41 0.0057 COL1A2 NM_000089 </dd></dl>

<dl><dt>PTK2 </dt><dd>1.40 0.0496 PTK2 NM_005607 </dd></dl>

<dl><dt>THBS1 </dt><dd>1.39 0.0059 THBS1 NM_003246 </dd></dl>

<dl><dt>RANBP9 </dt><dd>1.39 0.0333 RANBP9 NM_005493 </dd></dl>

<dl><dt>RANBP2 </dt><dd>1.39 0.0988 RANBP2 NM_006267 </dd></dl>

<dl><dt>ITGAV </dt><dd>1.38 0.0210 ITGAV NM_002210 </dd></dl>

<dl><dt>TIMP2 </dt><dd>1.38 0.0285 TIMP2 NM_003255 </dd></dl>

<dl><dt>PTHR1 </dt><dd>1.38 0.0297 PTHR1 NM_000316 </dd></dl>

<dl><dt>GADD45 </dt><dd>1.38 0.0340 GADD45A NM_001924 </dd></dl>

<dl><dt>c-ab1 </dt><dd>1.38 0.0526 ABL1 NM_005157 </dd></dl>

<dl><dt>EGR1 </dt><dd>1.37 0.0097 EGR1 NM_001964 </dd></dl>

<dl><dt>NCAM1 </dt><dd>1.37 0.0657 NCAM1 NM_000615 </dd></dl>

<dl><dt>VCL </dt><dd>1.37 0.0845 VCL NM_003373 </dd></dl>

<dl><dt>LOX </dt><dd>1.36 0.0026 LOX NM_002317 </dd></dl>

<dl><dt>SNAI2 </dt><dd>1.36 0.0178 SNAI2 NM_003068 </dd></dl>

<dl><dt>SPARC </dt><dd>1.36 0.0198 SPARC NM_003118 </dd></dl>

<dl><dt>CDH11 </dt><dd>1.36 0.0233 CDH11 NM_001797 </dd></dl>

<dl><dt>NFKBp50 </dt><dd>1.36 0.0767 NFKBI NM_003998 </dd></dl>

<dl><dt>CYR61 </dt><dd>1.35 0.0065 CYR61 NM_001554 </dd></dl>

<dl><dt>S100A4 </dt><dd>1.35 0.0104 S100A4 NM_002961 </dd></dl>

<dl><dt>TAGLN </dt><dd>1.35 0.0168 TAGLN NM_003186 </dd></dl>

<dl><dt>PCAF </dt><dd>1.34 0.0327 PCAF NM_003884 </dd></dl>

<dl><dt>NOTCH2 </dt><dd>1.34 0.0390 NOTCH2 NM_024408 </dd></dl>

<dl><dt>LRP5 </dt><dd>1.34 0.0722 LRP5 NM_002335 </dd></dl>

<dl><dt>YES </dt><dd>1.34 0.0787 YES NM_001041 </dd></dl>

<dl><dt>GBP2 </dt><dd>1.33 0.0139 GBP2 NM_004120 </dd></dl>

<dl><dt>Bcl2 </dt><dd>1.33 0.0143 BCL2 NM_000633 </dd></dl>

<dl><dt>MCP1 </dt><dd>1.33 0.0159 CCL2 NM_002982 </dd></dl>

<dl><dt>EPHA2 </dt><dd>1.33 0.0184 EPHA2 NM_004431 </dd></dl>

<dl><dt>PRKCA </dt><dd>1.33 0.0329 PRKCA NM_002737 </dd></dl>

<dl><dt>TIMP3 </dt><dd>1.33 0.0337 TIMP3 NM_000362 </dd></dl>

<dl><dt>ANGPT2 </dt><dd>1.33 0.0476 ANGPT2 NM_001147 </dd></dl>

<dl><dt>CTSD </dt><dd>1.33 0.0766 CTSD NM_001909 </dd></dl>

<dl><dt>SEMA3F </dt><dd>1.33 0.0931 SEMA3F NM_004186 </dd></dl>

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<dl><dt>BCAS1 </dt><dd>1.32 0.0044 BCAS1 NM_003657 </dd></dl>

<dl><dt>ANXA1 </dt><dd>1.32 0.0458 ANXA1 NM_000700 </dd></dl>

<dl><dt>KKT19 </dt><dd>1.32 0.0535 KRT19 NM_002276 </dd></dl>

<dl><dt>PTPRJ </dt><dd>1.32 0.0618 PTPRJ NM_002843 </dd></dl>

<dl><dt>GAPG </dt><dd>1.32 0.0641 CAPG NM_001747 </dd></dl>

<dl><dt>FOS </dt><dd>1.31 0.0129 FOS NM_005252 </dd></dl>

<dl><dt>COL1A1 </dt><dd>1.31 0.0236 COL1A1 NM_000088 </dd></dl>

<dl><dt>CXCR4 </dt><dd>1.31 0.0251 CXCR4 NM_003467 </dd></dl>

<dl><dt>TUBB </dt><dd>1.31 0.0354 TUBB2 NM_001069 </dd></dl>

<dl><dt>PIM1 </dt><dd>1.31 0.0373 PIM1 NM_002648 </dd></dl>

<dl><dt>IGFBP5 </dt><dd>1.31 0.0477 IGFBP5 NM_000599 </dd></dl>

<dl><dt>AP-1 (official JUN) </dt><dd>1.31 0.0519 JUN NM_002228 </dd></dl>

<dl><dt>GCNT1 </dt><dd>1.31 0.0534 GCNT1 NM_001490 </dd></dl>

<dl><dt>MAX </dt><dd>1.31 0.0650 MAX NM_002382 </dd></dl>

<dl><dt>PAI1 </dt><dd>1.30 0.0017 SERPINE1 NM_000602 </dd></dl>

<dl><dt>SLP1 </dt><dd>1.30 0.0176 SLPI NM_003064 </dd></dl>

<dl><dt>IGFBP3 </dt><dd>1.30 0.0320 IGFBP3 NM_000598 </dd></dl>

<dl><dt>DAPK1 </dt><dd>1.30 0.0402 DAPK1 NM_004938 </dd></dl>

<dl><dt>ID3 </dt><dd>1.30 0.0442 ID3 NM_002167 </dd></dl>

<dl><dt>EFNA1 </dt><dd>1.30 0.0623 EFNA1 NM_004428 </dd></dl>

<dl><dt>AKAP12 </dt><dd>1.29 0.0162 AKAP12 NM_005100 </dd></dl>

<dl><dt>PDGFB </dt><dd>1.29 0.0242 PDGFB NM_002608 </dd></dl>

<dl><dt>CD68 </dt><dd>1.29 0.0524 CD68 NM_001251 </dd></dl>

<dl><dt>FGFR1 </dt><dd>1.29 0.0709 FGFR1 NM_023109 </dd></dl>

<dl><dt>GSK3B </dt><dd>1.29 0.0765 GSK3B NM_002093 </dd></dl>

<dl><dt>CXCL12 </dt><dd>1.28 0.0129 CXCL12 NM_000609 </dd></dl>

<dl><dt>DPYD </dt><dd>1.28 0.0186 DPYD NM_000110 </dd></dl>

<dl><dt>LAMA3 </dt><dd>1.28 0.0193 LAMA3 NM_000227 </dd></dl>

<dl><dt>MRP3 </dt><dd>1.28 0.0384 ABCC3 NM_003786 </dd></dl>

<dl><dt>ABCC5 </dt><dd>1.28 0.0402 ABCC5 NM_005688 </dd></dl>

<dl><dt>PDGFA </dt><dd>1.28 0.0482 NM_002607 </dd></dl>

<dl><dt>XPA </dt><dd>1.28 0.0740 XPA NM_000380 </dd></dl>

<dl><dt>NDRG1 </dt><dd>1.28 0.0786 NDRG1 NM_006096 </dd></dl>

<dl><dt>FES </dt><dd>1.27 0.0458 FES NM_002005 </dd></dl>

<dl><dt>CTSL </dt><dd>1.27 0.0485 CTSL NM_001912 </dd></dl>

<dl><dt>IL6 </dt><dd>1.27 0.0606 IL6 NM_000600 </dd></dl>

<dl><dt>SFRP2 </dt><dd>1.26 0.0085 SFRP2 NM_003013 </dd></dl>

<dl><dt>Maspina </dt><dd>1.26 0.0096 SERPINB5 NM_002639 </dd></dl>

<dl><dt>TGFBI </dt><dd>1.26 0.0470 TGFBI NM_000358 </dd></dl>

<dl><dt>US3 </dt><dd>1.26 0.0978 US3 NM_000603 </dd></dl>

<dl><dt>HSPA1A </dt><dd>1.25 0.0161 HSPA1A NM_005345 </dd></dl>

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<dl><dt>S100A8 </dt><dd>1.25 0.0180 S100A8 NM_002964 </dd></dl>

<dl><dt>HOXB7 </dt><dd>1.25 0.0396 HOXB7 NM_004502 </dd></dl>

<dl><dt>P14ARF </dt><dd>1.25 0.0697 S78535 </dd></dl>

<dl><dt>WISP1 </dt><dd>1.25 0.0712 WISP1 NM_003882 </dd></dl>

<dl><dt>ID4 </dt><dd>1.25 0.0883 ID4 NM_001546 </dd></dl>

<dl><dt>SFRP4 </dt><dd>1.24 0.0200 SFRP4 NM_003014 </dd></dl>

<dl><dt>FZD6 </dt><dd>1.24 0.0220 FZD6 NM_003506 </dd></dl>

<dl><dt>EGR3 </dt><dd>1.24 0.0237 EGR3 NM_004430 </dd></dl>

<dl><dt>ALDH1A1 </dt><dd>1.24 0.0258 ALDH1A1 NM_000689 </dd></dl>

<dl><dt>CRYAB </dt><dd>1.23 0.0394 CRYAB NM_001885 </dd></dl>

<dl><dt>TGFB3 </dt><dd>1.23 0.0541 TGFB3 NM_003239 </dd></dl>

<dl><dt>ANTXR1 </dt><dd>1.23 0.0661 ANTXR1 NM_032208 </dd></dl>

<dl><dt>KLK6 </dt><dd>1.22 0.0211 KLK6 NM_002774 </dd></dl>

<dl><dt>ILT-2 </dt><dd>1.22 0.0676 LILRB1 NM_006669 </dd></dl>

<dl><dt>EMP1 </dt><dd>1.22 0.0871 EMP1 NM_001423 </dd></dl>

<dl><dt>PLAUR </dt><dd>1.22 0.0943 PLAUR NM_002659 </dd></dl>

<dl><dt>S100A2 </dt><dd>1.20 0.0100 S100A2 NM_005978 </dd></dl>

<dl><dt>MMP7 </dt><dd>1.19 0.0810 MMP7 NM_002423 </dd></dl>

<dl><dt>OPN_osteopontina </dt><dd>1.17 0.0231 SPP1 NM_000582 </dd></dl>

<dl><dt>FABP4 </dt><dd>1.17 0.0325 FABP4 NM_001442 </dd></dl>

<dl><dt>KLK10 </dt><dd>1.17 0.0452 KLK10 NM_002776 </dd></dl>

<dl><dt>PS2 </dt><dd>1.16 0.0140 TFF1 NM_003225 </dd></dl>

<dl><dt>STMY3 </dt><dd>1.15 0.0850 MMP11 NM_005940 </dd></dl>

<dl><dt>REG4 </dt><dd>1.14 0.0042 REG4 NM_032044 </dd></dl>

<dl><dt>MUC2 </dt><dd>1.09 0.0370 MUC2 NM_002457 </dd></dl>

Table 4B shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio &lt;1.0 and for which p &lt;0.1. A Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using ILRD as a metric for the clinical outcome.

Table 4B

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>HSPA8 </dt><dd>0.51 0.0261 HSPA8 NM_006597 </dd></dl>

<dl><dt>RPS13 </dt><dd>0.58 0.0089 RPS13 NM_001017 </dd></dl>

<dl><dt>RPLPO </dt><dd>0.63 0.0324 RPLP0 NM_001002 </dd></dl>

<dl><dt>NDUFS3 </dt><dd>0.66 0.0142 NDUFS3 NM_004551 </dd></dl>

<dl><dt>LMNB1 </dt><dd>0.67 0.0202 LMNB1 NM_005573 </dd></dl>

<dl><dt>ST14 </dt><dd>0.67 0.0206 ST14 NM_021978 </dd></dl>

<dl><dt>BRCA1 </dt><dd>0.68 0.0032 BRCA1 NM_007295 </dd></dl>

<dl><dt>TMSB4X </dt><dd>0.68 0.0075 TMSB4X NM_021109 </dd></dl>

<dl><dt>DHFR </dt><dd>0.68 0.0356 DHFR NM_000791 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.69 0.0248 SKP2 NM_005983 </dd></dl>

<dl><dt>TCF-1 </dt><dd>0.70 0.0015 TCF1 NM_000545 </dd></dl>

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<dl><dt>CDC20 </dt><dd>0.70 0.0067 CDC20 NM_001255 </dd></dl>

<dl><dt>SLC25A3 </dt><dd>0.70 0.0418 SLC25A3 NM_213611 </dd></dl>

<dl><dt>NME1 </dt><dd>0.72 0.0503 NME1 NM_000269 </dd></dl>

<dl><dt>RRM1 </dt><dd>0.72 0.0850 RRM1 NM_001033 </dd></dl>

<dl><dt>MCM2 </dt><dd>0.76 0.0168 MCM2 NM_004526 </dd></dl>

<dl><dt>ABC6 </dt><dd>0.76 0.0445 ABCC6 NM_001171 </dd></dl>

<dl><dt>CKS2 </dt><dd>0.76 0.0869 CKS2 NM_001827 </dd></dl>

<dl><dt>EPHB2 </dt><dd>0.77 0.0174 EPHB2 NM_004442 </dd></dl>

<dl><dt>C20 orf1 </dt><dd>0.77 0.0716 TPX2 NM_012112 </dd></dl>

<dl><dt>CSEL1 </dt><dd>0.77 0.0725 CSE1L NM_001316 </dd></dl>

<dl><dt>NFKBp65 </dt><dd>0.78 0.0957 RELAY NM_021975 </dd></dl>

<dl><dt>AURKB </dt><dd>0.79 0.0742 AURKB NM_004217 </dd></dl>

<dl><dt>CMYC </dt><dd>0.82 0.0901 MYC NM_002467 </dd></dl>

<dl><dt>Cdx2 </dt><dd>0.85 0.0510 CDX2 NM_001265 </dd></dl>

<dl><dt>EREG </dt><dd>0.85 0.0730 EREG NM_001432 </dd></dl>

<dl><dt>AREG </dt><dd>0.86 0.0365 AREG NM_001657 </dd></dl>

Table 5A shows associations between gene expression and ILR, controlling particular demographic and clinical characteristics of patients included in the analysis. All genes whose expression correlates with ILR (p <0.1) and that demonstrated a risk ratio> 1 are listed in a multi-variable analysis that includes the following variables: tumor location, surgery, tumor grade, nodes examined and number of positive nodes.

Table 5A

<dl><dt>Gen </dt><dd>RR LR square chi GL P value </dd></dl>

<dl><dt>RARB </dt><dd> 2,06780 4,23265 1 0,03965 </dd></dl>

<dl><dt>CYP3A4 </dt><dd> 1,85387 7,99462 1 0,00469 </dd></dl>

<dl><dt>ANXA2 </dt><dd> 1,80012 10,84166 1 0,00099 </dd></dl>

<dl><dt>COX2 </dt><dd> 1,79051 4,52307 1 0,03344 </dd></dl>

<dl><dt>RhoC </dt><dd> 1,73986 9,97133 1 0,00159 </dd></dl>

<dl><dt>MAPK14 </dt><dd> 1,68382 8,04253 1 0,00457 </dd></dl>

<dl><dt>UBC </dt><dd> 1,67323 11,69444 1 0,00063 </dd></dl>

<dl><dt>RhoB </dt><dd> 1,66612 15,92497 1 0,00007 </dd></dl>

<dl><dt>ITGB1 </dt><dd> 1,65796 8,18638 1 0,00422 </dd></dl>

<dl><dt>KRAS2 </dt><dd> 1,63873 6,80447 1 0,00909 </dd></dl>

<dl><dt>NTN1 </dt><dd> 1,61833 5,43469 1 0,01974 </dd></dl>

<dl><dt>ATP5E </dt><dd> 1,60990 4,93660 1 0,02629 </dd></dl>

<dl><dt>G Catenin </dt><dd> 1,58482 9,24422 1 000236 </dd></dl>

<dl><dt>STC1 </dt><dd> 1,58163 11,10757 1 0,00086 </dd></dl>

<dl><dt>SPINT2 </dt><dd> 1,52653 6,17276 1 0,01297 </dd></dl>

<dl><dt>Claudina 4 </dt><dd> 1,50290 12,29943 1 0,00045 </dd></dl>

<dl><dt>IGFBP7 </dt><dd> 1,48789 9,62569 1 0,00192 </dd></dl>

<dl><dt>NCAM1 </dt><dd> 1,48294 5,11428 1 0,02373 </dd></dl>

<dl><dt>TIMP1 </dt><dd> 1,46045 9,98492 1 0,00158 </dd></dl>

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<dl><dt>CEBPB </dt><dd> 1,46025 5,23659 1 0,02212 </dd></dl>

<dl><dt>KCNH2 iso a / b </dt><dd> 1,44616 3,97304 1 0,04623 </dd></dl>

<dl><dt>TMSB10 </dt><dd> 1,43107 4,65463 1 0,03097 </dd></dl>

<dl><dt>VEGFC </dt><dd> 1,41860 4,66904 1 0,03071 </dd></dl>

<dl><dt>HB-EGF </dt><dd> 1,41757 7,00399 1 000813 </dd></dl>

<dl><dt>FST </dt><dd> 1,41061 5,59674 1 0,01799 </dd></dl>

<dl><dt>LAMC2 </dt><dd> 1,40860 11,33997 1 0,00076 </dd></dl>

<dl><dt>GADD45B </dt><dd> 1,40671 12,26323 1 0,00046 </dd></dl>

<dl><dt>AKT3 </dt><dd> 1,40161 10,13028 1 0,00146 </dd></dl>

<dl><dt>EFNA1 </dt><dd> 1,40048 8,86645 1 0,00290 </dd></dl>

<dl><dt>p21 </dt><dd> 1,39939 5,42981 1 0,01980 </dd></dl>

<dl><dt>INHBA </dt><dd> 1,38204 11,03909 1 0,00089 </dd></dl>

<dl><dt>CALD1 </dt><dd> 1,38009 6,93406 1 0,00846 </dd></dl>

<dl><dt>DUSP1 </dt><dd> 1,36464 13,04379 1 0,00030 </dd></dl>

<dl><dt>HSPG2 </dt><dd> 1,36387 4,11749 1 0,04244 </dd></dl>

<dl><dt>GJB2 </dt><dd> 1,36358 8,42204 1 0,00371 </dd></dl>

<dl><dt>EPAS1 </dt><dd> 1,36323 4,74318 1 0,02941 </dd></dl>

<dl><dt>BGN </dt><dd> 1,35821 7,66947 1 0,00562 </dd></dl>

<dl><dt>TIMP2 </dt><dd> 1,35571 5,78791 1 0,01614 </dd></dl>

<dl><dt>To Catenina </dt><dd> 1,35566 4,35623 1 0,03687 </dd></dl>

<dl><dt>LOXL2 </dt><dd> 1,35470 7,23663 1 0,00714 </dd></dl>

<dl><dt>DKK1 </dt><dd> 1,35126 3,88504 1 0,04872 </dd></dl>

<dl><dt>ITGAV </dt><dd> 1,34899 8,03554 1 0,00459 </dd></dl>

<dl><dt>CGB </dt><dd> 1,34840 7,06221 1 0,00787 </dd></dl>

<dl><dt>EGR1 </dt><dd> 1,33424 8,41855 1 0,00371 </dd></dl>

<dl><dt>TIMP3 </dt><dd> 1,33197 6,28550 1 0,01217 </dd></dl>

<dl><dt>VIM </dt><dd> 1,33196 4,92198 1 0,02652 </dd></dl>

<dl><dt>TGFBI </dt><dd> 1,32511 8,30278 1 0,00396 </dd></dl>

<dl><dt>FXYD5 </dt><dd> 1,32500 6,22751 1 0,01258 </dd></dl>

<dl><dt>VEGF </dt><dd> 1,32291 4,93825 1 0,02627 </dd></dl>

<dl><dt>ADAMTS12 </dt><dd> 1,31794 7,46749 1 0,00628 </dd></dl>

<dl><dt>SLP1 </dt><dd> 1,31565 8,38324 1 0,00379 </dd></dl>

<dl><dt>DLC1 </dt><dd> 1,30862 5,51638 1 0,01884 </dd></dl>

<dl><dt>HOXB7 </dt><dd> 1,30822 8,04076 1 0,00457 </dd></dl>

<dl><dt>TMEPAI </dt><dd> 1,30395 8,43736 1 0,00368 </dd></dl>

<dl><dt>IGFBP5 </dt><dd> 1,30260 5,44022 1 0,01968 </dd></dl>

<dl><dt>CDC42BPA </dt><dd> 1,30167 4,20771 1 0,04024 </dd></dl>

<dl><dt>PDGFA </dt><dd> 1,29760 5,54964 1 0,01848 </dd></dl>

<dl><dt>GSTp </dt><dd> 1,29594 3,96268 1 0,04652 </dd></dl>

<dl><dt>FOS </dt><dd> 1,29427 8,42847 1 0,00369 </dd></dl>

<dl><dt>PDGFC </dt><dd> 1,28813 6,81737 1 0,00903 </dd></dl>

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<dl><dt>IGFBP3 </dt><dd> 1,28701 6,33625 1 0,01183 </dd></dl>

<dl><dt>LOX </dt><dd> 1,28433 8,15598 1 0,00429 </dd></dl>

<dl><dt>SPARC </dt><dd> 1,28260 4,75876 1 0,02915 </dd></dl>

<dl><dt>EFNB2 </dt><dd> 1,27720 4,71247 1 0,02994 </dd></dl>

<dl><dt>Maspina </dt><dd> 1,27645 10,57657 1 0,00115 </dd></dl>

<dl><dt>THBS1 </dt><dd> 1,27619 6,61087 1 0,01014 </dd></dl>

<dl><dt>TAGLN </dt><dd> 1,26904 5,15123 1 0,02323 </dd></dl>

<dl><dt>VEGF_altsplice1 </dt><dd> 1,26734 5,29282 1 0,02141 </dd></dl>

<dl><dt>S100P </dt><dd> 1,26586 9,88713 1 0,00166 </dd></dl>

<dl><dt>HSPA1A </dt><dd> 1,26209 8,59704 1 0,00337 </dd></dl>

<dl><dt>MAD </dt><dd> 1,26112 3,96163 1 0,04655 </dd></dl>

<dl><dt>ANGPT2 </dt><dd> 1,25701 3,91148 1 0,04796 </dd></dl>

<dl><dt>PRKCA </dt><dd> 1,24853 4,69452 1 0,03026 </dd></dl>

<dl><dt>F3 </dt><dd> 1,24848 5,06788 1 0,02437 </dd></dl>

<dl><dt>FAP </dt><dd> 1,24657 5,19589 1 0,02264 </dd></dl>

<dl><dt>BRK </dt><dd> 1,24507 5,44048 1 0,01968 </dd></dl>

<dl><dt>CD68 </dt><dd> 1,23943 4,02530 1 0,04482 </dd></dl>

<dl><dt>NR4A1 </dt><dd> 1,23772 7,09548 1 0,00773 </dd></dl>

<dl><dt>CTHRC1 </dt><dd> 1,23465 5,21100 1 0,02244 </dd></dl>

<dl><dt>SLC2A1 </dt><dd> 1,22967 5,22364 1 0,02228 </dd></dl>

<dl><dt>Grb10 </dt><dd> 1,22209 4,12811 1 0,04218 </dd></dl>

<dl><dt>p16-INK4 </dt><dd> 1,21325 4,44296 1 0,03505 </dd></dl>

<dl><dt>MDK </dt><dd> 1,21116 5,25025 1 0,02194 </dd></dl>

<dl><dt>CYR61 </dt><dd> 1,19995 4,14452 1 0,04177 </dd></dl>

<dl><dt>LAMA3 </dt><dd> 1,19794 4,33073 1 0,03743 </dd></dl>

<dl><dt>FOXO3A </dt><dd> 1,19557 4,20079 1 0,04041 </dd></dl>

<dl><dt>EFNA3 </dt><dd> 1,19439 5,51728 1 0,01883 </dd></dl>

<dl><dt>CRYAB </dt><dd> 1,17514 3,90435 1 0,04816 </dd></dl>

<dl><dt>CEACAM6 </dt><dd> 1,16804 3,96486 1 0,04646 </dd></dl>

<dl><dt>OPN_osteopontina </dt><dd> 1,16112 5,50891 1 0,01892 </dd></dl>

<dl><dt>KLKIO </dt><dd> 1,15851 5,65625 1 0,01739 </dd></dl>

<dl><dt>SFRP2 </dt><dd> 1,15773 4,02893 1 0,04473 </dd></dl>

<dl><dt>KLK6 </dt><dd> 1,15163 4,65953 1 0,03088 </dd></dl>

<dl><dt>S100A2 </dt><dd> 1,14185 3,94284 1 0,04707 </dd></dl>

<dl><dt>REG4 </dt><dd> 1,09037 4,16995 1 0,04115 </dd></dl>

Table 5B shows associations between gene expression and ILR, controlling particular demographic and clinical characteristics of patients included in the analysis. All genes whose expression correlates with ILR (p &lt;0.1) and which demonstrated a risk ratio &lt;1 are listed in a multi-variable analysis that includes the following variables: tumor location, surgery, tumor grade, nodes examined and number of positive nodes.

Table 5B

<figref>image2</figref>

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<dl><dt>BFGF </dt><dd> 0,46674 6,95233 1 0,00837 </dd></dl>

<dl><dt>Fasl </dt><dd> 0,47324 4,08714 1 0,04321 </dd></dl>

<dl><dt>KLRK1 </dt><dd> 0,63331 10,28820 1 0,00134 </dd></dl>

<dl><dt>DHFR </dt><dd> 0,64947 7,64434 1 0,00570 </dd></dl>

<dl><dt>BRCA1 </dt><dd> 0,65247 15,21566 1 0,00010 </dd></dl>

<dl><dt>SLC25A3 </dt><dd> 0,67480 5,72977 1 0,01668 </dd></dl>

<dl><dt>RAD54L </dt><dd> 0,68215 5,38684 1 0,02029 </dd></dl>

<dl><dt>PPMID </dt><dd> 0,68777 10,02879 1 0,00154 </dd></dl>

<dl><dt>CD80 </dt><dd> 0,69347 8,70087 1 0,00318 </dd></dl>

<dl><dt>ATP5A1 </dt><dd> 0,70467 4,06718 1 0,04372 </dd></dl>

<dl><dt>PRKCB1 </dt><dd> 0,73152 5,21950 1 0,02234 </dd></dl>

<dl><dt>KIF22 </dt><dd> 0,73945 5,13202 1 0,02349 </dd></dl>

<dl><dt>Chk1 </dt><dd> 0,75865 4,38139 1 0,03633 </dd></dl>

<dl><dt>TRAIL </dt><dd> 0,76430 4,12533 1 0,04225 </dd></dl>

<dl><dt>CDC20 </dt><dd> 0,77071 5,04557 1 0,02469 </dd></dl>

<dl><dt>DUT </dt><dd> 0,78196 4,13381 1 0,04203 </dd></dl>

<dl><dt>ABCB1 </dt><dd> 0,79434 5,33783 1 0,02087 </dd></dl>

<dl><dt>UMPS </dt><dd> 0,80011 4,65425 1 0,03098 </dd></dl>

<dl><dt>ING5 </dt><dd> 0,80230 4,04085 1 0,04441 </dd></dl>

<dl><dt>CMYC </dt><dd> 0,80757 4,26709 1 0,03886 </dd></dl>

<dl><dt>GBP1 </dt><dd> 0,83015 3,98302 1 0,04596 </dd></dl>

<dl><dt>AREG </dt><dd> 0,86091 4,94239 1 0,02621 </dd></dl>

Table 6 shows associations between gene expression and clinical outcome based on a nonlinear proportional hazard analysis, using a natural spline curve of 2 degrees of freedom. All genes that demonstrated a deviation from a strictly linear relationship (p &lt;0.05) with ILR in patients in

5 stage II (Duke B) and state III (Duke C) combined. The relationship between gene expression and ILR was not constant over the entire observed range of expression values ​​in the study, for example increases in gene expression may have been related to increases in the duration of ILR in a part of the observed range. and with decreases in the duration of ILR in a different part of the interval.

10 Table 6

<dl><dt>Gen </dt><dd>P value Official symbol Registry number </dd></dl>

<dl><dt>PTHLH </dt><dd>0.001 PTHLH NM_002820 </dd></dl>

<dl><dt>CDCA7 v2 </dt><dd>0.002 CDCA7 NM_145810 </dd></dl>

<dl><dt>CREBBP </dt><dd>0.002 CREBBP NM_004380 </dd></dl>

<dl><dt>KLF5 </dt><dd>0.002 KLF5 NM_001730 </dd></dl>

<dl><dt>LAMB3 </dt><dd>0.004 LAMB3 NM_000228 </dd></dl>

<dl><dt>TGFBR1 </dt><dd>0.005 TGFBR1 NM_004612 </dd></dl>

<dl><dt>NR4A1 </dt><dd>0.005 NR4A1 NM_002135 </dd></dl>

<dl><dt>Upa </dt><dd>0.005 PLAU NM_002658 </dd></dl>

<dl><dt>Cad17 </dt><dd>0.007 CDH17 NM_004063 </dd></dl>

<dl><dt>S100A4 </dt><dd>0.008 S100A4 NM_002961 </dd></dl>

<dl><dt>A-Catenin </dt><dd>0.008 CTNNA1 NM_001903 </dd></dl>

<dl><dt>EPHB2 </dt><dd>0.009 EPHB2 NM_004442 </dd></dl>

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<dl><dt>Axina2 </dt><dd>0.011 AXIN2 NM_004655 </dd></dl>

<dl><dt>PTPRJ </dt><dd>0.011 PTPRJ NM_002843 </dd></dl>

<dl><dt>CAPN1 </dt><dd>0.012 CAPN1 NM_005186 </dd></dl>

<dl><dt>CEGP1 </dt><dd>0.013 SCUBE2 NM_020974 </dd></dl>

<dl><dt>APOC1 </dt><dd>0.013 APOC1 NM_001645 </dd></dl>

<dl><dt>GHP1 </dt><dd>0.015 GBP1 NM_002053 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.016 SKP2 NM_005983 </dd></dl>

<dl><dt>ATP5E </dt><dd>0.016 ATP5E NM_006886 </dd></dl>

<dl><dt>GRIK1 </dt><dd>0.017 GRIK1 NM_000830 </dd></dl>

<dl><dt>PRKR </dt><dd>0.018 EIF2AK2 NM_002759 </dd></dl>

<dl><dt>FUT6 </dt><dd>0.020 FUT6 NM_000150 </dd></dl>

<dl><dt>NFP2 </dt><dd>0.020 NFP2 NM_053024 </dd></dl>

<dl><dt>ITGB4 </dt><dd>0.021 ITGB4 NM_000213 </dd></dl>

<dl><dt>MADH7 </dt><dd>0.021 SMAD7 NM_005904 </dd></dl>

<dl><dt>RALBP1 </dt><dd>0.021 RALBP1 NM_006788 </dd></dl>

<dl><dt>AKT1 </dt><dd>0.022 AKT1 NM_005163 </dd></dl>

<dl><dt>KLK6 </dt><dd>0.022 KLK6 NM_002774 </dd></dl>

<dl><dt>PLK </dt><dd>0.023 PLK1 NM_005030 </dd></dl>

<dl><dt>CYP2C8 </dt><dd>0.025 CYP2C8 NM_000770 </dd></dl>

<dl><dt>BTF3 </dt><dd>0.026 BTF3 NM_001207 </dd></dl>

<dl><dt>CCNE2 variant 1 </dt><dd>0.026 CCNE2 NM_057749 </dd></dl>

<dl><dt>STMY3 </dt><dd>0.030 MMP11 NM_005940 </dd></dl>

<dl><dt>NRP1 </dt><dd>0.030 NRP1 NM_003873 </dd></dl>

<dl><dt>SIAT4A </dt><dd>0.031 ST3GAL1 NM_003033 </dd></dl>

<dl><dt>SEMA3B </dt><dd>0.033 SEMA3B NM_004636 </dd></dl>

<dl><dt>TRAG3 </dt><dd>0.033 CSAG2 NM_004909 </dd></dl>

<dl><dt>HSPE1 </dt><dd>0.035 HSPE1 NM_002157 </dd></dl>

<dl><dt>SBA2 </dt><dd>0.036 WSB2 NM_018639 </dd></dl>

<dl><dt>TK1 </dt><dd>0.036 TK1 NM_003258 </dd></dl>

<dl><dt>CCNB2 </dt><dd>0.037 CCNB2 NM_004701 </dd></dl>

<dl><dt>TMEPAI </dt><dd>0.037 TMEPAI NM_020182 </dd></dl>

<dl><dt>SPRY2 </dt><dd>0.037 SPRY2 NM_005842 </dd></dl>

<dl><dt>AGXT </dt><dd>0.038 AGXT NM_000030 </dd></dl>

<dl><dt>ALCAM </dt><dd>0.038 ALCAM NM_001627 </dd></dl>

<dl><dt>HSPCA </dt><dd>0.038 HSPCA NM_005348 </dd></dl>

<dl><dt>TIMP3 </dt><dd>0.038 TIMP3 NM_000362 </dd></dl>

<dl><dt>DET1 </dt><dd>0.039 DET1 NM_017996 </dd></dl>

<dl><dt>tusc4 </dt><dd>0.040 TUSC4 NM_006545 </dd></dl>

<dl><dt>SNAI2 </dt><dd>0.040 SNAI2 NM_003068 </dd></dl>

<dl><dt>CD28 </dt><dd>0.040 CD28 NM_006139 </dd></dl>

<dl><dt>RNF11 </dt><dd>0.041 RNF11 NM_014372 </dd></dl>

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<dl><dt>PAI1 </dt><dd>0.042 SERPINE1 NM_000602 </dd></dl>

<dl><dt>XRCC1 </dt><dd>0.042 XRCC1 NM_006297 </dd></dl>

<dl><dt>EGLN1 </dt><dd>0.044 EGLN1 NM_022051 </dd></dl>

<dl><dt>EGFR </dt><dd>0.044 EGFR NM_005228 </dd></dl>

<dl><dt>HES6 </dt><dd>0.044 HES6 NM_018645 </dd></dl>

<dl><dt>KCNK4 </dt><dd>0.045 KCNK4 NM_016611 </dd></dl>

<dl><dt>CXCR4 </dt><dd>0.047 CXCR4 NM_003467 </dd></dl>

<dl><dt>PTP4A3 </dt><dd>0.048 PTP4A3 NM_007079 </dd></dl>

<dl><dt>p27 </dt><dd>0.048 CDKNIB NM_004064 </dd></dl>

<dl><dt>MADH4 </dt><dd>0.049 SMAD4 NM_005359 </dd></dl>

<dl><dt>ICAM1 </dt><dd>0.049 ICAM1 NM_000201 </dd></dl>

Table 7 shows all the genes that have an interaction (p value &lt;0.05) with the tumor stage. Data were modeled using a proportional hazard model of ILR with gene expression, tumor stage and their interaction as predictive factors.

Table 7

<dl><dt>Gen </dt><dd>Stage II RR Stage III RR P value for interaction </dd></dl>

<dl><dt>ICAM2 </dt><dd> 1,49 0,68 0,0019 </dd></dl>

<dl><dt>CD24 </dt><dd> 1,26 0,84 0,0054 </dd></dl>

<dl><dt>PRDX6 </dt><dd> 2,29 0,73 0,0058 </dd></dl>

<dl><dt>HSD17B2 </dt><dd> 0,62 1,29 0,0072 </dd></dl>

<dl><dt>ALCAM </dt><dd> 1,61 0,94 0,0088 </dd></dl>

<dl><dt>SIR2 </dt><dd> 2,02 1,09 0,0089 </dd></dl>

<dl><dt>NUFIP1 </dt><dd> 1,32 0,79 0,0093 </dd></dl>

<dl><dt>EMR3 </dt><dd> 2,14 0,57 0,0127 </dd></dl>

<dl><dt>CDC20 </dt><dd> 0,56 0,98 0,0130 </dd></dl>

<dl><dt>MT3 </dt><dd> 1,37 0,79 0,0134 </dd></dl>

<dl><dt>CLTC </dt><dd> 1,80 0,71 0,0144 </dd></dl>

<dl><dt>CYR61 </dt><dd> 1,73 1,10 0,0145 </dd></dl>

<dl><dt>WIF </dt><dd> 1,34 0,78 0,0195 </dd></dl>

<dl><dt>TFF3 </dt><dd> 1,23 0,90 0,0209 </dd></dl>

<dl><dt>SOS1 </dt><dd> 1,46 0,79 0,0287 </dd></dl>

<dl><dt>TMSB4X </dt><dd> 1,34 0,74 0,0293 </dd></dl>

<dl><dt>CENPE </dt><dd> 3,05 0,85 0,0330 </dd></dl>

<dl><dt>CDH11 </dt><dd> 1,49 0,96 0,0339 </dd></dl>

<dl><dt>CAPG </dt><dd> 0,90 1,50 0,0348 </dd></dl>

<dl><dt>TP53HP1 </dt><dd> 1,54 0,93 0,0357 </dd></dl>

<dl><dt>MGAT5 </dt><dd> 1,25 0,73 0,0362 </dd></dl>

<dl><dt>MADH2 </dt><dd> 1,36 0,70 0,0393 </dd></dl>

<dl><dt>LOX </dt><dd> 1,58 1,11 0,0396 </dd></dl>

<dl><dt>DKK1 </dt><dd> 0,87 1,55 0,0415 </dd></dl>

<dl><dt>CKSIB </dt><dd> 0,31 1,75 0,0467 </dd></dl>

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<dl><dt>MMP7 </dt><dd> 0,92 1,28 0,0471 </dd></dl>

<dl><dt>STAT5B </dt><dd> 1,28 0,86 0,0471 </dd></dl>

<dl><dt>CD28 </dt><dd> 0,69 1,25 0,0472 </dd></dl>

Results of the second analysis study

The set of reference genes for the second analysis was ATP5E, CLTC, GPX1, NEDD8, PGK1, UBB.

5 Table 1.2A shows associations for genes whose increased expression is predictive of a shorter recurrence free interval (ILR) based on the analysis of proportional hazards of a variable.

Table 1.2B shows associations for genes whose increased expression is predictive of a longer recurrence interval (ILR) longer based on the analysis of proportional hazards of a variable.

Table 2.2A shows associations for genes whose increased expression is predictive of a decreased overall survival rate (OS) based on the analysis of proportional hazards of a variable.

fifteen Table 2.2B shows associations for genes whose increased expression is predictive of an increased overall survival rate (OS) based on the analysis of proportional hazards of a variable.

Table 3.2A shows associations for genes whose increased expression is predictive of a decreased disease-free survival rate (SLE) based on the analysis of proportional hazards of a variable.

twenty Table 3.2B shows associations for genes whose increased expression is predictive of an increased disease-free survival rate (SLE) based on the analysis of proportional hazards of a variable.

Table 4.2A shows associations for genes whose increased expression is predictive of a shorter distance recurrence interval (ILRD) shorter based on the analysis of proportional hazards of a variable.

Table 4.2B shows associations for genes whose increased expression is predictive of a longer distance-free recurrence interval (ILRD) based on the analysis of proportional hazards of a variable.

30 Table 5.2A shows associations between gene expression and ILR for genes whose increased expression is predictive of a shorter recurrence free interval (ILR), based on a multi-variable analysis that controls particular demographic and clinical characteristics of patients included in the study. analysis.

Table 5.2B shows associations between gene expression and ILR for genes whose increased expression is predictive of a longer recurrence free interval (ILR), based on a multivariate analysis that controls particular demographic and clinical characteristics of patients included in the analysis.

Table 6.2 shows genes for which an association between gene expression and clinical outcome was identified based on a nonlinear proportional hazard analysis, using a natural spline curve of 2 degrees 40 of freedom.

Table 7.2 shows all genes that have an interaction (p value &lt;0.05) with the tumor stage.

Table 1.2A shows associations between clinical outcome and gene expression for genes that demonstrated a

Four. Five risk ratio> 1.0 and for which p <0.1. Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using ILR as a metric for the clinical outcome.

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>RARB </dt><dd>2.22 0.0294 RARB NM_016152 </dd></dl>

<dl><dt>ITGB1 </dt><dd>2.04 0.0002 ITGB1 NM_002211 </dd></dl>

<dl><dt>ANXA2 </dt><dd>1.78 0.0003 ANXA2 NM_004039 </dd></dl>

<dl><dt>CYP3A4 </dt><dd>1.68 0.0075 CYP3A4 NM_017460 </dd></dl>

<dl><dt>COX2 </dt><dd>1.64 0.0604 PTGS2 NM_000963 </dd></dl>

<dl><dt>KRAS2 </dt><dd>1.62 0.0064 KRAS NM_004985 </dd></dl>

<dl><dt>TJP1 </dt><dd>1.58 0.0751 TJP1 NM_003257 </dd></dl>

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<dl><dt>KIAA0125 </dt><dd>1.58 0.0889 KIAA0125 NM_014792 </dd></dl>

<dl><dt>RhoB </dt><dd>1.57 0.0002 Rhob NM_004040 </dd></dl>

<dl><dt>RhoC </dt><dd>1.56 0.0059 RHOC NM_175744 </dd></dl>

<dl><dt>NTN1 </dt><dd>1.54 0.0336 NTN1 NM_004822 </dd></dl>

<dl><dt>ANXA5 </dt><dd>1.52 0.0086 ANXA5 NM_001154 </dd></dl>

<dl><dt>TIMP1 </dt><dd>1.52 &lt;0.0001 TIMP1 NM_003254 </dd></dl>

<dl><dt>AKT3 </dt><dd>1.50 &lt;0.0001 AKT3 NM_005465 </dd></dl>

<dl><dt>CALD1 </dt><dd>1.48 0.0007 CALD1 NM_004342 </dd></dl>

<dl><dt>IGFBP7 </dt><dd>1.46 0.0023 IGFBP7 NM_001553 </dd></dl>

<dl><dt>CYP1B1 </dt><dd>1.45 0.0222 CYP1B1 NM_000104 </dd></dl>

<dl><dt>BGN </dt><dd>1.44 0.0002 BGN NM_001711 </dd></dl>

<dl><dt>VEGFC </dt><dd>1.44 0.0151 VEGFC NM_005429 </dd></dl>

<dl><dt>DLC1 </dt><dd>1.44 0.0014 DLC1 NM_006094 </dd></dl>

<dl><dt>YES </dt><dd>1.42 0.0086 YES NM_001041 </dd></dl>

<dl><dt>TIMP2 </dt><dd>1.42 0.0022 TIMP2 NM_003255 </dd></dl>

<dl><dt>CDC42BPA </dt><dd>1.41 0.0038 CDC42BPA NM_003607 </dd></dl>

<dl><dt>LAMC2 </dt><dd>1.40 0.0004 LAMC2 NM_005562 </dd></dl>

<dl><dt>ITGAV </dt><dd>1.40 0.0019 ITGAV NM_002210 </dd></dl>

<dl><dt>CTSB </dt><dd>1.40 0.0357 CTSB NM_001908 </dd></dl>

<dl><dt>DUSP1 </dt><dd>1.39 &lt;0.0001 DUSP1 NM_004417 </dd></dl>

<dl><dt>TLN1 </dt><dd>1.39 0.0335 TLN1 NM_006289 </dd></dl>

<dl><dt>CCNE2 variant 1 </dt><dd>1.39 0.0708 CCNE2 NM_057749 </dd></dl>

<dl><dt>TIMP3 </dt><dd>1.38 0.0023 TIMP3 NM_000362 </dd></dl>

<dl><dt>GHI BRAF mut4 </dt><dd>1.38 0.0537 GHIBRAFmut4 </dd></dl>

<dl><dt>HB-EGF </dt><dd>1.38 0.0109 HBEGF NM_001945 </dd></dl>

<dl><dt>HSPG2 </dt><dd>1.38 0.0258 HSPG2 NM_005529 </dd></dl>

<dl><dt>VIM </dt><dd>1.37 0.0077 VIM NM_003380 </dd></dl>

<dl><dt>ROCK1 </dt><dd>1.37 0.0168 ROCK1 NM_005406 </dd></dl>

<dl><dt>S100A1 </dt><dd>1.36 0.0233 S100A1 NM_006271 </dd></dl>

<dl><dt>p21 </dt><dd>1.36 0.0113 CDKN1A NM_000389 </dd></dl>

<dl><dt>CGB </dt><dd>1.36 0.0023 CGB NM_000737 </dd></dl>

<dl><dt>UBC </dt><dd>1.36 0.0137 UBC NM_021009 </dd></dl>

<dl><dt>GADD45B </dt><dd>1.36 0.0003 GADD45B NM_015675 </dd></dl>

<dl><dt>INHBA </dt><dd>1.35 0.0010 INHBA NM_002192 </dd></dl>

<dl><dt>VCL </dt><dd>1.34 0.0286 VCL NM_003373 </dd></dl>

<dl><dt>SIR2 </dt><dd>1.34 0.0049 SIRT1 NM_012238 </dd></dl>

<dl><dt>CD68 </dt><dd>134 0.0042 CD68 NM_001251 </dd></dl>

<dl><dt>Maspina </dt><dd>1.34 &lt;0.0001 SERPINB5 NM_002639 </dd></dl>

<dl><dt>FST </dt><dd>1.33 0.0326 FST NM_006350 </dd></dl>

<dl><dt>EPAS1 </dt><dd>1.33 0.0306 EPAS1 NM_001430 </dd></dl>

<dl><dt>LOXL2 </dt><dd>1.33 0.0076 LOXL2 NM_002318 </dd></dl>

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<dl><dt>STC1 </dt><dd>1.33 0.0119 STC1 NM_003155 </dd></dl>

<dl><dt>UNC5C </dt><dd>1.32 0.0642 UNC5C NM_003728 </dd></dl>

<dl><dt>IGFBP5 </dt><dd>1.32 0.0080 IGFBP5 NM_000599 </dd></dl>

<dl><dt>INHBB </dt><dd>1.32 0.0643 INHBB NM_002193 </dd></dl>

<dl><dt>FAP </dt><dd>1.32 0.0017 FAP NM_004460 </dd></dl>

<dl><dt>DKK1 </dt><dd>1.31 0.0298 DKK1 NM_012242 </dd></dl>

<dl><dt>FYN </dt><dd>1.31 0.0053 FYN NM_002037 </dd></dl>

<dl><dt>CTHRC1 </dt><dd>1.31 0.0017 CTHRC1 NM_138455 </dd></dl>

<dl><dt>FOS </dt><dd>1.31 0.0010 FOS NM_005252 </dd></dl>

<dl><dt>RBX1 </dt><dd>1.31 0.0633 RBX1 NM_014248 </dd></dl>

<dl><dt>TAGLN </dt><dd>1.31 0.0058 TAGLN NM_003186 </dd></dl>

<dl><dt>SBA2 </dt><dd>1.31 0.0439 WSB2 NM_018639 </dd></dl>

<dl><dt>CYR61 </dt><dd>1.30 0.0018 CYR61 NM_001554 </dd></dl>

<dl><dt>SPARC </dt><dd>1.30 0.0117 SPARC NM_003118 </dd></dl>

<dl><dt>SNAI2 </dt><dd>1.30 0.0076 SNAI2 NM_003068 </dd></dl>

<dl><dt>TMSB10 </dt><dd>1.30 0.0757 TMSB10 NM_021103 </dd></dl>

<dl><dt>IGFBP3 </dt><dd>1.30 0.0056 IGFBP3 NM_000598 </dd></dl>

<dl><dt>PDGFC </dt><dd>1.29 0.0040 PDGFC NM_016205 </dd></dl>

<dl><dt>SLPI </dt><dd>1.29 0.0026 SLPI NM_003064 </dd></dl>

<dl><dt>COL1A2 </dt><dd>1.29 0.0087 COL1A2 NM_000089 </dd></dl>

<dl><dt>NRP2 </dt><dd>1.29 0.0112 NRP2 NM_003872 </dd></dl>

<dl><dt>PRKCA </dt><dd>1.29 0.0093 PRKCA NM_002737 </dd></dl>

<dl><dt>KLF6 </dt><dd>1.29 0.0661 KLF6 NM_001300 </dd></dl>

<dl><dt>THBS1 </dt><dd>1.28 0.0062 THBS1 NM_003246 </dd></dl>

<dl><dt>EGR1 </dt><dd>1.28 0.0067 EGR1 NM_001964 </dd></dl>

<dl><dt>S100A4 </dt><dd>1.28 0.0070 S100A4 NM_002961 </dd></dl>

<dl><dt>CXCR4 </dt><dd>1.28 0.0089 CXCR4 NM_003467 </dd></dl>

<dl><dt>LAMA3 </dt><dd>1.27 0.0024 LAMA3 NM_000227 </dd></dl>

<dl><dt>LOX </dt><dd>1.26 0.0036 LOX NM_002317 </dd></dl>

<dl><dt>AKAP12 </dt><dd>1.26 0.0046 AKAP12 NM_005100 </dd></dl>

<dl><dt>ADAMTS12 </dt><dd>1.26 0.0109 ADAMTS12 NM_030955 </dd></dl>

<dl><dt>MCP1 </dt><dd>1.25 0.0122 CCL2 NM_002982 </dd></dl>

<dl><dt>Grb10 </dt><dd>1.25 0.0107 GRB10 NM_005311 </dd></dl>

<dl><dt>PTGER3 </dt><dd>1.25 0.0240 PTGER3 NM_000957 </dd></dl>

<dl><dt>CRYAB </dt><dd>1.25 0.0035 CRYAB NM_001885 </dd></dl>

<dl><dt>ANGPT2 </dt><dd>1.25 0.0566 ANGPT2 NM_001147 </dd></dl>

<dl><dt>ANXA1 </dt><dd>1.25 0.0353 ANXA1 NM_000700 </dd></dl>

<dl><dt>EphB6 </dt><dd>1.24 0.0960 EPHB6 NM_004445 </dd></dl>

<dl><dt>PDGFB </dt><dd>1.24 0.0139 PDGFB NM_002608 </dd></dl>

<dl><dt>COL1A1 </dt><dd>1.24 0.0198 COL1A1 NM_000088 </dd></dl>

<dl><dt>TGFB3 </dt><dd>1.23 0.0094 TGFB3 NM_003239 </dd></dl>

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<dl><dt>CTGF </dt><dd>1.23 0.0265 CTGF NM_001901 </dd></dl>

<dl><dt>PDGFA </dt><dd>1.23 0.0312 NM_002607 </dd></dl>

<dl><dt>HSPA1A </dt><dd>1.23 0.0027 HSPA1A NM_005345 </dd></dl>

<dl><dt>EFNB2 </dt><dd>1.23 0.0331 EFNB2 NM_004093 </dd></dl>

<dl><dt>CAPG </dt><dd>1.23 0.0724 CAPG NM_001747 </dd></dl>

<dl><dt>TGFBI </dt><dd>1.22 0.0231 TGFBI NM_000358 </dd></dl>

<dl><dt>SIAT4A </dt><dd>1.22 0.0253 ST3GAL1 NM_003033 </dd></dl>

<dl><dt>THE T </dt><dd>1.22 0.0307 THE T NM_014387 </dd></dl>

<dl><dt>ITGA5 </dt><dd>1.22 0.0224 ITGA5 NM_002205 </dd></dl>

<dl><dt>GBP2 </dt><dd>1.22 0.0225 GBP2 NM_004120 </dd></dl>

<dl><dt>ANTXR1 </dt><dd>1.22 0.0204 ANTXR1 NM_032208 </dd></dl>

<dl><dt>ID4 </dt><dd>1.22 0.0512 ID4 NM_001546 </dd></dl>

<dl><dt>SFRP2 </dt><dd>1.22 0.0039 SFRP2 NM_003013 </dd></dl>

<dl><dt>TMEPAI </dt><dd>1.21 0.0170 TMEPAI NM_020182 </dd></dl>

<dl><dt>CTSL </dt><dd>1.21 0.0388 CTSL NM_001912 </dd></dl>

<dl><dt>KLK10 </dt><dd>1.21 0.0007 KLK10 NM_002776 </dd></dl>

<dl><dt>FXYD5 </dt><dd>1.21 0.0547 FXYD5 NM_014164 </dd></dl>

<dl><dt>GJB2 </dt><dd>1.21 0.0356 GJB2 NM_004004 </dd></dl>

<dl><dt>P14ARF </dt><dd>1.21 0.0451 S78535 </dd></dl>

<dl><dt>DAPK1 </dt><dd>1.21 0.0525 DAPK1 NM_004938 </dd></dl>

<dl><dt>SKP1A </dt><dd>1.21 0.0663 SKP1A NM_006930 </dd></dl>

<dl><dt>SFRP4 </dt><dd>1.21 0.0078 SFRP4 NM_003014 </dd></dl>

<dl><dt>KLK6 </dt><dd>1.20 0.0048 KLK6 NM_002774 </dd></dl>

<dl><dt>GJA1 </dt><dd>1.20 0.0345 GJA1 NM_000165 </dd></dl>

<dl><dt>HOXB7 </dt><dd>1.20 0.0278 HOXB7 NM_004502 </dd></dl>

<dl><dt>NDRG1 </dt><dd>1.20 0.0948 NDRG1 NM_006096 </dd></dl>

<dl><dt>PAI1 </dt><dd>1.19 0.0061 SERPINE1 NM_000602 </dd></dl>

<dl><dt>CDH11 </dt><dd>1.19 0.0762 CDH11 NM_001797 </dd></dl>

<dl><dt>EGR3 </dt><dd>1.19 0.0149 EGR3 NM_004430 </dd></dl>

<dl><dt>EMP1 </dt><dd>1.19 0.0533 EMP1 NM_001423 </dd></dl>

<dl><dt>FZD1 </dt><dd>1.19 0.0671 FZD1 NM_003505 </dd></dl>

<dl><dt>ABCC5 </dt><dd>1.19 0.0631 ABCC5 NM_005688 </dd></dl>

<dl><dt>S100P </dt><dd>1.18 0.0160 S100P NM_005980 </dd></dl>

<dl><dt>OPN, osteopontin </dt><dd>1.18 0.0030 SPP1 NM_000582 </dd></dl>

<dl><dt>p16-INK4 </dt><dd>1.17 0.0503 L27211 </dd></dl>

<dl><dt>NR4A1 </dt><dd>1.17 0.0332 NR4A1 NM_002135 </dd></dl>

<dl><dt>TUBB </dt><dd>1.17 0.0950 TUBB2 NM_001069 </dd></dl>

<dl><dt>SIAT7B </dt><dd>1.17 0.0352 ST6GALNAC2 NM_006456 </dd></dl>

<dl><dt>ALDH1A1 </dt><dd>1.17 0.0299 ALDH1A1 NM_000689 </dd></dl>

<dl><dt>F3 </dt><dd>1.16 0.0654 F3 NM_001993 </dd></dl>

<dl><dt>SLC2A1 </dt><dd>1.15 0.0806 SLC2A1 NM_006516 </dd></dl>

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<dl><dt>CXCL12 </dt><dd>1.13 0.0986 CXCL12 NM_000609 </dd></dl>

<dl><dt>STMY3 </dt><dd>1.13 0.0518 MMP11 NM_005940 </dd></dl>

<dl><dt>S100A2 </dt><dd>1.13 0.0303 S100A2 NM_005978 </dd></dl>

<dl><dt>FABP4 </dt><dd>1.13 0.0363 FABP4 NM_001442 </dd></dl>

<dl><dt>REG4 </dt><dd>1.11 0.0034 REG4 NM_032044 </dd></dl>

<dl><dt>pS2 </dt><dd>1.09 0.0690 TFF1 NM_003225 </dd></dl>

<dl><dt>MUC2 </dt><dd>1.06 0.0674 MUC2 NM_002457 </dd></dl>

Table 1.2B shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio &lt;1.0 and for which p &lt;0.1. Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using ILR as a metric for the clinical outcome

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>ORC1L </dt><dd>0.41 0.0623 ORC1L NM_004153 </dd></dl>

<dl><dt>E2F1 </dt><dd>0.63 0.0006 E2F1 NM_005225 </dd></dl>

<dl><dt>HSPA8 </dt><dd>0.63 0.0346 HSPA8 NM_006597 </dd></dl>

<dl><dt>RAD54L </dt><dd>0.65 0.0026 RAD54L NM_003579 </dd></dl>

<dl><dt>BRCA1 </dt><dd>0.68 0.0001 BRCA1 NM_007295 </dd></dl>

<dl><dt>SLC25A3 </dt><dd>0.70 0.0100 SLC25A3 NM_213611 </dd></dl>

<dl><dt>PPM1D </dt><dd>0.71 0.0025 PPM1D NM_003620 </dd></dl>

<dl><dt>DHFR </dt><dd>0.71 0.0106 DHFR NM_000791 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.72 0.0087 SKP2 NM_005983 </dd></dl>

<dl><dt>FASN </dt><dd>0.73 0.0070 FASN NM_004104 </dd></dl>

<dl><dt>HNRPD </dt><dd>0.73 0.0611 HNRPD NM_031370 </dd></dl>

<dl><dt>ENO1 </dt><dd>0.74 0.0432 ENO1 NM_001428 </dd></dl>

<dl><dt>C20orf1 </dt><dd>0.74 0.0086 TPX2 NM_012112 </dd></dl>

<dl><dt>BRCA2 </dt><dd>0.75 0.0515 BRCA2 NM_000059 </dd></dl>

<dl><dt>DDB1 </dt><dd>0.75 0.0639 DDB1 NM_001923 </dd></dl>

<dl><dt>KIF22 </dt><dd>0.76 0.0127 KIF22 NM_007317 </dd></dl>

<dl><dt>RPLPO </dt><dd>0.76 0.0330 RPLPO NM_001002 </dd></dl>

<dl><dt>Chk1 </dt><dd>0.76 0.0164 CHEK1 NM_001274 </dd></dl>

<dl><dt>ST14 </dt><dd>0.77 0.0392 ST14 NM_021978 </dd></dl>

<dl><dt>Bax </dt><dd>0.77 0.0502 BAX NM_004324 </dd></dl>

<dl><dt>TCF-1 </dt><dd>0.78 0.0023 TCF1 NM_000545 </dd></dl>

<dl><dt>LMNB1 </dt><dd>0.78 0.0458 LMNB1 NM_005573 </dd></dl>

<dl><dt>RRM1 </dt><dd>0.78 0.0693 RRM1 NM_001033 </dd></dl>

<dl><dt>CSEL1 </dt><dd>0.79 0.0261 CSE1L NM_001316 </dd></dl>

<dl><dt>CDC20 </dt><dd>0.79 0.0274 CDC20 NM_001255 </dd></dl>

<dl><dt>PRDX2 </dt><dd>0.79 0.0930 PRDX2 NM_005809 </dd></dl>

<dl><dt>RPS13 </dt><dd>0.79 0.0906 RPS13 NM_001017 </dd></dl>

<dl><dt>RAF1 </dt><dd>0.80 0.0717 RAF1 NM_002880 </dd></dl>

<dl><dt>CMYC </dt><dd>0.80 0.0095 MYC NM_002467 </dd></dl>

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<dl><dt>UBE2M </dt><dd>0.80 0.0390 UBE2M NM_003969 </dd></dl>

<dl><dt>CKS2 </dt><dd>0.80 0.0596 CKS2 NM_001827 </dd></dl>

<dl><dt>NME1 </dt><dd>0.80 0.0694 NM_E1 NM_000269 </dd></dl>

<dl><dt>c-myb (official MYB) </dt><dd>0.80 0.0082 MY B NM_005375 </dd></dl>

<dl><dt>CD80 </dt><dd>0.80 0.0688 CD80 NM_005191 </dd></dl>

<dl><dt>CDCA7 v2 </dt><dd>0.81 0.0164 CDCA7 NM_145810 </dd></dl>

<dl><dt>EFP </dt><dd>0.81 0.0387 TRIM25 NM_005082 </dd></dl>

<dl><dt>CCNE2 </dt><dd>0.81 0.0405 CCNE2 NM_057749 </dd></dl>

<dl><dt>SURV </dt><dd>0.81 0.0573 BIRC5 NM_001168 </dd></dl>

<dl><dt>RRM2 </dt><dd>0.82 0.0181 RRM2 NM_001034 </dd></dl>

<dl><dt>ABCC6 </dt><dd>0.82 0.0464 ABCC6 NM_001171 </dd></dl>

<dl><dt>UMPS </dt><dd>0.82 0.0371 UMPS NM_000373 </dd></dl>

<dl><dt>PI3KC2A </dt><dd>0.82 0.0855 PIK3C2A NM_002645 </dd></dl>

<dl><dt>NOTCH1 </dt><dd>0.82 0.0222 NOTCH1 NM_017617 </dd></dl>

<dl><dt>EIF4E </dt><dd>0.82 0.0928 EIF4E NM_001968 </dd></dl>

<dl><dt>EPHB2 </dt><dd>0.82 0.0183 EPHB2 NM_004442 </dd></dl>

<dl><dt>AREG </dt><dd>0.83 0.0012 AREG NM_001657 </dd></dl>

<dl><dt>EREG </dt><dd>0.83 0.0059 EREG NM_001432 </dd></dl>

<dl><dt>MYBL2 </dt><dd>0.83 0.0234 MYBL2 NM_002466 </dd></dl>

<dl><dt>ABCB1 </dt><dd>0.83 0.0342 ABCB1 NM_000927 </dd></dl>

<dl><dt>HRAS </dt><dd>0.83 0.0708 HRAS NM_005343 </dd></dl>

<dl><dt>SLC7A5 </dt><dd>0.84 0.0547 SLC7A5 NM_003486 </dd></dl>

<dl><dt>MAD2L1 </dt><dd>0.84 0.0653 MAD2L1 NM_002358 </dd></dl>

<dl><dt>ING5 </dt><dd>0.85 0.0920 ING5 NM_032329 </dd></dl>

<dl><dt>Ki-67 </dt><dd>0.85 0.0562 MKI67 NM_002417 </dd></dl>

<dl><dt>MCM2 </dt><dd>0.85 0.0671 MCM2 NM_004526 </dd></dl>

<dl><dt>Cdx2 </dt><dd>0.88 0.0430 CDX2 NM_001265 </dd></dl>

<dl><dt>HES6 </dt><dd>0.89 0.0966 HES6 NM_018645 </dd></dl>

<dl><dt>PTPRO </dt><dd>0.89 0.0664 PTPRO NM_030667 </dd></dl>

<dl><dt>cnpto (official TDGF1) </dt><dd>0.90 0.0781 TDGF1 NM_003212 </dd></dl>

Table 2.2A shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio> 1.0 and for which p <0.1. A Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using OS as a metric for the clinical outcome.

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>RhoC </dt><dd>1.66 0.0002 RHOC NM_175744 </dd></dl>

<dl><dt>ITGB1 </dt><dd>1.59 0.0049 ITGB1 NM_002211 </dd></dl>

<dl><dt>ANXA2 </dt><dd>1.58 0.0004 ANXA2 NM_004039 </dd></dl>

<dl><dt>CYP3A4 </dt><dd>1.49 0.0114 CYP3A4 NM_017460 </dd></dl>

<dl><dt>p21 </dt><dd>1.49 &lt;0.0001 CDKN1A NM_000389 </dd></dl>

<dl><dt>HMLH </dt><dd>1.42 0.0555 MLH1 NM_000249 </dd></dl>

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<dl><dt>VEGFC </dt><dd>1.41 0.0095 VEGFC NM_005429 </dd></dl>

<dl><dt>TGFBR1 </dt><dd>1.40 0.0113 TGFBR1 NM_004612 </dd></dl>

<dl><dt>UBC </dt><dd>1.38 0.0013 UBC NM_021009 </dd></dl>

<dl><dt>RhoB </dt><dd>1.37 0.0016 Rhob NM_004040 </dd></dl>

<dl><dt>HSPG2 </dt><dd>1.37 0.0111 HSPG2 NM_005529 </dd></dl>

<dl><dt>NFP1 </dt><dd>1.35 0.0987 NFP1 NM_005022 </dd></dl>

<dl><dt>TIMP1 </dt><dd>1.35 0.0008 TIMP1 NM_003254 </dd></dl>

<dl><dt>VCL </dt><dd>1.33 0.0116 VCL NM_003373 </dd></dl>

<dl><dt>INHBB </dt><dd>1.32 0.0265 INHBB NM_002193 </dd></dl>

<dl><dt>SPINT2 </dt><dd>1.32 0.0358 SPINT2 NM_021102 </dd></dl>

<dl><dt>GHI BRAF mut4 </dt><dd>1.31 0.0822 GHI_BRAF_mut4 </dd></dl>

<dl><dt>LAMC2 </dt><dd>1.31 0.0007 LAMC2 NM_005562 </dd></dl>

<dl><dt>KCNH2 iso a / b </dt><dd>1.31 0.0474 KCNH2 NM_000238 </dd></dl>

<dl><dt>UNC5C </dt><dd>1.30 0.0417 UNC5C NM_003728 </dd></dl>

<dl><dt>CDC42 </dt><dd>1.30 0.0122 CDC42 NM_001791 </dd></dl>

<dl><dt>UBL1 </dt><dd>1.29 0.0169 SUMO1 NM_003352 </dd></dl>

<dl><dt>GADD45B </dt><dd>1.29 0.0003 GADD45B NM_015675 </dd></dl>

<dl><dt>KRAS2 </dt><dd>1.29 0.0774 KRAS NM_004985 </dd></dl>

<dl><dt>HB EGF </dt><dd>1.29 0.0219 HBEGF NM_001945 </dd></dl>

<dl><dt>DKK1 </dt><dd>1.28 0.0304 DKK1 NM_012242 </dd></dl>

<dl><dt>FXYD5 </dt><dd>1.28 0.0035 FXYD5 NM_014164 </dd></dl>

<dl><dt>CALD1 </dt><dd>1.28 0.0107 CALD1 NM_004342 </dd></dl>

<dl><dt>ANXA5 </dt><dd>1.27 0.0723 ANXA5 NM_001154 </dd></dl>

<dl><dt>HLA-G </dt><dd>1.27 0.0732 HLA-G NM_002127 </dd></dl>

<dl><dt>DUSP1 </dt><dd>1.27 0.0004 DUSP1 NM_004417 </dd></dl>

<dl><dt>LOXL2 </dt><dd>1.27 0.0050 LOXL2 NM_002318 </dd></dl>

<dl><dt>CDC42BPA </dt><dd>1.27 0.0155 CDC42BPA NM_003607 </dd></dl>

<dl><dt>BGN </dt><dd>1.27 0.0039 BGN NM_001711 </dd></dl>

<dl><dt>LAMB3 </dt><dd>1.27 0.0221 LAMB3 NM_000228 </dd></dl>

<dl><dt>EphB6 </dt><dd>1.27 0.0373 EPHB6 NM_004445 </dd></dl>

<dl><dt>SHC1 </dt><dd>1.27 0.0582 SHC1 NM_003029 </dd></dl>

<dl><dt>TIMP2 </dt><dd>1.26 0.0126 TIMP2 NM_003255 </dd></dl>

<dl><dt>CTSB </dt><dd>1.26 0.0748 CTSB NM_001908 </dd></dl>

<dl><dt>TIMP3 </dt><dd>1.26 0.0072 TIMP3 NM_000362 </dd></dl>

<dl><dt>ID3 </dt><dd>1.26 0.0033 ID3 NM_002167 </dd></dl>

<dl><dt>CAPG </dt><dd>1.26 0.0162 CAPG NM_001747 </dd></dl>

<dl><dt>NRP1 </dt><dd>1.26 0.0135 NRP1 NM_003873 </dd></dl>

<dl><dt>INHBA </dt><dd>1.26 0.0021 INHBA NM_002192 </dd></dl>

<dl><dt>KLF6 </dt><dd>1.25 0.0477 KLF6 NM_001300 </dd></dl>

<dl><dt>IGFBP7 </dt><dd>1.25 0.0251 IGFBP7 NM_001553 </dd></dl>

<dl><dt>S100A1 </dt><dd>1.25 0.0528 S100A1 NM_006271 </dd></dl>

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<dl><dt>EPAS1 </dt><dd>1.24 0.0382 EPAS1 NM_001430 </dd></dl>

<dl><dt>DLC1 </dt><dd>1.24 0.0228 DLC1 NM_006094 </dd></dl>

<dl><dt>KLK10 </dt><dd>1.24 &lt;0.0001 KLK10 NM_002776 </dd></dl>

<dl><dt>SBA2 </dt><dd>1.24 0.0493 WSB2 NM_018639 </dd></dl>

<dl><dt>SPARC </dt><dd>1.24 0.0133 SPARC NM_003118 </dd></dl>

<dl><dt>GAGE4 </dt><dd>1.23 0.0475 GAGE4 NM_001474 </dd></dl>

<dl><dt>HSPA1A </dt><dd>1.23 0.0004 HSPA1A NM_005345 </dd></dl>

<dl><dt>SIR2 </dt><dd>1.23 0.0179 SIRT1 NM_012238 </dd></dl>

<dl><dt>CGB </dt><dd>1.23 0.0202 CGB NM_000737 </dd></dl>

<dl><dt>Grb10 </dt><dd>1.22 0.0059 GRB10 NM_005311 </dd></dl>

<dl><dt>SNAI2 </dt><dd>1.22 0.0145 SNAI2 NM_003068 </dd></dl>

<dl><dt>LAMA3 </dt><dd>1.22 0.0019 LAMA3 NM_000227 </dd></dl>

<dl><dt>AKT3 </dt><dd>1.22 0.0169 AKT3 NM_005465 </dd></dl>

<dl><dt>FYN </dt><dd>1.22 0.0138 FYN NM_002037 </dd></dl>

<dl><dt>FOS </dt><dd>1.22 0.0035 FOS NM_005252 </dd></dl>

<dl><dt>CTHRC1 </dt><dd>1.21 0.0056 CTHRC1 NM_138455 </dd></dl>

<dl><dt>CTSD </dt><dd>1.21 0.0506 CTSD NM_001909 </dd></dl>

<dl><dt>THY1 </dt><dd>1.21 0.0290 THY1 NM_006288 </dd></dl>

<dl><dt>ANXA1 </dt><dd>1.21 0.0339 ANXA1 NM_000700 </dd></dl>

<dl><dt>CD68 </dt><dd>1.21 0.0227 CD68 NM_001251 </dd></dl>

<dl><dt>G-Catenin </dt><dd>1.20 0.0789 JUP NM_002230 </dd></dl>

<dl><dt>PLK3 </dt><dd>1.20 0.0081 PLK3 NM_004073 </dd></dl>

<dl><dt>STC1 </dt><dd>1.20 0.0577 STC1 NM_003155 </dd></dl>

<dl><dt>TAGLN </dt><dd>1.20 0.0238 TAGLN NM_003186 </dd></dl>

<dl><dt>VIM </dt><dd>1.20 0.0632 VIM NM_003380 </dd></dl>

<dl><dt>HSPA1B </dt><dd>1.20 0.0302 HSPA1B NM_005346 </dd></dl>

<dl><dt>THE T </dt><dd>1.20 0.0184 THE T NM_014387 </dd></dl>

<dl><dt>KRT19 </dt><dd>1.20 0.0309 KRT19 NM_002276 </dd></dl>

<dl><dt>IGFBP3 </dt><dd>1.20 0.0167 IGFBP3 NM_000598 </dd></dl>

<dl><dt>BMP4 </dt><dd>1.20 0.0035 BMP4 NM_001202 </dd></dl>

<dl><dt>KLK6 </dt><dd>1.20 0.0014 KLK6 NM_002774 </dd></dl>

<dl><dt>THBS1 </dt><dd>1.20 0.0206 THBS1 NM_003246 </dd></dl>

<dl><dt>TULP3 </dt><dd>1.19 0.0344 TULP3 NM_003324 </dd></dl>

<dl><dt>ERK1 </dt><dd>1.19 0.0522 Z11696 </dd></dl>

<dl><dt>CREBBP </dt><dd>1.19 0.0866 CREBBP NM_004380 </dd></dl>

<dl><dt>S100A4 </dt><dd>1.19 0.0259 S100A4 NM_002961 </dd></dl>

<dl><dt>PDGFB </dt><dd>1.19 0.0205 PDGFB NM_002608 </dd></dl>

<dl><dt>EFNB2 </dt><dd>1.19 0.0299 EFNB2 NM_004093 </dd></dl>

<dl><dt>LOX </dt><dd>1.19 0.0104 LOX NM_002317 </dd></dl>

<dl><dt>PTK2 </dt><dd>1.18 0.0983 PTK2 NM_005607 </dd></dl>

<dl><dt>IGFBP5 </dt><dd>1.18 0.0544 IGFBP5 NM_000599 </dd></dl>

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<dl><dt>APC </dt><dd>1.18 0.0461 APC NM_000038 </dd></dl>

<dl><dt>DYRK1B </dt><dd>1.18 0.0681 DYRK1B NM_004714 </dd></dl>

<dl><dt>NOTCH2 </dt><dd>1.18 0.0533 NOTCH2 NM_024408 </dd></dl>

<dl><dt>Maspina </dt><dd>1.18 0.0033 SERPINB5 NM_002639 </dd></dl>

<dl><dt>AKAP12 </dt><dd>1.18 0.0195 AKAP12 NM_005100 </dd></dl>

<dl><dt>COL1A1 </dt><dd>1.17 0.0417 COL1A1 NM_000088 </dd></dl>

<dl><dt>EMP1 </dt><dd>1.17 0.0295 EMP1 NM_001423 </dd></dl>

<dl><dt>SIAT4A </dt><dd>1.17 0.0311 ST3GAL1 NM_003033 </dd></dl>

<dl><dt>PAI1 </dt><dd>1.17 0.0036 SERPINE1 NM_000602 </dd></dl>

<dl><dt>NR4A1 </dt><dd>1.17 0.0117 NR4A1 NM_002135 </dd></dl>

<dl><dt>EGR1 </dt><dd>1.17 0.0379 EGR1 NM_001964 </dd></dl>

<dl><dt>BRK </dt><dd>1.17 0.0156 PTK6 NM_005975 </dd></dl>

<dl><dt>UNC5B </dt><dd>1.17 0.0956 UNC5B NM_170744 </dd></dl>

<dl><dt>SR-A1 </dt><dd>1.77 0.0512 SR-A1 NM_021228 </dd></dl>

<dl><dt>MRP3 </dt><dd>1.16 0.0353 ABCC3 NM_003786 </dd></dl>

<dl><dt>hCRA to </dt><dd>1.16 0.0878 U78556 </dd></dl>

<dl><dt>Upa </dt><dd>1.16 0.0630 PLAU NM_002658 </dd></dl>

<dl><dt>BCAS1 </dt><dd>1.16 0.0147 BCAS1 NM_003657 </dd></dl>

<dl><dt>PDGFC </dt><dd>1.16 0.0375 PDGFC NM_016205 </dd></dl>

<dl><dt>COL1A2 </dt><dd>1.16 0.0620 COL1A2 NM_000089 </dd></dl>

<dl><dt>CTGF </dt><dd>1.16 0.0580 CTGF NM_00190 </dd></dl>

<dl><dt>MCP1 </dt><dd>1.16 0.0463 CCL2 NM_002982 </dd></dl>

<dl><dt>RAB32 </dt><dd>1.16 0.0686 RAB32 NM_006834 </dd></dl>

<dl><dt>SKP1A </dt><dd>1.16 0.0842 SKP1A NM_006930 </dd></dl>

<dl><dt>FAP </dt><dd>1.16 0.0443 FAP NM_004460 </dd></dl>

<dl><dt>EFNA1 </dt><dd>1.16 0.0990 EFNA1 NM_004428 </dd></dl>

<dl><dt>HOXB7 </dt><dd>1.15 0.0378 HOXB7 NM_004502 </dd></dl>

<dl><dt>CYR61 </dt><dd>1.15 0.0452 CYR61 NM_001554 </dd></dl>

<dl><dt>TGFBI </dt><dd>1.15 0.0591 TGFBI NM_000358 </dd></dl>

<dl><dt>TMEPAI </dt><dd>1.15 0.0419 TMEPAI NM_020182 </dd></dl>

<dl><dt>SIN3A </dt><dd>1.15 0.0853 SIN3A NM_015477 </dd></dl>

<dl><dt>S100A2 </dt><dd>1.15 0.0038 S100A2 NM_005978 </dd></dl>

<dl><dt>PDGFA </dt><dd>1.15 0.0840 NM_002607 </dd></dl>

<dl><dt>MMP7 </dt><dd>1.15 0.0469 MMP7 NM_002423 </dd></dl>

<dl><dt>ANTXR1 </dt><dd>1.15 0.0520 ANTXR1 NM_032208 </dd></dl>

<dl><dt>SLPI </dt><dd>1.14 0.0755 SLPI NM_003064 </dd></dl>

<dl><dt>SFRP2 </dt><dd>1.13 0.0253 SFRP2 NM_003013 </dd></dl>

<dl><dt>S100A8 </dt><dd>1.13 0.0795 S100A8 NM_002964 </dd></dl>

<dl><dt>TP53I3 </dt><dd>1.13 0.0973 TP53I3 NM_004881 </dd></dl>

<dl><dt>F3 </dt><dd>1.13 0.0735 F3 NM_001993 </dd></dl>

<dl><dt>OPN, osteopontin </dt><dd>1.12 0.0100 SPP1 NM_000582 </dd></dl>

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<dl><dt>EGLN3 </dt><dd>1.11 0.0883 EGLN3 NM_022073 </dd></dl>

<dl><dt>FZD6 </dt><dd>1.11 0.0791 FZD6 NM_003506 </dd></dl>

<dl><dt>OSM </dt><dd>1.10 0.0913 OSM NM_020530 </dd></dl>

<dl><dt>FABP4 </dt><dd>1.10 0.0521 FABP4 NM_001442 </dd></dl>

<dl><dt>GSTT1 </dt><dd>1.09 0.0837 GSTT1 NM_000853 </dd></dl>

<dl><dt>REG4 </dt><dd>1.07 0.0300 REG4 NM_032044 </dd></dl>

Table 2.2B shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio &lt;1.0 and for which p &lt;0.1. A Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using OS as a metric for the clinical outcome.

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>ORC1L </dt><dd>0.52 0.0895 ORC1L NM_004153 </dd></dl>

<dl><dt>HSPA8 </dt><dd>0.64 0.0164 HSPA8 NM_006597 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.71 0.0012 SKP2 NM_005983 </dd></dl>

<dl><dt>PRDX4 </dt><dd>0.74 0.0202 PRDX4 NM_006406 </dd></dl>

<dl><dt>DHFR </dt><dd>0.76 0.0111 DHFR NM_000791 </dd></dl>

<dl><dt>FGF18 </dt><dd>0.76 0.0915 FGF18 NM_003862 </dd></dl>

<dl><dt>SLC25A3 </dt><dd>0.76 0.0391 SLC25A3 NM_213611 </dd></dl>

<dl><dt>RRM1 </dt><dd>0.77 0.0218 RRM1 NM_001033 </dd></dl>

<dl><dt>E2F1 </dt><dd>0.78 0.0180 E2F1 NM_005225 </dd></dl>

<dl><dt>SURV </dt><dd>0.79 0.0098 BIRC5 NM_001168 </dd></dl>

<dl><dt>PPM1D </dt><dd>0.80 0.0154 PPM1D NM_003620 </dd></dl>

<dl><dt>CCNE2 </dt><dd>0.80 0.0090 CCNE2 NM_057749 </dd></dl>

<dl><dt>BRCA1 </dt><dd>0.80 0.0093 BRCA1 NM_007295 </dd></dl>

<dl><dt>ST14 </dt><dd>0.80 0.0436 ST14 NM_021978 </dd></dl>

<dl><dt>c-myb (official MY6) </dt><dd>0.81 0.0027 MY B NM_005375 </dd></dl>

<dl><dt>Chk1 </dt><dd>0.81 0.0220 CHEK1 NM_001274 </dd></dl>

<dl><dt>C20 orf1 </dt><dd>0.81 0.0305 TPX2 NM_012112 </dd></dl>

<dl><dt>IE24 </dt><dd>0.81 0.0574 IE24 NM_004879 </dd></dl>

<dl><dt>CDC20 </dt><dd>0.82 0.0234 CDC20 NM_001255 </dd></dl>

<dl><dt>TCF-1 </dt><dd>0.82 0.0061 TCF1 NM_000545 </dd></dl>

<dl><dt>PPID </dt><dd>0.83 0.0584 PPID NM_005038 </dd></dl>

<dl><dt>KIF22 </dt><dd>0.83 0.0466 KIF22 NM_007317 </dd></dl>

<dl><dt>UBE2M </dt><dd>0.83 0.0850 UBE2M NM_003969 </dd></dl>

<dl><dt>MRPL40 </dt><dd>0.83 0.0716 MRPL40 NM_003776 </dd></dl>

<dl><dt>RPLPO </dt><dd>0.84 0.0987 RPLP0 NM_001002 </dd></dl>

<dl><dt>LMNB1 </dt><dd>0.84 0.0910 LMNB1 NM_005573 </dd></dl>

<dl><dt>DUT </dt><dd>0.84 0.0401 DUT NM_001948 </dd></dl>

<dl><dt>CD44E </dt><dd>0.84 0.0483 X55150 </dd></dl>

<dl><dt>MCM2 </dt><dd>0.85 0.0214 MCM2 NM_004526 </dd></dl>

<dl><dt>CDC6 </dt><dd>0.85 0.0235 CDC6 NM_001254 </dd></dl>

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<dl><dt>AURKB </dt><dd>0.85 0.0373 AURKB NM_004217 </dd></dl>

<dl><dt>SMARCA3 </dt><dd>0.86 0.0562 SMARCA3 NM_003071 </dd></dl>

<dl><dt>CDCA7 v2 </dt><dd>0.86 0.0435 CDCA7 NM_145810 </dd></dl>

<dl><dt>EPHB2 </dt><dd>0.86 0.0281 EPHB2 NM_004442 </dd></dl>

<dl><dt>CMYC </dt><dd>0.86 0.0441 MYC NM_002467 </dd></dl>

<dl><dt>ABCB1 </dt><dd>0.86 0.0352 ABCB1 NM_000927 </dd></dl>

<dl><dt>Cdx2 </dt><dd>0.87 0.0156 CDX2 NM_001265 </dd></dl>

<dl><dt>PPARG </dt><dd>0.88 0.0655 PPARG NM_005037 </dd></dl>

<dl><dt>MYBL2 </dt><dd>0.88 0.0667 MYBL2 NM_002466 </dd></dl>

<dl><dt>EREG </dt><dd>0.89 0.0352 EREG NM_001432 </dd></dl>

<dl><dt>AREG </dt><dd>0.90 0.0221 AREG NM_001657 </dd></dl>

Table 3.2A shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio> 1.0 and for which p <0.1. Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using SLE as a metric for the clinical outcome.

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>ANXA2 </dt><dd>1.67 &lt;0.0001 ANXA2 NM_004039 </dd></dl>

<dl><dt>CYP3A4 </dt><dd>1.59 0.0035 CYP3A4 NM_017460 </dd></dl>

<dl><dt>RhoC </dt><dd>1.52 0.0010 RHOC NM_175744 </dd></dl>

<dl><dt>TJP1 </dt><dd>1.44 0.0951 TJP1 NM_003257 </dd></dl>

<dl><dt>HB-EGF </dt><dd>1.39 0.0023 HBEGF NM_001945 </dd></dl>

<dl><dt>p21 </dt><dd>1.39 0.0006 CDKN1A NM_000389 </dd></dl>

<dl><dt>HMLH </dt><dd>1.37 0.0678 MLH1 NM_000249 </dd></dl>

<dl><dt>ITGB1 </dt><dd>1.37 0.0419 ITGB1 NM_002211 </dd></dl>

<dl><dt>UBC </dt><dd>1.34 0.0024 UBC NM_021009 </dd></dl>

<dl><dt>VEGFC </dt><dd>1.33 0.0246 VEGFC NM_005429 </dd></dl>

<dl><dt>TIMP1 </dt><dd>1.33 0.0007 TIMP1 NM_003254 </dd></dl>

<dl><dt>CCNE2 variant 1 </dt><dd>1.32 0.0745 CCNE2 NM_057749 </dd></dl>

<dl><dt>SPINT2 </dt><dd>1.32 0.0224 SPINT2 NM_021102 </dd></dl>

<dl><dt>LAMC2 </dt><dd>1.32 0.0002 LAMC2 NM_005562 </dd></dl>

<dl><dt>VCL </dt><dd>1.31 0.0119 VCL NM_003373 </dd></dl>

<dl><dt>RhoB </dt><dd>1.31 0.0049 Rhob NM_004040 </dd></dl>

<dl><dt>PKR2 </dt><dd>1.30 0.0258 PKM2 NM_002654 </dd></dl>

<dl><dt>ANXA5 </dt><dd>1.30 0.0406 ANXA5 NM_001154 </dd></dl>

<dl><dt>GADD45B </dt><dd>1.30 0.0001 GADD45B NM_015675 </dd></dl>

<dl><dt>INHBB </dt><dd>1.29 0.0368 INHBB NM_002193 </dd></dl>

<dl><dt>DUSP1 </dt><dd>1.29 &lt;0.0001 DUSP1 NM_004417 </dd></dl>

<dl><dt>KRAS2 </dt><dd>1.28 0.0686 KRAS NM_004985 </dd></dl>

<dl><dt>KLF6 </dt><dd>1.28 0.0284 KLF6 NM_001300 </dd></dl>

<dl><dt>IGFBP7 </dt><dd>1.27 0.0103 IGFBP7 NM_001553 </dd></dl>

<dl><dt>GRIK1 </dt><dd>1.27 0.0421 GRIK1 NM_000830 </dd></dl>

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<dl><dt>DLC1 </dt><dd>1.27 0.0084 DLC1 NM_006094 </dd></dl>

<dl><dt>FOS </dt><dd>1.26 0.0003 FOS NM_005252 </dd></dl>

<dl><dt>HSPG2 </dt><dd>1.26 0.0443 HSPG2 NM_005529 </dd></dl>

<dl><dt>INHBA </dt><dd>1.26 0.0009 INHBA NM_002192 </dd></dl>

<dl><dt>TIMP3 </dt><dd>1.26 0.0045 TIMP3 NM_000362 </dd></dl>

<dl><dt>BGN </dt><dd>1.26 0.0035 BGN NM_001711 </dd></dl>

<dl><dt>CGB </dt><dd>1.26 0.0172 CGB NM_000737 </dd></dl>

<dl><dt>HK1 </dt><dd>1.26 0.0352 HK1 NM_000188 </dd></dl>

<dl><dt>SHC1 </dt><dd>1.25 0.0562 SHC1 NM_003029 </dd></dl>

<dl><dt>STC1 </dt><dd>1.25 0.0161 STC1 NM_003155 </dd></dl>

<dl><dt>LOXL2 </dt><dd>1.24 0.0078 LOXL2 NM_002318 </dd></dl>

<dl><dt>CAPG </dt><dd>1.24 0.0161 CAPG NM_001747 </dd></dl>

<dl><dt>UNC5B </dt><dd>1.23 0.0204 UNC5B NM_170744 </dd></dl>

<dl><dt>MVP </dt><dd>1.23 0.0729 MVP NM_017458 </dd></dl>

<dl><dt>CTSD </dt><dd>1.23 0.0256 CTSD NM_001909 </dd></dl>

<dl><dt>EGR1 </dt><dd>1.23 0.0041 EGR1 NM_001964 </dd></dl>

<dl><dt>LOX </dt><dd>1.23 0.0017 LOX NM_002317 </dd></dl>

<dl><dt>CDC42BPA </dt><dd>1.23 0.0278 CDC42BPA NM_003607 </dd></dl>

<dl><dt>GAGE4 </dt><dd>1.23 0.0425 GAGE4 NM_001474 </dd></dl>

<dl><dt>CALD1 </dt><dd>1.22 0.0239 CALD1 NM_004342 </dd></dl>

<dl><dt>FXYD5 </dt><dd>1.22 0.0096 FXYD5 NM_014164 </dd></dl>

<dl><dt>EphB6 </dt><dd>1.22 0.0825 EPHB6 NM_004445 </dd></dl>

<dl><dt>LAMB3 </dt><dd>1.22 0.0444 LAMB3 NM_000228 </dd></dl>

<dl><dt>VEGF </dt><dd>1.21 0.0267 VEGF NM_003376 </dd></dl>

<dl><dt>PDGFB </dt><dd>1.21 0.0062 PDGFB NM_002608 </dd></dl>

<dl><dt>TIMP2 </dt><dd>1.21 0.0292 TIMP2 NM_003255 </dd></dl>

<dl><dt>A-Catenin </dt><dd>1.21 0.0598 CTNNA1 NM_001903 </dd></dl>

<dl><dt>IGFBP3 </dt><dd>1.21 0.0081 IGFBP3 NM_000598 </dd></dl>

<dl><dt>CD68 </dt><dd>1.21 0.0138 CD68 NM_001251 </dd></dl>

<dl><dt>S100A1 </dt><dd>1.21 0.0886 S100A1 NM_006271 </dd></dl>

<dl><dt>SIAT4A </dt><dd>1.21 0.0076 ST3GAL1 NM_003033 </dd></dl>

<dl><dt>HSPA1B </dt><dd>1.21 0.0182 HSPA1B NM_005346 </dd></dl>

<dl><dt>DKK1 </dt><dd>1.20 0.0900 DKK1 NM_012242 </dd></dl>

<dl><dt>SBA2 </dt><dd>1.20 0.0733 WSB2 NM_018639 </dd></dl>

<dl><dt>SIR2 </dt><dd>1.20 0.0250 SIRT1 NM_012238 </dd></dl>

<dl><dt>THBS1 </dt><dd>1.20 0.0119 THBS1 NM_003246 </dd></dl>

<dl><dt>FYN </dt><dd>1.20 0.0156 FYN NM_002037 </dd></dl>

<dl><dt>TULP3 </dt><dd>1.20 0.0205 TULP3 NM_003324 </dd></dl>

<dl><dt>LAMA3 </dt><dd>1.20 0.0026 LAMA3 NM_000227 </dd></dl>

<dl><dt>NR4A1 </dt><dd>1.20 0.0022 NR4A1 NM_002135 </dd></dl>

<dl><dt>EFNA1 </dt><dd>1.20 0.0258 EFNA1 NM_004428 </dd></dl>

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<dl><dt>EMP1 </dt><dd>1.20 0.0102 EMP1 NM_001423 </dd></dl>

<dl><dt>SPARC </dt><dd>1.19 0.0333 SPARC NM_003118 </dd></dl>

<dl><dt>G-Catenin </dt><dd>1.19 0.0761 JUP NM_002230 </dd></dl>

<dl><dt>CYR61 </dt><dd>1.19 0.0103 CYR61 NM_001554 </dd></dl>

<dl><dt>Maspina </dt><dd>1.19 0.0015 SERPINB5 NM_002639 </dd></dl>

<dl><dt>HSPA1A </dt><dd>1.18 0.0018 HSPA1A NM_005345 </dd></dl>

<dl><dt>PTHR1 </dt><dd>1.18 0.0856 PTHR1 NM_000316 </dd></dl>

<dl><dt>EPAS1 </dt><dd>1.18 0.0789 EPAS1 NM_001430 </dd></dl>

<dl><dt>Grb10 </dt><dd>1.18 0.0173 GRB10 NM_005311 </dd></dl>

<dl><dt>ERK1 </dt><dd>1.18 0.0464 Z11696 </dd></dl>

<dl><dt>VIM </dt><dd>1.18 0.0772 VIM NM_003380 </dd></dl>

<dl><dt>SNAI2 </dt><dd>1.18 0.0379 SNAI2 NM_003068 </dd></dl>

<dl><dt>IGFBP5 </dt><dd>1.17 0.0492 IGFBP5 NM_000599 </dd></dl>

<dl><dt>CTHRC1 </dt><dd>1.17 0.0155 CTHRC1 NM_138455 </dd></dl>

<dl><dt>THY1 </dt><dd>1.17 0.0562 THY1 NM_006288 </dd></dl>

<dl><dt>NRP1 </dt><dd>1.17 0.0747 NRP1 NM_003873 </dd></dl>

<dl><dt>PTGER3 </dt><dd>1.17 0.0493 PTGER3 NM_000957 </dd></dl>

<dl><dt>ID3 </dt><dd>1.17 0.0437 ID3 NM_002167 </dd></dl>

<dl><dt>F3 </dt><dd>1.17 0.0157 F3 NM_001993 </dd></dl>

<dl><dt>CTGF </dt><dd>1.17 0.0394 CTGF NM_001901 </dd></dl>

<dl><dt>KRT19 </dt><dd>1.17 0.0517 KRT19 NM_002276 </dd></dl>

<dl><dt>PAI1 </dt><dd>1.17 0.0033 SERPINE1 NM_000602 </dd></dl>

<dl><dt>FAP </dt><dd>1.17 0.0260 FAP NM_004460 </dd></dl>

<dl><dt>ANXA1 </dt><dd>1.16 0.0688 ANXA1 NM_000700 </dd></dl>

<dl><dt>KLK10 </dt><dd>1.16 0.0009 KLK10 NM_002776 </dd></dl>

<dl><dt>EFNB2 </dt><dd>1.16 0.0447 EFNB2 NM_004093 </dd></dl>

<dl><dt>P14ARF </dt><dd>1.16 0.0573 S78535 </dd></dl>

<dl><dt>MCP1 </dt><dd>1.16 0.0359 CCL2 NM_002982 </dd></dl>

<dl><dt>PLK3 </dt><dd>1.16 0.0296 PLK3 NM_004073 </dd></dl>

<dl><dt>ANTXR1 </dt><dd>1.16 0.0243 ANTXR1 NM_032208 </dd></dl>

<dl><dt>ADAMTS12 </dt><dd>1.16 0.0346 ADAMTS12 NM_030955 </dd></dl>

<dl><dt>EGR3 </dt><dd>1.16 0.0109 EGR3 NM_004430 </dd></dl>

<dl><dt>APC </dt><dd>1.16 0.0733 APC NM_000038 </dd></dl>

<dl><dt>PDGFC </dt><dd>1.16 0.0326 PDGFC NM_016205 </dd></dl>

<dl><dt>BMP4 </dt><dd>1.16 0.0151 BMP4 NM_001202 </dd></dl>

<dl><dt>HOXB7 </dt><dd>1.15 0.0281 HOXB7 NM_004502 </dd></dl>

<dl><dt>NDRG1 </dt><dd>1.15 0.0912 NDRG1 NM_006096 </dd></dl>

<dl><dt>Herstatin </dt><dd>1.15 0.0380 AF177761 </dd></dl>

<dl><dt>TMEPAI </dt><dd>1.15 0.0268 TMEPAI NM_020182 </dd></dl>

<dl><dt>IL6 </dt><dd>1.15 0.0914 IL6 NM_000600 </dd></dl>

<dl><dt>PDGFA </dt><dd>1.15 0.0599 NM_002607 </dd></dl>

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<dl><dt>TGFBI </dt><dd>1.15 0.0439 TGFBI NM_000358 </dd></dl>

<dl><dt>Upa </dt><dd>1.15 0.0740 PLAU NM_002658 </dd></dl>

<dl><dt>S100A4 </dt><dd>1.15 0.0621 S100A4 NM_002961 </dd></dl>

<dl><dt>SLPI </dt><dd>1.15 0.0447 SLPI NM_003064 </dd></dl>

<dl><dt>KLK6 </dt><dd>1.15 0.0112 KLK6 NM_002774 </dd></dl>

<dl><dt>COL1A1 </dt><dd>1.15 0.0637 COL1A1 NM_000088 </dd></dl>

<dl><dt>GJB2 </dt><dd>1.15 0.0604 GJB2 NM_004004 </dd></dl>

<dl><dt>PKD1 </dt><dd>1.15 0.0939 PKD1 NM_000296 </dd></dl>

<dl><dt>TP53I3 </dt><dd>1.15 0.0450 TP53I3 NM_004881 </dd></dl>

<dl><dt>PLAUR </dt><dd>1.14 0.0477 PLAUR NM_002659 </dd></dl>

<dl><dt>TAGLN </dt><dd>1.14 0.0739 TAGLN NM_003186 </dd></dl>

<dl><dt>COL1A2 </dt><dd>1.14 0.0818 COL1A2 NM_000089 </dd></dl>

<dl><dt>S100A2 </dt><dd>1.14 0.0045 S100A2 NM_005978 </dd></dl>

<dl><dt>AKT3 </dt><dd>1.14 0.0949 AKT3 NM_005465 </dd></dl>

<dl><dt>SEMA3B </dt><dd>1.13 0.0467 SEMA3B NM_004636 </dd></dl>

<dl><dt>BRK </dt><dd>1.13 0.0476 PTK6 NM_005975 </dd></dl>

<dl><dt>OSM </dt><dd>1.13 0.0344 OSM NM_020530 </dd></dl>

<dl><dt>SFRP2 </dt><dd>1.12 0.0279 SFRP2 NM_003013 </dd></dl>

<dl><dt>MRP3 </dt><dd>1.12 0.0946 ABCC3 NM_003786 </dd></dl>

<dl><dt>EGLN33 </dt><dd>1.12 0.0452 EGLN3 NM_022073 </dd></dl>

<dl><dt>SIAT7B </dt><dd>1.12 0.0603 ST6GALNAC2 NM_006456 </dd></dl>

<dl><dt>OPN, osteopontin </dt><dd>1.12 0.0082 SPP1 NM_000582 </dd></dl>

<dl><dt>S100P </dt><dd>1.12 0.0313 S100P NM_005980 </dd></dl>

<dl><dt>AKAP12 </dt><dd>1.12 0.0865 AKAP12 NM_005100 </dd></dl>

<dl><dt>MMP7 </dt><dd>1.11 0.0909 MMP7 NM_002423 </dd></dl>

<dl><dt>FABP4 </dt><dd>1.11 0.0214 FABP4 NM_001442 </dd></dl>

<dl><dt>CRYAB </dt><dd>1.11 0.0960 CRYAB NM_001885 </dd></dl>

<dl><dt>SFRP4 </dt><dd>1.10 0.0625 SFRP4 NM_003014 </dd></dl>

<dl><dt>EFNA3 </dt><dd>1.10 0.0707 EFNA3 NM_004952 </dd></dl>

<dl><dt>GSTT1 </dt><dd>1.09 0.0516 GSTT1 NM_000853 </dd></dl>

<dl><dt>pS2 </dt><dd>1.08 0.0313 TFF1 NM_003225 </dd></dl>

<dl><dt>REG4 </dt><dd>1.08 0.0080 REG4 NM_032044 </dd></dl>

<dl><dt>IGFBP2 </dt><dd>1.08 0.0846 IGFBP2 NM_000597 </dd></dl>

<dl><dt>MUC5B </dt><dd>1.08 0.0387 MUC5B XM_039877 </dd></dl>

Table 3.2B shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio &lt;1.0 and for which p &lt;0.1. Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using SLE as a metric for the clinical outcome.

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>HSPA8 </dt><dd>0.72 0.0604 HSPA8 NM_006597 </dd></dl>

<dl><dt>SLC25A3 </dt><dd>0.73 0.0126 SLC25A3 NM_213611 </dd></dl>

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<dl><dt>E2F1 </dt><dd>0.73 0.0019 E2F1 NM_005225 </dd></dl>

<dl><dt>IFIT1 </dt><dd>0.74 0.0820 IFIT1 NM_001548 </dd></dl>

<dl><dt>PPM1D </dt><dd>0.74 0.0007 PPM1D NM_003620 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.75 0.0049 SKP2 NM_005983 </dd></dl>

<dl><dt>RRM1 </dt><dd>0.78 0.0224 RRM1 NM_001033 </dd></dl>

<dl><dt>DDB1 </dt><dd>0.79 0.0720 DDB1 NM_001923 </dd></dl>

<dl><dt>NPM1 </dt><dd>0.79 0.0255 NPM1 NM_002520 </dd></dl>

<dl><dt>PRDX4 </dt><dd>0.80 0.0570 PRDX4 NM_006406 </dd></dl>

<dl><dt>BRCA1 </dt><dd>0.80 0.0064 BRCA1 NM_007295 </dd></dl>

<dl><dt>C20 orf1 </dt><dd>0.81 0.0180 TPX2 NM_012112 </dd></dl>

<dl><dt>Chk1 </dt><dd>0.81 0.0148 CHEK1 NM_001274 </dd></dl>

<dl><dt>IE24 </dt><dd>0.81 0.0417 IE24 NM_004879 </dd></dl>

<dl><dt>CCNE2 </dt><dd>0.81 0.0094 CCNE2 NM_057749 </dd></dl>

<dl><dt>HMGB1 </dt><dd>0.82 0.0852 HMGB1 NM_002128 </dd></dl>

<dl><dt>SURV </dt><dd>0.82 0.0185 BIRC5 NM_001168 </dd></dl>

<dl><dt>KIF22 </dt><dd>0.82 0.0264 KIF22 NM_007317 </dd></dl>

<dl><dt>RAD54L </dt><dd>0.82 0.0674 RAD54L NM_003579 </dd></dl>

<dl><dt>c-myb (official MYB) </dt><dd>0.82 0.0038 MY B NM_005375 </dd></dl>

<dl><dt>DHFR </dt><dd>0.82 0.0669 DHFR NM_000791 </dd></dl>

<dl><dt>TNFRSF5 </dt><dd>0.83 0.0855 CD40 NM_001250 </dd></dl>

<dl><dt>LMNB1 </dt><dd>0.83 0.0741 LMNB1 NM_005573 </dd></dl>

<dl><dt>CDC20 </dt><dd>0.85 0.0538 CDC20 NM_001255 </dd></dl>

<dl><dt>CDCA7 v2 </dt><dd>0.85 0.0277 CDCA7 NM_145810 </dd></dl>

<dl><dt>FASN </dt><dd>0.85 0.0919 FASN NM_004104 </dd></dl>

<dl><dt>MCM2 </dt><dd>0.85 0.0194 MCM2 NM_004526 </dd></dl>

<dl><dt>ABCB1 </dt><dd>0.85 0.0169 ABCB1 NM_000927 </dd></dl>

<dl><dt>EIF4E </dt><dd>0.85 0.0902 EIF4E NM_001968 </dd></dl>

<dl><dt>DUT </dt><dd>0.86 0.0535 DUT NM_001948 </dd></dl>

<dl><dt>C20ORF126 </dt><dd>0.86 0.0932 PDRG1 NM_030815 </dd></dl>

<dl><dt>MCM6 </dt><dd>0.86 0.0970 MCM6 NM_005915 </dd></dl>

<dl><dt>EFP </dt><dd>0.87 0.0850 TRIM25 NM_005082 </dd></dl>

<dl><dt>EPHB2 </dt><dd>0.87 0.0314 EPHB2 NM_004442 </dd></dl>

<dl><dt>GCLC </dt><dd>0.87 0.0862 GCLC NM_001498 </dd></dl>

<dl><dt>RFC1 </dt><dd>0.87 0.0540 RCC1 NM_001269 </dd></dl>

<dl><dt>AREG </dt><dd>0.87 0.0028 AREG NM_001657 </dd></dl>

<dl><dt>CMYC </dt><dd>0.88 0.0584 MYC NM_002467 </dd></dl>

<dl><dt>MYBL2 </dt><dd>0.88 0.0567 MYBL2 NM_002466 </dd></dl>

<dl><dt>TCF-1 </dt><dd>0.88 0.0644 TCF1 NM_000545 </dd></dl>

<dl><dt>EREG </dt><dd>0.89 0.0232 EREG NM_001432 </dd></dl>

<dl><dt>Cdx2 </dt><dd>0.90 0.0354 CDX2 NM_001265 </dd></dl>

<dl><dt>PTPRO </dt><dd>0.92 0.0935 PTPRO NM_030667 </dd></dl>

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<dl><dt>cnpto (official TDGF1) </dt><dd>0.92 0.0950 TDGF1 NM_003212 </dd></dl>

<dl><dt>HLA-DRB1 </dt><dd>0.93 0.0521 HLA-DRB1 NM_002124 </dd></dl>

Table 4.2A shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio> 1.0 and for which p <0.1. A Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using ILRD as a metric for the clinical outcome.

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>ALDOA </dt><dd>3.21 0.0189 ALDOA NM_000034 </dd></dl>

<dl><dt>DCK </dt><dd>2.60 0.0248 DCK NM_000788 </dd></dl>

<dl><dt>ITGB1 </dt><dd>2.58 0.0002 ITGB1 NM_002211 </dd></dl>

<dl><dt>COX2 </dt><dd>2.16 0.0198 PTGS2 NM_000963 </dd></dl>

<dl><dt>TJP1 </dt><dd>2.10 0.0122 TJP1 NM_003257 </dd></dl>

<dl><dt>STAT3 </dt><dd>1.87 0.0148 STAT3 NM_003150 </dd></dl>

<dl><dt>ANXA5 </dt><dd>1.83 0.0043 ANXA5 NM_B001154 </dd></dl>

<dl><dt>GHI BRAF mut4 </dt><dd>1.82 0.0024 GHI_BRAF_mut4 </dd></dl>

<dl><dt>TIMP1 </dt><dd>1.80 &lt;0.0001 TIMP1 NM_003254 </dd></dl>

<dl><dt>hMLH </dt><dd>1.80 0.0242 MLH1 NM_000249 </dd></dl>

<dl><dt>PADI4 </dt><dd>1.74 0.0288 PADI4 NM_012387 </dd></dl>

<dl><dt>rhoC </dt><dd>1.74 0.0093 RHOC NM_175744 </dd></dl>

<dl><dt>CYP3A4 </dt><dd>173 0.0219 CYP3A4 NM_017460 </dd></dl>

<dl><dt>WWOX </dt><dd>1.72 0.0467 WWOX NM_016373 </dd></dl>

<dl><dt>ANXA2 </dt><dd>1.70 0.0081 ANXA2 NM_004039 </dd></dl>

<dl><dt>LILRB3 </dt><dd>1.70 0.0295 LILRB3 NM_006864 </dd></dl>

<dl><dt>VIM </dt><dd>1.66 0.0015 VIM NM_003380 </dd></dl>

<dl><dt>FUS </dt><dd>1.65 0.0432 FUS NM_004960 </dd></dl>

<dl><dt>KCNH2 Iso a / b </dt><dd>1.64 0.0111 KCNH2 NM_000238 </dd></dl>

<dl><dt>RhoB </dt><dd>1.63 0.0019 Rhob NM_004040 </dd></dl>

<dl><dt>CRIP2 </dt><dd>1.62 0.0455 CRIP2 NM_001312 </dd></dl>

<dl><dt>AKT3 </dt><dd>1.60 0.0004 AKT3 NM_005465 </dd></dl>

<dl><dt>RBX1 </dt><dd>1.60 0.0195 RBX1 NM_014248 </dd></dl>

<dl><dt>HB-EGF </dt><dd>1.59 0.0032 HBEGF NM_001945 </dd></dl>

<dl><dt>NRP2 </dt><dd>1.55 0.0007 NRP2 NM_003872 </dd></dl>

<dl><dt>MSH3 </dt><dd>1.55 0.0353 MSH3 NM_002439 </dd></dl>

<dl><dt>PI3K </dt><dd>1.54 0.0651 PIK3C2B NM_002646 </dd></dl>

<dl><dt>BGN </dt><dd>1.54 0.0009 BGN NM_001711 </dd></dl>

<dl><dt>RAB6C </dt><dd>1.54 0.0210 RAB6C NM_032144 </dd></dl>

<dl><dt>CTSB </dt><dd>1.53 0.0415 CTSB NM_001908 </dd></dl>

<dl><dt>DLC1 </dt><dd>1.53 0.0047 DLC1 NM_006094 </dd></dl>

<dl><dt>p21 </dt><dd>1.53 0.0085 CDKN1A NM_000389 </dd></dl>

<dl><dt>CCNE2 variant 1 </dt><dd>1.52 0.0647 CCNE2 NM_057749 </dd></dl>

<dl><dt>CALD1 </dt><dd>1.51 0.0069 CALD1 NM_004342 </dd></dl>

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<dl><dt>SBA2 </dt><dd>1.51 0.0202 WSB2 NM_018639 </dd></dl>

<dl><dt>SIR2 </dt><dd>1.51 0.0028 SIRT1 NM_012238 </dd></dl>

<dl><dt>ITGA5 </dt><dd>1.50 0.0006 ITGA5 NM_002205 </dd></dl>

<dl><dt>RAP1GDS1 </dt><dd>1.50 0.0317 RAP1GDS1 NM_021159 </dd></dl>

<dl><dt>CTHRC1 </dt><dd>1.46 0.0010 CTHRC1 NM_138455 </dd></dl>

<dl><dt>STC1 </dt><dd>1.46 0.0083 STC1 NM_003155 </dd></dl>

<dl><dt>KLF6 </dt><dd>1.46 0.0362 KLF6 NM_001300 </dd></dl>

<dl><dt>CDC42BPA </dt><dd>1.45 0.0187 CDC42BPA NM_003607 </dd></dl>

<dl><dt>CEBPB </dt><dd>1.45 0.0605 CEBPB NM_005194 </dd></dl>

<dl><dt>LAMC2 </dt><dd>1.45 0.0031 LAMC2 NM_005562 </dd></dl>

<dl><dt>TGFBR1 </dt><dd>1.45 0.0824 TGFBR1 NM_004612 </dd></dl>

<dl><dt>TLN1 </dt><dd>1.45 0.0730 TLN1 NM_006289 </dd></dl>

<dl><dt>CDC42 </dt><dd>1.44 0.0387 CDC42 NM_001791 </dd></dl>

<dl><dt>FYN </dt><dd>1.43 0.0070 FYN NM_002037 </dd></dl>

<dl><dt>IGFBP7 </dt><dd>1.43 0.0283 IGFBP7 NM_001553 </dd></dl>

<dl><dt>ARG </dt><dd>1.43 0.0119 ABL2 NM_005158 </dd></dl>

<dl><dt>HIF1A </dt><dd>1.42 0.0397 HIF1A NM_001530 </dd></dl>

<dl><dt>FST </dt><dd>1.42 0.0460 FST NM_006350 </dd></dl>

<dl><dt>S100A1 </dt><dd>1.42 0.0473 S100A1 NM_006271 </dd></dl>

<dl><dt>FAP </dt><dd>1.42 0.0023 FAP NM_004460 </dd></dl>

<dl><dt>DUSP1 </dt><dd>1.42 0.0014 DUSP1 NM_004417 </dd></dl>

<dl><dt>EPAS1 </dt><dd>1.41 0.0494 EPAS1 NM_001430 </dd></dl>

<dl><dt>Grb10 </dt><dd>1.41 0.0027 GRB10 NM_005311 </dd></dl>

<dl><dt>VEGFC </dt><dd>1.41 0.0894 VEGFC NM_005429 </dd></dl>

<dl><dt>INHBB </dt><dd>1.41 0.0710 INHBB NM_002193 </dd></dl>

<dl><dt>GADD45B </dt><dd>1.40 0.0023 GADD45B NM_015675 </dd></dl>

<dl><dt>UBC </dt><dd>1.40 0.0368 UBC NM_021009 </dd></dl>

<dl><dt>GJA1 </dt><dd>1.40 0.0053 GJA1 NM_000165 </dd></dl>

<dl><dt>COL1A2 </dt><dd>1.40 0.0086 COL1A2 NM_000089 </dd></dl>

<dl><dt>RBM5 </dt><dd>1.40 0.0423 RBM5 NM_005778 </dd></dl>

<dl><dt>ROCK1 </dt><dd>1.39 0.0604 ROCK1 NM_005406 </dd></dl>

<dl><dt>CTGF </dt><dd>1.39 0.0081 CTGF NM_001901 </dd></dl>

<dl><dt>FLT4 </dt><dd>1.39 0.0978 FLT4 NM_002020 </dd></dl>

<dl><dt>PDGFC </dt><dd>1.39 0.0052 PDGFC NM_016205 </dd></dl>

<dl><dt>INHBA </dt><dd>1.39 0.0058 INHBA NM_002192 </dd></dl>

<dl><dt>LOXL2 </dt><dd>1.38 0.0209 LOXL2 NM_002318 </dd></dl>

<dl><dt>THBS1 </dt><dd>1.37 0.0090 THBS1 NM_003246 </dd></dl>

<dl><dt>ITGAV </dt><dd>1.37 0.0298 ITGAV NM_002210 </dd></dl>

<dl><dt>NCAM1 </dt><dd>1.36 0.0714 NCAM1 NM_000615 </dd></dl>

<dl><dt>PTHR1 </dt><dd>1.35 0.0410 PTHR1 NM_000316 </dd></dl>

<dl><dt>TIMP2 </dt><dd>1.35 0.0446 TIMP2 NM_003255 </dd></dl>

08-11-2014 E07717900

<dl><dt>LOX </dt><dd>1.35 0.0041 LOX NM_002317 </dd></dl>

<dl><dt>SPARC </dt><dd>1.35 0.0292 SPARC NM_003118 </dd></dl>

<dl><dt>TAGLN </dt><dd>1.34 0.0222 TAGLN NM_003186 </dd></dl>

<dl><dt>CYR61 </dt><dd>1.34 0.0086 CYR61 NM_001554 </dd></dl>

<dl><dt>RANBP9 </dt><dd>1.34 0.0553 RANBP9 NM_005493 </dd></dl>

<dl><dt>GADD45 </dt><dd>1.34 0.0604 GADD45A NM_001924 </dd></dl>

<dl><dt>S100A4 </dt><dd>1.34 0.0141 S100A4 NM_002961 </dd></dl>

<dl><dt>SNAI2 </dt><dd>1.33 0.0263 SNAI2 NM_003068 </dd></dl>

<dl><dt>EGR1 </dt><dd>1.33 0.0174 EGR1 NM_001964 </dd></dl>

<dl><dt>CDH11 </dt><dd>1.33 0.0355 CDH11 NM_001797 </dd></dl>

<dl><dt>YES </dt><dd>1.33 0.0967 YES NM_001041 </dd></dl>

<dl><dt>PTK2 </dt><dd>1.33 0.0911 PTK2 NM_005607 </dd></dl>

<dl><dt>MCP1 </dt><dd>1.32 0.0215 CCL2 NM_002982 </dd></dl>

<dl><dt>PCAF </dt><dd>1.32 0.0463 PCAF NM_003884 </dd></dl>

<dl><dt>c-abl </dt><dd>1.32 0.0868 ABL1 NM_005157 </dd></dl>

<dl><dt>TIMP3 </dt><dd>1.32 0.0455 TIMP3 NM_000362 </dd></dl>

<dl><dt>ANGPT2 </dt><dd>1.31 0.0711 ANGPT2 NM_001147 </dd></dl>

<dl><dt>NOTCH2 </dt><dd>1.30 0.0645 NOTCH2 NM_024408 </dd></dl>

<dl><dt>GBP2 </dt><dd>1.30 0.0218 GBP2 NM_004120 </dd></dl>

<dl><dt>PAI1 </dt><dd>1.30 0.0022 SERPINE1 NM_000602 </dd></dl>

<dl><dt>CXCR4 </dt><dd>1.30 0.0341 CXCR4 NM_003467 </dd></dl>

<dl><dt>BCAS1 </dt><dd>1.30 0.0060 BCAS1 NM_003657 </dd></dl>

<dl><dt>COL1A1 </dt><dd>1.29 0.0349 COL1A1 NM_000088 </dd></dl>

<dl><dt>PIM1 </dt><dd>1.29 0.0507 PIM1 NM_002648 </dd></dl>

<dl><dt>PDGFB </dt><dd>1.29 0.0288 PDGFB NM_002608 </dd></dl>

<dl><dt>Bcl2 </dt><dd>1.29 0.0270 BCL2 NM_000633 </dd></dl>

<dl><dt>SLPI </dt><dd>1.29 0.0222 SLPI NM_003064 </dd></dl>

<dl><dt>IGFBP5 </dt><dd>1.29 0.0676 IGFBP5 NM_000599 </dd></dl>

<dl><dt>ANXA1 </dt><dd>1.29 0.0690 ANXA1 NM_000700 </dd></dl>

<dl><dt>FGFR1 </dt><dd>1.28 0.0790 FGFR1 NM_023109 </dd></dl>

<dl><dt>CAPG </dt><dd>1.28 0.0987 CAPG NM_001747 </dd></dl>

<dl><dt>PRKCA </dt><dd>1.28 0.0548 PRKCA NM_002737 </dd></dl>

<dl><dt>EPHA2 </dt><dd>1.28 0.0339 EPHA2 NM_004431 </dd></dl>

<dl><dt>AKAP12 </dt><dd>1.28 0.0215 AKAP12 NM_005100 </dd></dl>

<dl><dt>FOS </dt><dd>1.28 0.0219 FOS NM_005252 </dd></dl>

<dl><dt>CXCL12 </dt><dd>1.27 0.0169 CXCL12 NM_000609 </dd></dl>

<dl><dt>GCNT1 </dt><dd>1.27 0.0875 GCNT1 NM_001490 </dd></dl>

<dl><dt>IGFBP3 </dt><dd>1.27 0.0499 IGFBP3 NM_000598 </dd></dl>

<dl><dt>DPYD </dt><dd>1.27 0.0259 DPYD NM_000110 </dd></dl>

<dl><dt>CD68 </dt><dd>1.27 0.0752 CD68 NM_001251 </dd></dl>

<dl><dt>EFNA1 </dt><dd>1.27 0.0890 EFNA1 NM_004428 </dd></dl>

11-08-2014

<dl><dt>ABCC5 </dt><dd>1.26 0.0536 ABCC5 NM_005688 </dd></dl>

<dl><dt>TUBB </dt><dd>1.26 0.0635 TUBB2 NM_001069 </dd></dl>

<dl><dt>PDGFA </dt><dd>1.26 0.0676 NM_002607 </dd></dl>

<dl><dt>DAPK1 </dt><dd>1.26 0.0701 DAPK1 NM_004938 </dd></dl>

<dl><dt>SFRP2 </dt><dd>1.25 0.0109 SFRP2 NM_003013 </dd></dl>

<dl><dt>ID3 </dt><dd>1.25 0.0744 ID3 NM_002167 </dd></dl>

<dl><dt>CTSL </dt><dd>1.25 0.0679 CTSL NM_001912 </dd></dl>

<dl><dt>LAMA3 </dt><dd>1.25 0.0299 LAMA3 NM_000227 </dd></dl>

<dl><dt>KRT19 </dt><dd>1.25 0.0982 KRT19 NM_002276 </dd></dl>

<dl><dt>S100A8 </dt><dd>1.25 0.0228 S100A8 NM_002964 </dd></dl>

<dl><dt>IL6 </dt><dd>1.25 0.0933 IL6 NM_000600 </dd></dl>

<dl><dt>MRP3 </dt><dd>1.25 0.0538 ABCC3 NM_003786 </dd></dl>

<dl><dt>FES </dt><dd>1.25 0.0694 FES NM_002005 </dd></dl>

<dl><dt>AP-1 (official JUN) </dt><dd>1.25 0.0974 JUN NM_002228 </dd></dl>

<dl><dt>WISP1 </dt><dd>1.24 0.0897 WISP1 NM_003882 </dd></dl>

<dl><dt>SFRP4 </dt><dd>1.24 0.0250 SFRP4 NM_003014 </dd></dl>

<dl><dt>TGFBI </dt><dd>1.24 0.0692 TGFBI NM_000358 </dd></dl>

<dl><dt>Maspina </dt><dd>1.24 0.0152 SERPINB5 NM_002639 </dd></dl>

<dl><dt>HOXB7 </dt><dd>1.23 0.0541 HOXB7 NM_004502 </dd></dl>

<dl><dt>P14ARF </dt><dd>1.23 0.0944 S78535 </dd></dl>

<dl><dt>HSPA1A </dt><dd>1.23 0.0259 HSPA1A NM_005345 </dd></dl>

<dl><dt>EGR3 </dt><dd>1.22 0.0312 EGR3 NM_004430 </dd></dl>

<dl><dt>CRYAB </dt><dd>1.22 0.0483 CRYAB NM_001885 </dd></dl>

<dl><dt>ALDH1A1 </dt><dd>1.22 0.0372 ALDH1A1 NM_000689 </dd></dl>

<dl><dt>TGFB3 </dt><dd>1.22 0.0673 TGFB3 NM_003239 </dd></dl>

<dl><dt>KLK6 </dt><dd>1.21 0.0288 KLK6 NM_002774 </dd></dl>

<dl><dt>ANTXR1 </dt><dd>1.21 0.0942 ANTXR1 NM_032208 </dd></dl>

<dl><dt>FZD6 </dt><dd>1.20 0.0479 FZD6 NM_003506 </dd></dl>

<dl><dt>ILT-2 </dt><dd>1.20 0.0930 LILRB1 NM_006669 </dd></dl>

<dl><dt>S100A2 </dt><dd>1.20 0.0116 S100A2 NM_005978 </dd></dl>

<dl><dt>MMP7 </dt><dd>1.18 0.0987 MMP7 NM_002423 </dd></dl>

<dl><dt>FABP4 </dt><dd>1.17 0.0371 FABP4 NM_001442 </dd></dl>

<dl><dt>OPN, osteopontin </dt><dd>1.17 0.0301 SPP1 NM_000582 </dd></dl>

<dl><dt>KLK10 </dt><dd>1.16 0.0581 KLK10 NM_002776 </dd></dl>

<dl><dt>pS2 </dt><dd>1.15 0.0186 TFF1 NM_003225 </dd></dl>

<dl><dt>REG4 </dt><dd>1.14 0.0053 REG4 NM_032044 </dd></dl>

<dl><dt>MUC2 </dt><dd>1.09 0.0429 MUC2 NM_002457 </dd></dl>

Table 4.2B shows associations between clinical outcome and gene expression for genes that demonstrated a risk ratio &lt;1.0 and for which p &lt;0.1. A Cox proportional hazards regression analysis of one variable was applied in patients in stage II (Duke B) and state III (Duke C) combined using ILRD as a metric for the clinical outcome.

<dl><dt>Gen </dt><dd>Risk ratio P value Official symbol Registry number </dd></dl>

<dl><dt>HSPA8 </dt><dd>0.48 0.0114 HSPA8 NM_006597 </dd></dl>

<dl><dt>RPS13 </dt><dd>0.64 0.0082 RPS13 NM_001017 </dd></dl>

<dl><dt>NDUFS3 </dt><dd>0.66 0.0096 NDUFS3 NM_004551 </dd></dl>

<dl><dt>ST14 </dt><dd>0.66 0.0132 ST14 NM_021978 </dd></dl>

<dl><dt>LMNB1 </dt><dd>0.66 0.0135 LMNB1 NM_005573 </dd></dl>

<dl><dt>TMSB4X </dt><dd>0.67 0.0039 TMSB4X NM_021109 </dd></dl>

<dl><dt>DHFR </dt><dd>0.68 0.0260 DHFR NM_000791 </dd></dl>

<dl><dt>BRCA1 </dt><dd>0.68 0.0029 BRCA1 NM_007295 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.68 0.0151 SKP2 NM_005983 </dd></dl>

<dl><dt>SLC25A3 </dt><dd>0.69 0.0265 SLC25A3 NM_213611 </dd></dl>

<dl><dt>CDC20 </dt><dd>0.69 0.0048 CDC20 NM_001255 </dd></dl>

<dl><dt>RPLPO </dt><dd>0.70 0.0320 RPLPO NM_001002 </dd></dl>

<dl><dt>TCF-1 </dt><dd>0.70 0.0013 TCF1 NM_000545 </dd></dl>

<dl><dt>RRM1 </dt><dd>0.71 0.0598 RRM1 NM_001033 </dd></dl>

<dl><dt>ATP5A1 </dt><dd>0.71 0.0827 ATP5A1 NM_004046 </dd></dl>

<dl><dt>NME1 </dt><dd>0.73 0.0378 NM_E1 NM_000269 </dd></dl>

<dl><dt>CKS2 </dt><dd>0.74 0.0537 CKS2 NM_001827 </dd></dl>

<dl><dt>IE24 </dt><dd>0.74 0.0639 IE24 NM_004879 </dd></dl>

<dl><dt>C20 orf1 </dt><dd>0.74 0.0435 TPX2 NM_012112 </dd></dl>

<dl><dt>SDC1 </dt><dd>0.74 0.0930 SDC1 NM_002997 </dd></dl>

<dl><dt>CSEL1 </dt><dd>0.75 0.0443 CSE1L NM_001316 </dd></dl>

<dl><dt>ABCC6 </dt><dd>0.76 0.0416 ABCC6 NM_001171 </dd></dl>

<dl><dt>MCM2 </dt><dd>0.76 0.0136 MCM2 NM_004526 </dd></dl>

<dl><dt>NFKBp65 </dt><dd>0.77 0.0672 RELAY NM_021975 </dd></dl>

<dl><dt>EPHB2 </dt><dd>0.77 0.0133 EPHB2 NM_004442 </dd></dl>

<dl><dt>FASN </dt><dd>0.78 0.0980 FASN NM_004104 </dd></dl>

<dl><dt>AUR KB</dt><dd>0.78 0.0528 AURKB NM_004217 </dd></dl>

<dl><dt>VDR </dt><dd>0.79 0.0832 VDR NM_000376 </dd></dl>

<dl><dt>UMPS </dt><dd>0.80 0.0721 UMPS NM_000373 </dd></dl>

<dl><dt>UBE2C </dt><dd>0.81 0.0860 UBE2C NM_007019 </dd></dl>

<dl><dt>CMYC </dt><dd>0.82 0.0742 MYC NM_002467 </dd></dl>

<dl><dt>MYBL2 </dt><dd>0.83 0.0780 MYBL2 NM_002466 </dd></dl>

<dl><dt>Cdx2 </dt><dd>0.84 0.0392 CDX2 NM_001265 </dd></dl>

<dl><dt>MX1 </dt><dd>0.85 0.0786 MX1 NM_002462 </dd></dl>

<dl><dt>EREG </dt><dd>0.85 0.0638 EREG NM_001432 </dd></dl>

<dl><dt>AREG </dt><dd>0.85 0.0295 AREG NM_001657 </dd></dl>

Table 5.2A shows associations between gene expression and ILR, controlling particular demographic and clinical characteristics of patients included in the analysis. All genes whose expression correlates with ILR (p <0.1) and that demonstrate a risk ratio> 1 are listed in a multi-variant analysis that includes the following variables: tumor location, year of surgery, tumor grade , treatment protocol (C-01

or C-02), treatment with BCG (yes or no) and classification of patients according to lymph node status as follows: 0 positive nodes and &lt;12 nodes examined, 0 positive nodes and ≥12 nodes examined, 1-3 nodes

positive and ≥4 positive nodes.

<dl><dt>Gen </dt><dd>Risk ratio LR square chi GL P value Official symbol Registry number </dd></dl>

<dl><dt>RARB </dt><dd>2.02 3.42 1 0.0644 RARB NM_016152 </dd></dl>

<dl><dt>COX2 </dt><dd>1.69 3.13 1 0.0768 PTGS2 NM_000963 </dd></dl>

<dl><dt>RhoC </dt><dd>1.60 8.71 1 0.0032 RHOC NM_175744 </dd></dl>

<dl><dt>CYP3A4 </dt><dd>1.57 5.15 1 0.0233 CYP3A4 NM_017460 </dd></dl>

<dl><dt>RhoB </dt><dd>1.54 12.40 1 0.0004 Rhob NM_004040 </dd></dl>

<dl><dt>ANXA2 </dt><dd>1.54 7.01 1 0.0081 ANXA2 NM_004039 </dd></dl>

<dl><dt>ITGB1 </dt><dd>1.54 5.54 1 0.0186 ITGB1 NM_002211 </dd></dl>

<dl><dt>NTN1 </dt><dd>1.53 3.63 1 0.0568 NTN1 NM_004822 </dd></dl>

<dl><dt>KRAS2 </dt><dd>1.51 4.83 1 0.0279 KRAS NM_004985 </dd></dl>

<dl><dt>IGFBP7 </dt><dd>1.44 8.53 1 0.0035 IGFBP7 NM_001553 </dd></dl>

<dl><dt>TIMP1 </dt><dd>1.43 9.03 1 0.0027 TIMP1 NM_003254 </dd></dl>

<dl><dt>WWOX </dt><dd>1.43 2.73 1 0.0988 WWOX NM_016373 </dd></dl>

<dl><dt>CYP1B1 </dt><dd>1.39 3.69 1 0.0548 CYP1B1 NM_000104 </dd></dl>

<dl><dt>KCNH2 iso a / b </dt><dd>1.38 3.23 1 0.0723 KCNH2 NM_000238 </dd></dl>

<dl><dt>STC1 </dt><dd>1.37 6.55 1 0.0105 STC1 NM_003155 </dd></dl>

<dl><dt>ITGAV </dt><dd>1.37 9.37 1 0.0022 ITGAV NM_002210 </dd></dl>

<dl><dt>VEGFC </dt><dd>1.37 3.62 1 0.0571 VEGFC NM_005429 </dd></dl>

<dl><dt>G-Catenin </dt><dd>1.36 4.78 1 0.0287 JUP NM_002230 </dd></dl>

<dl><dt>S100A1 </dt><dd>1.34 4.12 1 0.0423 S100A1 NM_006271 </dd></dl>

<dl><dt>GADD45B </dt><dd>1.34 9.63 1 0.0019 GADD45B NM_015675 </dd></dl>

<dl><dt>NCAM1 </dt><dd>1.33 3.00 1 0.0832 NCAM1 NM_000615 </dd></dl>

<dl><dt>CALD1 </dt><dd>1.33 6.05 1 0.0139 CALD1 NM_004342 </dd></dl>

<dl><dt>FST </dt><dd>1.33 4.24 1 0.0396 FST NM_006350 </dd></dl>

<dl><dt>INHBA </dt><dd>1.33 9.68 1 0.0019 INHBA NM_002192 </dd></dl>

<dl><dt>BGN </dt><dd>1.33 7.27 1 0.0070 BGN NM_001711 </dd></dl>

<dl><dt>Claudina 4 </dt><dd>1.33 7.13 1 0.0076 CLDN4 NM_001305 </dd></dl>

<dl><dt>CEBPB </dt><dd>1.33 2.96 1 0.0851 CEBPB NM_005194 </dd></dl>

<dl><dt>LAMC2 </dt><dd>1.32 8.62 1 0.0033 LAMC2 NM_005562 </dd></dl>

<dl><dt>SPINT2 </dt><dd>1.32 3.14 1 0.0762 SPINT2 NM_021102 </dd></dl>

<dl><dt>AKT3 </dt><dd>1.32 7.54 1 0.0060 AKT3 NM_005465 </dd></dl>

<dl><dt>TIMP3 </dt><dd>1.32 6.33 1 0.0119 TIMP3 NM_000362 </dd></dl>

<dl><dt>MAPK14 </dt><dd>1.31 2.75 1 0.0972 MAPK14 NM_139012 </dd></dl>

<dl><dt>HB-EGF </dt><dd>1.31 4.74 1 0.0294 HBEGF NM_001945 </dd></dl>

<dl><dt>DUSP1 </dt><dd>1.30 11.34 1 0.0008 DUSP1 NM_004417 </dd></dl>

<dl><dt>EFNA1 </dt><dd>1.30 5.87 1 0.0154 EFNA1 NM_004428 </dd></dl>

<dl><dt>PTK2 </dt><dd>1.29 3.60 1 0.0576 PTK2 NM_005607 </dd></dl>

<dl><dt>DLC1 </dt><dd>1.29 5.19 1 0.0227 DLC1 NM_006094 </dd></dl>

<dl><dt>EPAS1 </dt><dd>1.28 3.30 1 0.0693 EPAS1 NM_001430 </dd></dl>

<dl><dt>THBS1 </dt><dd>1.28 7.51 1 0.0061 THBS1 NM_003246 </dd></dl>

<dl><dt>TIMP2 </dt><dd>1.28 4.20 1 0.0404 TIMP2 NM_003255 </dd></dl>

<dl><dt>TGFBI </dt><dd>1.27 6.68 1 0.0098 TGFBI NM_000358 </dd></dl>

<dl><dt>DKK1 </dt><dd>1.27 3.05 1 0.0806 DKK1 NM_012242 </dd></dl>

<dl><dt>SPARC </dt><dd>1.26 4.37 1 0.0366 SPARC NM_003118 </dd></dl>

<dl><dt>PDGFC </dt><dd>1.26 6.74 1 0.0094 PDGFC NM_016205 </dd></dl>

<dl><dt>RAB6C </dt><dd>1.26 3.27 1 0.0704 RAB6C NM_032144 </dd></dl>

<dl><dt>LOXL2 </dt><dd>1.26 4.48 1 0.0343 LOXL2 NM_002318 </dd></dl>

<dl><dt>CD68 </dt><dd>1.25 4.68 1 0.0305 CD68 NM_001251 </dd></dl>

<dl><dt>LOX </dt><dd>1.25 7.16 1 0.0075 LOX NM_002317 </dd></dl>

<dl><dt>CDC42BPA </dt><dd>1.25 3.35 1 0.0671 CDC42BPA NM_003607 </dd></dl>

<dl><dt>TAGLN </dt><dd>1.25 4.83 1 0.0279 TAGLN NM_003186 </dd></dl>

<dl><dt>CTHRC1 </dt><dd>1.25 5.96 1 0.0146 CTHRC1 NM_138455 </dd></dl>

<dl><dt>PDGFA </dt><dd>1.25 4.63 1 0.0314 NM_002607 </dd></dl>

<dl><dt>TMEPAI </dt><dd>1.24 5.63 1 0.0176 TMEPAI NM_020182 </dd></dl>

<dl><dt>RAB32 </dt><dd>1.24 4.48 1 0.0343 RAB32 NM_006834 </dd></dl>

<dl><dt>HSPA1A </dt><dd>1.24 8.19 1 0.0042 HSPA1A NM_005345 </dd></dl>

<dl><dt>VIM </dt><dd>1.24 2.97 1 0.0848 VIM NM_003380 </dd></dl>

<dl><dt>IGFBP5 </dt><dd>1.23 3.69 1 0.0549 IGFBP5 NM_000599 </dd></dl>

<dl><dt>EGR1 </dt><dd>1.23 5.12 1 0.0236 EGR1 NM_001964 </dd></dl>

<dl><dt>ANGPT2 </dt><dd>1.23 2.96 1 0.0852 ANGPT2 NM_001147 </dd></dl>

<dl><dt>NDRG1 </dt><dd>1.22 2.91 1 0.0879 NDRG1 NM_006096 </dd></dl>

<dl><dt>VEGF_altsplice1 </dt><dd>1.22 4.08 1 0.0433 AF486837 </dd></dl>

<dl><dt>SLPI </dt><dd>1.22 4.94 1 0.0262 SLPI NM_003064 </dd></dl>

<dl><dt>FOS </dt><dd>1.22 5.67 1 0.0172 FOS NM_005252 </dd></dl>

<dl><dt>VEGF </dt><dd>1.22 2.80 1 0.0942 VEGF NM_003376 </dd></dl>

<dl><dt>ADAMTS12 </dt><dd>1.22 4.40 1 0.0359 ADAMTS12 NM_030955 </dd></dl>

<dl><dt>Maspina </dt><dd>1.22 7.60 1 0.0058 SERPINB5 NM_002639 </dd></dl>

<dl><dt>CGB </dt><dd>1.22 3.25 1 0.0713 CGB NM_000737 </dd></dl>

<dl><dt>CYR61 </dt><dd>1.21 5.22 1 0.0224 CYR61 NM_001554 </dd></dl>

<dl><dt>GJB2 </dt><dd>1.21 3.77 1 0.0522 GJB2 NM_004004 </dd></dl>

<dl><dt>IGFBP3 </dt><dd>1.21 4.24 1 0.0396 IGFBP3 NM_000598 </dd></dl>

<dl><dt>PRKCA </dt><dd>1.21 3.81 1 0.0508 PRKCA NM_002737 </dd></dl>

<dl><dt>S100P </dt><dd>1.21 6.98 1 0.0082 S100P NM_005980 </dd></dl>

<dl><dt>NRP2 </dt><dd>1.21 3.25 1 0.0714 NRP2 NM_003872 </dd></dl>

<dl><dt>EFNB2 </dt><dd>1.21 3.00 1 0.0834 EFNB2 NM_004093 </dd></dl>

<dl><dt>COL1A2 </dt><dd>1.21 3.59 1 0.0581 COL1A2 NM_000089 </dd></dl>

<dl><dt>VEGFB </dt><dd>1.20 2.80 1 0.0942 VEGFB NM_003377 </dd></dl>

<dl><dt>HOXB7 </dt><dd>1.20 4.37 1 0.0367 HOXB7 NM_004502 </dd></dl>

<dl><dt>Grb10 </dt><dd>1.20 3.91 1 0.0480 GRB10 NM_005311 </dd></dl>

<dl><dt>FAP </dt><dd>1.20 4.12 1 0.0425 FAP NM_004460 </dd></dl>

<dl><dt>GJA1 </dt><dd>1.20 4.80 1 0.0285 GJA1 NM_000165 </dd></dl>

<dl><dt>CTGF </dt><dd>1.19 3.38 1 0.0660 CTGF NM_001901 </dd></dl>

<dl><dt>NR4A1 </dt><dd>1.18 5.13 1 0.0235 NR4A1 NM_002135 </dd></dl>

<dl><dt>COL1A1 </dt><dd>1.18 2.77 1 0.0961 COL1A1 NM_000088 </dd></dl>

<dl><dt>ABCC5 </dt><dd>1.17 2.80 1 0.0945 ABCC5 NM_005688 </dd></dl>

<dl><dt>EMP1 </dt><dd>1.17 3.06 1 0.0804 EMP1 NM_001423 </dd></dl>

<dl><dt>SFRP2 </dt><dd>1.17 4.89 1 0.0270 SFRP2 NM_003013 </dd></dl>

<dl><dt>SLC2A1 </dt><dd>1.17 3.52 1 0.0606 SLC2A1 NM_006516 </dd></dl>

<dl><dt>F3 </dt><dd>1.17 3.10 1 0.0783 F3 NM_001993 </dd></dl>

<dl><dt>S100A4 </dt><dd>1.17 2.87 1 0.0900 S100A4 NM_002961 </dd></dl>

<dl><dt>BRK </dt><dd>1.17 2.81 1 0.0935 PTK6 NM_005975 </dd></dl>

<dl><dt>CRYAB </dt><dd>1.17 3.77 1 0.0523 CRYAB NM_001885 </dd></dl>

<dl><dt>MDK </dt><dd>1.16 3.84 1 0.0500 MDK NM_002391 </dd></dl>

<dl><dt>OPN, osteopontin </dt><dd>1.16 6.07 1 0.0138 SPP1 NM_000582 </dd></dl>

<dl><dt>SFRP4 </dt><dd>1.16 4.09 1 0.0432 SFRP4 NM_003014 </dd></dl>

<dl><dt>SIAT4A </dt><dd>1.16 2.76 1 0.0969 ST3GAL1 NM_003033 </dd></dl>

<dl><dt>LAMA3 </dt><dd>1.16 3.23 1 0.0725 LAMA3 NM_000227 </dd></dl>

<dl><dt>AKAP12 </dt><dd>1.15 2.74 1 0.0976 AKAP12 NM_005100 </dd></dl>

<dl><dt>KLK10 </dt><dd>1.15 5.23 1 0.0221 KLK10 NM_002776 </dd></dl>

<dl><dt>EGR3 </dt><dd>1.14 3.16 1 0.0755 EGR3 NM_004430 </dd></dl>

<dl><dt>PAI1 </dt><dd>1.13 3.39 1 0.0655 SERPINE1 NM_000602 </dd></dl>

<dl><dt>CEACAM6 </dt><dd>1.13 2.98 1 0.0845 CEACAM6 NM_002483 </dd></dl>

<dl><dt>KLK6 </dt><dd>1.13 3.74 1 0.0532 KLK6 NM_002774 </dd></dl>

<dl><dt>Nkd-1 </dt><dd>1.11 3.34 1 0.0674 NKD1 NM_033119 </dd></dl>

<dl><dt>IGFBP2 </dt><dd>1.11 3.15 1 0.0758 IGFBP2 NM_000597 </dd></dl>

<dl><dt>REG4 </dt><dd>1.08 3.51 1 0.0610 REG4 NM_032044 </dd></dl>

Table 5.2B shows associations between gene expression and ILR, controlling particular demographic and clinical characteristics of patients included in the analysis. All genes whose expression correlates with ILR (p &lt;0.1) and that demonstrate a risk ratio &lt;1 are listed in a multi-variant analysis that includes the following variables: tumor location, year of surgery, tumor grade , treatment protocol (C-01

or C-02), treatment with BCG (yes or no) and classification of patients according to lymph node status as follows: 0 positive nodes and &lt;12 nodes examined, 0 positive nodes and ≥12 nodes examined, 1-3 nodes positive and ≥4 positive nodes.

<dl><dt>Gen </dt><dd>Risk ratio LR square chi GL P value Official symbol Registry number </dd></dl>

<dl><dt>Fasl </dt><dd>0.43 5.57 1 0.0183 FASLG NM_000639 </dd></dl>

<dl><dt>BFGF </dt><dd>0.57 4.68 1 0.0306 NUDT6 NM_007083 </dd></dl>

<dl><dt>EstR1 </dt><dd>0.57 3.22 1 0.0726 ESR1 NM_000125 </dd></dl>

<dl><dt>IFIT1 </dt><dd>0.60 4.30 1 0.0381 IFIT1 NM_001548 </dd></dl>

<dl><dt>KLRK1 </dt><dd>0.64 10.81 1 0.0010 KLRK1 NM_007360 </dd></dl>

<dl><dt>E2F1 </dt><dd>0.65 7.49 1 0.0062 E2F1 NM_005225 </dd></dl>

<dl><dt>BRCA1 </dt><dd>0.66 16.33 1 &lt;0.0001 BRCA1 NM_007295 </dd></dl>

<dl><dt>RAD54L </dt><dd>0.67 6.36 1 0.0117 RAD54L NM_003579 </dd></dl>

<dl><dt>ATP5A1 </dt><dd>0.67 5.50 1 0.0190 ATP5A1 NM_004046 </dd></dl>

<dl><dt>MCM3 </dt><dd>0.68 2.84 1 0.0922 MCM3 NM_002388 </dd></dl>

<dl><dt>DHFR </dt><dd>0.68 7.44 1 0.0064 DHFR NM_000791 </dd></dl>

<dl><dt>HSPA8 </dt><dd>0.68 2.96 1 0.0855 HSPA8 NM_006597 </dd></dl>

<dl><dt>APG-1 </dt><dd>0.71 5.86 1 0.0155 HSPA4L NM_014278 </dd></dl>

<dl><dt>BRCA2 </dt><dd>0.71 4.69 1 0.0304 BRCA2 NM_000059 </dd></dl>

<dl><dt>TRAIL </dt><dd>0.71 7.27 1 0.0070 TNFSF10 NM_003810 </dd></dl>

<dl><dt>SLC25A3 </dt><dd>0.71 5.56 1 0.0184 SLC25A3 NM_213611 </dd></dl>

<dl><dt>PPM1D </dt><dd>0.72 8.02 1 0.0046 PPM1D NM_003620 </dd></dl>

<dl><dt>Chk1 </dt><dd>0.73 6.61 1 0.0102 CHEK1 NM_001274 </dd></dl>

<dl><dt>CD80 </dt><dd>0.73 6.85 1 0.0089 CD80 NM_005191 </dd></dl>

<dl><dt>MADH2 </dt><dd>0.73 3.93 1 0.0476 SMAD2 NM_005901 </dd></dl>

<dl><dt>KIF22 </dt><dd>0.75 5.77 1 0.0163 KIF22 NM_007317 </dd></dl>

<dl><dt>TNFRSF5 </dt><dd>0.76 3.52 1 0.0607 CD40 NM_001250 </dd></dl>

<dl><dt>C20 orf1 </dt><dd>0.76 4.82 1 0.0281 TPX2 NM_012112 </dd></dl>

<dl><dt>ENO1 </dt><dd>0.76 2.88 1 0.0894 ENO1 NM_001428 </dd></dl>

<dl><dt>PRKCB1 </dt><dd>0.77 4.25 1 0.0393 PRKCB1 NM_002738 </dd></dl>

<dl><dt>RAF1 </dt><dd>0.77 4.17 1 0.0412 RAF1 NM_002880 </dd></dl>

<dl><dt>RRM1 </dt><dd>0.78 3.07 1 0.0799 RRM1 NM_001033 </dd></dl>

<dl><dt>UBE2M </dt><dd>0.78 4.43 1 0.0352 UBE2M NM_003969 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.79 3.42 1 0.0644 SKP2 NM_005983 </dd></dl>

<dl><dt>DUT </dt><dd>0.79 4.38 1 0.0364 DUT NM_001948 </dd></dl>

<dl><dt>IE24 </dt><dd>0.80 2.85 1 0.0912 IE24 NM_004879 </dd></dl>

<dl><dt>UMPS </dt><dd>0.80 4.96 1 0.0260 UMPS NM_000373 </dd></dl>

<dl><dt>EFP </dt><dd>0.81 3.83 1 0.0502 TRIM25 NM_005082 </dd></dl>

<dl><dt>HRAS </dt><dd>0.81 3.80 1 0.0513 HRAS NM_005343 </dd></dl>

<dl><dt>CDC20 </dt><dd>0.81 3.78 1 0.0519 CDC20 NM_001255 </dd></dl>

<dl><dt>CSF1 </dt><dd>0.82 2.86 1 0.0910 CSF1 NM_000757 </dd></dl>

<dl><dt>CKS2 </dt><dd>0.82 2.90 1 0.0886 CKS2 NM_001827 </dd></dl>

<dl><dt>ABCB1 </dt><dd>0.82 4.02 1 0.0450 ABCB1 NM_000927 </dd></dl>

<dl><dt>CDC6 </dt><dd>0.83 4.23 1 0.0397 CDC6 NM_001254 </dd></dl>

<dl><dt>GBP1 </dt><dd>0.83 4.34 1 0.0373 GBP1 NM_002053 </dd></dl>

<dl><dt>SURV </dt><dd>0.83 2.91 1 0.0878 BIRC5 NM_001168 </dd></dl>

<dl><dt>CCNE2 </dt><dd>0.83 2.75 1 0.0975 CCNE2 NM_057749 </dd></dl>

<dl><dt>RRM2 </dt><dd>0.83 4.19 1 0.0407 RRM2 NM_001034 </dd></dl>

<dl><dt>CMYC </dt><dd>0.84 3.34 1 0.0677 MYC NM_002467 </dd></dl>

<dl><dt>TCF-1 </dt><dd>0.84 3.96 1 0.0466 TCF1 NM_000545 </dd></dl>

<dl><dt>c-myb (official MYB) </dt><dd>0.84 3.72 1 0.0538 MY B NM_005375 </dd></dl>

<dl><dt>NOTCH1 </dt><dd>0.85 3.39 1 0.0658 NOTCH1 NM_017617 </dd></dl>

<dl><dt>MCM2 </dt><dd>0.85 3.30 1 0.0693 MCM2 NM_004526 </dd></dl>

<dl><dt>ING5 </dt><dd>0.85 2.84 1 0.0922 ING5 NM_032329 </dd></dl>

<dl><dt>AREG </dt><dd>0.88 3.72 1 0.0538 AREG NM_001657 </dd></dl>

<dl><dt>HLA-DRB1 </dt><dd>0.90 3.84 1 0.0500 HLA-DRB1 NM_002124 </dd></dl>

Table 6.2 shows associations between gene expression and clinical outcome based on a nonlinear proportional hazard analysis, using a natural spline curve of 2 degrees of freedom. All genes that demonstrated a deviation from a strictly linear relationship (p &lt;0.05) with ILR in combined stage II (Duke B) and state III (Duke C) patients are listed. The relationship between gene expression and ILR was not constant over the entire observed range of expression values ​​in the study, for example increases in gene expression may have been related to increases in the duration of ILR in a part of the observed range. and with decreases in the duration of ILR in a different part of the interval.

<dl><dt>Gen </dt><dd>P value Official symbol Registry number </dd></dl>

<dl><dt>PTHLH </dt><dd>&lt;0.0001 PTHLH NM_002820 </dd></dl>

<dl><dt>TGFBR1 </dt><dd>0.0011 TGFBR1 NM_004612 </dd></dl>

<dl><dt>CDCA7 v2 </dt><dd>0.0020 CDCA7 NM_145810 </dd></dl>

<dl><dt>S100A4 </dt><dd>0.0034 S100A4 NM_002961 </dd></dl>

<dl><dt>CREBBP </dt><dd>0.0040 CREBBP NM_004380 </dd></dl>

<dl><dt>Upa </dt><dd>0.0040 PLAU NM_002658 </dd></dl>

<dl><dt>KLF5 </dt><dd>0.0048 KLF5 NM_001730 </dd></dl>

<dl><dt>CYP2C8 </dt><dd>0.0070 CYP2C8 NM_000770 </dd></dl>

<dl><dt>HES6 </dt><dd>0.0090 HES6 NM_018645 </dd></dl>

<dl><dt>Cad17 </dt><dd>0.0093 CDH17 NM_004063 </dd></dl>

<dl><dt>CEGP1 </dt><dd>0.0100 SCUBE2 NM_020974 </dd></dl>

<dl><dt>GHI k-ras mut3 </dt><dd>0.0100 GHI_k-ras_mut3 </dd></dl>

<dl><dt>AKT1 </dt><dd>0.0104 AKT1 NM_005163 </dd></dl>

<dl><dt>LAMB3 </dt><dd>0.0111 LAMB3 NM_000228 </dd></dl>

<dl><dt>CAPG </dt><dd>0.0120 CAPG NM_001747 </dd></dl>

<dl><dt>FUT6 </dt><dd>0.0130 FUT6 NM_000150 </dd></dl>

<dl><dt>A-Catenin </dt><dd>0.0141 CTNNA1 NM_001903 </dd></dl>

<dl><dt>CAPN1 </dt><dd>0.0167 CAPN1 NM_005186 </dd></dl>

<dl><dt>HSPE1 </dt><dd>0.0180 HSPE1 NM_002157 </dd></dl>

<dl><dt>MADH4 </dt><dd>0.0180 SMAD4 NM_005359 </dd></dl>

<dl><dt>STMY3 </dt><dd>0.0190 MMP11 NM_005940 </dd></dl>

<dl><dt>TRAG3 </dt><dd>0.0200 CSAG2 NM_004909 </dd></dl>

<dl><dt>GBP1 </dt><dd>0.0200 GBP1 NM_002053 </dd></dl>

<dl><dt>EFNA1 </dt><dd>0.0210 EFNA1 NM_004428 </dd></dl>

<dl><dt>SEMA3B </dt><dd>0.0210 SEMA3B NM_004636 </dd></dl>

<dl><dt>CLTC </dt><dd>0.0216 CLTC NM_004859 </dd></dl>

<dl><dt>BRK </dt><dd>0.0240 PTK6 NM_005975 </dd></dl>

<dl><dt>Fas </dt><dd>0.0240 FAS NM_000043 </dd></dl>

<dl><dt>CCNE2 variant 1 </dt><dd>0.0243 CCNE2 NM_057749 </dd></dl>

<dl><dt>TMEPAI </dt><dd>0.0246 TMEPAI NM_020182 </dd></dl>

<dl><dt>PTPRJ </dt><dd>0.0260 PTPRJ NM_002843 </dd></dl>

<dl><dt>SKP2 </dt><dd>0.0261 SKP2 NM_005983 </dd></dl>

<dl><dt>AGXT </dt><dd>0.0273 AGXT NM_000030 </dd></dl>

<dl><dt>MAP2 </dt><dd>0.0320 MAP2 NM_031846 </dd></dl>

<dl><dt>NFP2 </dt><dd>0.0330 NFP2 NM_053024 </dd></dl>

<dl><dt>ATP5E </dt><dd>0.0350 ATP5E NM_006886 </dd></dl>

<dl><dt>NRP1 </dt><dd>0.0352 NRP1 NM_003873 </dd></dl>

<dl><dt>MYH11 </dt><dd>0.0360 MYH11 NM_002474 </dd></dl>

<dl><dt>cIAP2 </dt><dd>0.0369 BIRC3 NM_001165 </dd></dl>

<dl><dt>INHBA </dt><dd>0.0370 INHBA NM_002192 </dd></dl>

<dl><dt>EGLN1 </dt><dd>0.0371 EGLN1 NM_022051 </dd></dl>

<dl><dt>GRIK1 </dt><dd>0.0380 GRIK1 NM_000830 </dd></dl>

<dl><dt>KDR </dt><dd>0.0380 KDR NM_002253 </dd></dl>

<dl><dt>KLK6 </dt><dd>0.0388 KLK6 NM_002774 </dd></dl>

<dl><dt>APOC1 </dt><dd>0.0390 APOC1 NM_001645 </dd></dl>

<dl><dt>EP300 </dt><dd>0.0390 EP300 NM_001429 </dd></dl>

<dl><dt>DET1 </dt><dd>0.0390 DET1 NM_017996 </dd></dl>

<dl><dt>ITGB4 </dt><dd>0.0394 ITGB4 NM_000213 </dd></dl>

<dl><dt>CD3z </dt><dd>0.0400 CD3Z NM_000734 </dd></dl>

<dl><dt>MAX </dt><dd>0.0400 MAX NM_002382 </dd></dl>

<dl><dt>PAI1 </dt><dd>0.0407 SERPINE1 NM_000602 </dd></dl>

<dl><dt>MADH7 </dt><dd>0.0430 SMAD7 NM_005904 </dd></dl>

<dl><dt>SIR2 </dt><dd>0.0440 SIRT1 NM_012238 </dd></dl>

<dl><dt>NEDD8 </dt><dd>0.0440 NEDD8 NM_006156 </dd></dl>

<dl><dt>EPHB2 </dt><dd>0.0445 EPHB2 NM_004442 </dd></dl>

<dl><dt>BTF3 </dt><dd>0.0460 BTF3 NM_001207 </dd></dl>

<dl><dt>CD34 </dt><dd>0.0470 CD34 NM_001773 </dd></dl>

<dl><dt>VEGF_altsplice2 </dt><dd>0.0480 AF214570 </dd></dl>

<dl><dt>Wnt-5b </dt><dd>0.0480 WNT5B NM_032642 </dd></dl>

<dl><dt>RXRA </dt><dd>0.0482 RXRA NM_002957 </dd></dl>

<dl><dt>tusc4 </dt><dd>0.0486 TUSC4 NM_006545 </dd></dl>

Table 7.2 shows all genes that have an interaction (p &lt;0.1) with the tumor stage. Data were modeled using a proportional hazard model of ILR with gene expression, tumor stage and their interaction as predictive factors. Patients who had 0 positive nodes but &lt;12 nodes examined were excluded from these analyzes.

<dl><dt>Gen </dt><dd>Stage II RR Stage III RR P value for interaction Official symbol Registry number </dd></dl>

<dl><dt>SOS1 </dt><dd>3.35 0.81 0.0009 SOS1 NM_005633 </dd></dl>

<dl><dt>ALCAM </dt><dd>2.36 0.94 0.0020 ALCAM NM_001627 </dd></dl>

<dl><dt>pS2 </dt><dd>1.58 1.04 0.0040 TFF1 NM_003225 </dd></dl>

<dl><dt>TGFB2 </dt><dd>1.83 0.95 0.0064 TGFB2 NM_003238 </dd></dl>

<dl><dt>TFF3 </dt><dd>1.57 0.90 0.0066 TFF3 NM_003226 </dd></dl>

<dl><dt>KLF6 </dt><dd>0.35 1.34 0.0092 KLF6 NM_001300 </dd></dl>

<dl><dt>SNRPF </dt><dd>0.50 1.16 0.0106 SNRPF NM_003095 </dd></dl>

<dl><dt>CENPA </dt><dd>2.41 0.94 0.0106 CENPA NM_001809 </dd></dl>

<dl><dt>HES6 </dt><dd>1.69 0.86 0.0119 HES6 NM_018645 </dd></dl>

<dl><dt>CLDN1 </dt><dd>0.51 0.95 0.0124 CLDN1 NM_021101 </dd></dl>

<dl><dt>FGF2 </dt><dd>0.19 0.97 0.0125 FGF2 NM_002008 </dd></dl>

<dl><dt>LEF </dt><dd>1.94 0.94 0.0141 LEF1 NM_016269 </dd></dl>

<dl><dt>MADH2 </dt><dd>2.70 0.74 0.0145 SMAD2 NM_005901 </dd></dl>

<dl><dt>TP53BP1 </dt><dd>2.31 0.91 0.0153 TP53BP1 NM_005657 </dd></dl>

<dl><dt>CCR7 </dt><dd>1.89 0.98 0.0182 CCR7 NM_001838 </dd></dl>

<dl><dt>MRP3 </dt><dd>2.26 1.08 0.0204 ABCC3 NM_003786 </dd></dl>

<dl><dt>UPP1 </dt><dd>0.16 1.02 0.0208 UPP1 NM_003364 </dd></dl>

<dl><dt>PTEN </dt><dd>3.46 1.00 0.0216 PTEN NM_000314 </dd></dl>

<dl><dt>ST14 </dt><dd>1.64 0.66 0.0223 ST14 NM_021978 </dd></dl>

<dl><dt>FYN </dt><dd>2.28 1.10 0.0241 FYN NM_002037 </dd></dl>

<dl><dt>CD24 </dt><dd>1.33 0.84 0.0260 CD24 NM_013230 </dd></dl>

<dl><dt>LMYC </dt><dd>1.80 0.82 0.0275 RLF NM_012421 </dd></dl>

<dl><dt>CDC42BPA </dt><dd>2.82 1.12 0.0315 CDC42BPA NM_003607 </dd></dl>

<dl><dt>CAV1 </dt><dd>2.11 0.95 0.0364 CAV1 NM_001753 </dd></dl>

<dl><dt>CHFR </dt><dd>1.81 0.99 0.0382 CHFR NM_018223 </dd></dl>

<dl><dt>MGAT5 </dt><dd>1.59 0.72 0.0383 MGAT5 NM_002410 </dd></dl>

<dl><dt>FPGS </dt><dd>1.93 0.71 0.0402 FPGS NM_004957 </dd></dl>

<dl><dt>EMR3 </dt><dd>2.63 0.57 0.0488 EMR3 NM_032571 </dd></dl>

<dl><dt>SIR2 </dt><dd>2.17 1.07 0.0538 SIRT1 NM_012238 </dd></dl>

<dl><dt>PTK2B </dt><dd>1.44 0.93 0.0542 PTK2B NM_004103 </dd></dl>

<dl><dt>Axina 2 </dt><dd>1.38 0.90 0.0549 AXIN2 NM_004655 </dd></dl>

<dl><dt>TRAG3 </dt><dd>0.46 1.12 0.0570 CSAG2 NM_004909 </dd></dl>

<dl><dt>MMP7 </dt><dd>0.78 1.28 0.0608 MMP7 NM_002423 </dd></dl>

<dl><dt>NFP2 </dt><dd>1.33 0.84 0.0610 NFP2 NM_053024 </dd></dl>

<dl><dt>PTPRJ </dt><dd>2.05 1.00 0.0632 PTPRJ NM_002843 </dd></dl>

<dl><dt>CXCR4 </dt><dd>1.96 1.08 0.0644 CXCR4 NM_003467 </dd></dl>

<dl><dt>CCNA2 </dt><dd>1.55 0.79 0.0661 CCNA2 NM_001237 </dd></dl>

<dl><dt>MMP12 </dt><dd>0.74 1.11 0.0685 MMP12 NM_002426 </dd></dl>

<dl><dt>KRT8 </dt><dd>0.64 1.27 0.0694 KRT8 NM_002273 </dd></dl>

<dl><dt>ABCC5 </dt><dd>2.06 1.14 0.0704 ABCC5 NM_005688 </dd></dl>

<dl><dt>PRDX6 </dt><dd>2.09 0.74 0.0711 PRDX6 NM_004905 </dd></dl>

<dl><dt>WIF </dt><dd>1.54 0.77 0.0738 WIF1 NM_007191 </dd></dl>

<dl><dt>cdc25A </dt><dd>2.48 0.94 0.0769 CDC25A NM_001789 </dd></dl>

<dl><dt>KLF5 </dt><dd>1.87 1.03 0.0772 KLF5 NM_001730 </dd></dl>

<dl><dt>LRP5 </dt><dd>1.92 0.98 0.0783 LRP5 NM_002335 </dd></dl>

<dl><dt>PTPD1 </dt><dd>0.54 1.00 0.0789 PTPN21 NM_007039 </dd></dl>

<dl><dt>RALBP1 </dt><dd>2.20 0.91 0.0791 RALBP1 NM_006788 </dd></dl>

<dl><dt>TP53BP2 </dt><dd>1.82 1.05 0.0819 TP53BP2 NM_005426 </dd></dl>

<dl><dt>STAT5B </dt><dd>1.57 0.86 0.0822 STAT5B NM_012448 </dd></dl>

<dl><dt>PPARG </dt><dd>1.32 0.79 0.0844 PPARG NM_005037 </dd></dl>

<dl><dt>HB-EGF </dt><dd>0.50 1.38 0.0845 HBEGF NM_001945 </dd></dl>

<dl><dt>WEIRD </dt><dd>1.77 0.96 0.0848 WEIRD NM_000964 </dd></dl>

<dl><dt>GCNT1 </dt><dd>1.86 1.07 0.0883 GCNT1 NM_001490 </dd></dl>

<dl><dt>Ki-67 </dt><dd>1.53 0.86 0.0885 MKI67 NM_002417 </dd></dl>

<dl><dt>EFNB2 </dt><dd>1.76 1.05 0.0895 EFNB2 NM_004093 </dd></dl>

<dl><dt>LGMN </dt><dd>0.59 1.37 0.0900 LGMN NM_001008530 </dd></dl>

<dl><dt>DKK1 </dt><dd>0.68 1.51 0.0922 DKK1 NK_012242 </dd></dl>

<dl><dt>MADH4 </dt><dd>2.04 0.98 0.0964 SMAD4 NM_005359 </dd></dl>

<dl><dt>BIK </dt><dd>1.53 0.94 0.0966 BIK NM_001197 </dd></dl>

<dl><dt>CD44v3 </dt><dd>1.58 0.97 0.0996 AJ251595v3 </dd></dl>

Table A

<dl><dt>Gen </dt><dd>Registry Reagent Sequence Sequence ID Number </dd></dl>

<dl><dt>A-Catenin </dt><dd>NM_001903.1 Direct primer CGTTCCGATCCTCTATACTGCAT SEQ ID NO: 1 </dd></dl>

<dl><dt>Probe </dt><dd>ATGCCTACAGCACCCTGATGTCGCA SEQ ID NO: 2 </dd></dl>

<dl><dt>Reverse primer </dt><dd>AGGTCCCTGTTGGCCTTATAGG SEQ ID NO: 3 </dd></dl>

<dl><dt>ABCB1 </dt><dd>NM_000927.2 Direct primer AAACACCACTGGAGCATTGA SEQ ID NO: 4 </dd></dl>

<dl><dt>Probe </dt><dd>CTCGCCAATGATGCTGCTCAAGTT SEQ ID NO: 5 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CAAGCCTGGAACCTATAGCC SEQ ID NO: 6 </dd></dl>

<dl><dt>ABCC5 </dt><dd>NM_005688.1 Direct primer TGCAGACTGTACCATGCTGA SEQ ID NO: 7 </dd></dl>

<dl><dt>Probe </dt><dd>CTGCACACGGTTCTAGGCTCCG SEQ ID NO: 8 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GGCCAGCACCATAATCCTAT SEQ ID NO: 9 </dd></dl>

<dl><dt>ABCC6 </dt><dd>NM_001171.2 Direct primer GGATGAACCTCGACCTGC SEQ ID NO: 10 </dd></dl>

<dl><dt>Probe </dt><dd>CCAGATAGCCTCGTCCGAGTGCTC SEQ ID NO: 11 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GAGCTGCACCGTCTCCAG SEQ ID NO: 12 </dd></dl>

<dl><dt>ACP1 </dt><dd>NM_004300.2 Direct primer GCTACCAAGTCCGTGCTGT SEQ ID NO: 13 </dd></dl>

<dl><dt>Probe </dt><dd>TGATCGACAAATGTTACCCAGACACACA SEQ ID NO: 14 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GAAAACTGCTTCTGCAATGG SEQ ID NO: 15 </dd></dl>

<dl><dt>ADAM10 </dt><dd>NM_001110.1 Direct primer CCCATCAACTTGTGCCAGTA SEQ ID NO: 16 </dd></dl>

<dl><dt>Probe </dt><dd>TGCCTACTCCACTGCACAGACCCT SEQ ID NO: 17 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GGTGATGGTTCGACCACTG SEQ ID NO: 18 </dd></dl>

<dl><dt>ADAM17 </dt><dd>NM_003183.3 Direct primer GAAGTGCCAGGAGGCGATTA SEQ ID NO: 19 </dd></dl>

<dl><dt>Probe </dt><dd>TGCTACTTGCAAAGGCGTGTCCTACTGC SEQ ID NO: 20 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CGGGCACTCACTGCTATTACC SEQ ID NO: 21 </dd></dl>

<dl><dt>ADAMTS12 </dt><dd>NM_030955.2 Direct primer GGAGAAGGGTGGAGTGCAG SEQ ID NO: 22 </dd></dl>

<dl><dt>Probe </dt><dd>CGCACAGTCAGAATCCATCTGGGT SEQ ID NO: 23 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CAGGGTCAGGTCTCTGGATG SEQ ID NO: 24 </dd></dl>

<dl><dt>ADPRT </dt><dd>NM_001618.2 Direct primer TTGACAACCTGCTGGACATC SEQ ID NO: 25 </dd></dl>

<dl><dt>Probe </dt><dd>CCCTGAGCAGACTGTAGGCCACCT SEQ ID NO: 26 </dd></dl>

<dl><dt>Reverse primer </dt><dd>ATGGGATCCTTGCTGCTATC SEQ ID NO: 27 </dd></dl>

<dl><dt>AGXT </dt><dd>NM_000030.1 Direct primer CTTTTCCCTCCAGTGGCA SEQ ID NO: 28 </dd></dl>

<dl><dt>Probe </dt><dd>CTCCTGGAAACAGTCCACTTGGGC SEQ ID NO: 29 </dd></dl>

<dl><dt>Reverse primer </dt><dd>ATTTGGAAGGCACTGGGTTT SEQ ID NO: 30 </dd></dl>

<dl><dt>AKAP12 </dt><dd>NM_005100.2 Direct primer TAGAGAGCCCCTGACAATCC SEQ ID NO: 31 </dd></dl>

<dl><dt>Probe </dt><dd>TGGCTCTAGCTCCTGATGAAGCCTC SEQ ID NO: 32 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GGTTGGTCTTGGAAAGAGGA SEQ ID NO: 33 </dd></dl>

<dl><dt>AKT1 </dt><dd>NM_005163.1 Direct primer CGCTTCTATGGCGGTGAGAT SEQ ID NO: 34 </dd></dl>

<dl><dt>Probe </dt><dd>CAGCCCTGGACTACCTGCACTCGG SEQ ID NO: 35 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TCCCGGTACACCACGTTCTT SEQ ID NO: 36 </dd></dl>

<dl><dt>AKT2 </dt><dd>NM_001626.2 Direct primer TCCTGCCACCCTTCAAACC SEQ ID NO: 37 </dd></dl>

<dl><dt>Probe </dt><dd>CAGGTCACGTCCGAGGTCGACACA SEQ ID NO: 38 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GGCGGTAAATTCATCATCGAA SEQ ID NO: 39 </dd></dl>

<dl><dt>AKT3 </dt><dd>NM_005465.1 Direct primer TTGTCTCTGCCTTGGACTATCTACA SEQ ID NO: 40 </dd></dl>

<dl><dt>Probe </dt><dd>TCACGGTACACAATCTTTCCGGA SEQ ID NO: 41 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CCAGCATTAGATTCTCCAACTTGA SEQ ID NO: 42 </dd></dl>

<dl><dt>AL137428 </dt><dd>AL137428.1 Direct primer CAAGAAGAGGCTCTACCCTGG SEQ ID NO: 43 </dd></dl>

<dl><dt>Probe </dt><dd>ACTGGGAATTTCCAAGGCCACCTT SEQ ID NO: 44 </dd></dl>

<dl><dt>Reverse primer </dt><dd>AAATGAGCTCTGCGATCCTC SEQ ID NO: 45 </dd></dl>

<dl><dt>ALCAM </dt><dd>NM_001627.1 Direct primer GAGGAATATGGAATCCAAGGG SEQ ID NO: 46 </dd></dl>

<dl><dt>Probe </dt><dd>CCAGTTCCTGCCGTCTGCTCTTCT SEQ ID NO: 47 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GTGGCGGAGATCAAGAGG SEQ ID NO: 48 </dd></dl>

<dl><dt>ALDH1A1 </dt><dd>NM_000689.1 Direct primer GAAGGAGATAAGGAGGATGTTGACA SEQ ID NO: 49 </dd></dl>

<dl><dt>Probe </dt><dd>AGTGAAGGCCGCAAGACAGGCTTTTC SEQ ID NO: 50 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CGCCACGGAGATCCAATC SEQ ID NO: 51 </dd></dl>

<dl><dt>ALDOA </dt><dd>NM_000034.2 Direct primer GCCTGTACGTGCCAGCTC SEQ ID NO: 52 </dd></dl>

<dl><dt>Probe </dt><dd>TGCCAGAGCCTCAACTGTCTCTGC SEQ ID NO: 53 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TCATCGGAGCTTGATCTCG SEQ ID NO: 54 </dd></dl>

<dl><dt>AMFR </dt><dd>NM_001144.2 Direct primer GATGGTTCAGCTCTGCAAGGA SEQ ID NO: 55 </dd></dl>

<dl><dt>Probe </dt><dd>CGATTTGAATATCTTTCCTTCTCGCCCACC SEQ ID NO: 56 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TCGACCGTGGCTGCTCAT SEQ ID NO: 57 </dd></dl>

<dl><dt>ANGPT2 </dt><dd>NM_001147.1 Direct primer CCGTGAAAGCTGCTCTGTAA SEQ ID NO: 58 </dd></dl>

<dl><dt>Probe </dt><dd>AAGCTGACACAGCCCTCCCAAGTG SEQ ID NO: 59 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TTGCAGTGGGAAGAACAGTC SEQ ID NO: 60 </dd></dl>

<dl><dt>ANTXR1 </dt><dd>NM_032208.1 Direct primer CTCCAGGTGTACCTCCAACC SEQ ID NO: 61 </dd></dl>

<dl><dt>Probe </dt><dd>AGCCTTCTCCCACAGCTGCCTACA SEQ ID NO: 62 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GAGAAGGCTGGGAGACTCTG SEQ ID NO: 63 </dd></dl>

<dl><dt>ANXA1 </dt><dd>NM_000700.1 Direct primer GCCCCTATCCTACCTTCAATCC SEQ ID NO: 64 </dd></dl>

<dl><dt>Probe </dt><dd>TCCTCGGATGTCGCTGCCT SEQ ID NO: 65 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CCTTTAACCATTATGGCCTTATGC SEQ ID NO: 66 </dd></dl>

<dl><dt>ANXA2 </dt><dd>NM_004039.1 Direct primer CAAGACACTAAGGGCGACTACCA SEQ ID NO: 67 </dd></dl>

<dl><dt>Probe </dt><dd>CCACCACACAGGTACAGCAGCGCT SEQ ID NO: 68 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CGTGTCGGGCTTCAGTCAT SEQ ID NO: 69 </dd></dl>

<dl><dt>ANXA5 </dt><dd>NM_001154.2 Direct primer GCTCAAGCCTGGAAGATGAC SEQ ID NO: 70 </dd></dl>

<dl><dt>Probe </dt><dd>AGTACCCTGAAGTGTCCCCCACCA SEQ ID NO: 71 </dd></dl>

<dl><dt>Reverse primer </dt><dd>AGAACCACCAACATCCGCT SEQ ID NO: 72 </dd></dl>

<dl><dt>AP-1 (official JUN) </dt><dd>NM_002228.2 Direct primer GACTGCAAAGATGGAAACGA SEQ ID NO: 73 </dd></dl>

<dl><dt>Probe </dt><dd>CTATGACGATGCCCTCAACGCCTC SEQ ID NO: 74 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TAGCCATAAGGTCCGCTCTC SEQ ID NO: 75 </dd></dl>

<dl><dt>APC </dt><dd>NM_000038.1 Direct primer GGACAGCAGGAATGTGTTTC SEQ ID NO: 76 </dd></dl>

<dl><dt>Probe </dt><dd>CATTGGCTCCCCGTGACCTGTA SEQ ID NO: 77 </dd></dl>

<dl><dt>Reverse primer </dt><dd>ACCCACTCGATTTGTTTCTG SEQ ID NO: 78 </dd></dl>

<dl><dt>APEX-1 </dt><dd>NM_001641.2 Direct primer GATGAAGCCTTTCGCAAGTT SEQ ID NO: 79 </dd></dl>

<dl><dt>Probe </dt><dd>CTTTCGGGAAGCCAGGCCCTT SEQ ID NO: 80 </dd></dl>

<dl><dt>Reverse primer </dt><dd>AGGTCTCCACACAGCACAAG SEQ ID NO: 81 </dd></dl>

<dl><dt>APG-1 </dt><dd>NM_014278.2 Direct primer ACCCCGGCCTGTATATCAT SEQ ID NO: 82 </dd></dl>

<dl><dt>Probe </dt><dd>CCAATGGCTCGAGTTCTTGATCCC SEQ ID NO: 83 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CTATCTGGCTCTTTGCTGCAT SEQ ID NO: 84 </dd></dl>

<dl><dt>APN (official ANPEP) </dt><dd>NM_001150.1 Direct primer CCACCTTGGACCAAAGTAAAGC SEQ ID NO: 85 </dd></dl>

<dl><dt>Probe </dt><dd>CTCCCCAACACGCTGAAACCCG SEQ ID NO: 86 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TCTCAGCGTCACCTGGTAGGA SEQ ID NO: 87 </dd></dl>

<dl><dt>APOC1 </dt><dd>NM_001645.3 Direct primer GGAAACACACTGGAGGACAAG SEQ ID NO: 88 </dd></dl>

<dl><dt>Probe </dt><dd>TCATCAGCCGCATCAAACAGAGTG SEQ ID NO: 89 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CGCATCTTGGCAGAAAGTT SEQ ID NO: 90 </dd></dl>

<dl><dt>AREG </dt><dd>NM_001657.1 Direct primer TGTGAGTGAAATGCCTTCTAGTAGTGA SEQ ID NO: 91 </dd></dl>

<dl><dt>Probe </dt><dd>CCGTCCTCGGGAGCCGACTATGA SEQ ID NO: 92 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TTGTGGTTCGTTATCATACTCTTCTGA SEQ ID NO: 93 </dd></dl>

<dl><dt>ARG </dt><dd>NM_005158.2 Direct primer CGCAGTGCAGCTGAGTATCTG SEQ ID NO: 94 </dd></dl>

<dl><dt>Probe </dt><dd>TCGCACCAGGAAGCTGCCATTGA SEQ ID NO: 95 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TGCCCAGGGCTACTCTCACTT SEQ ID NO: 96 </dd></dl>

<dl><dt>ARHF </dt><dd>NM_019034.2 Direct primer ACTGGCCCACTTAGTCCTCA SEQ ID NO: 97 </dd></dl>

<dl><dt>Probe </dt><dd>CTCCCAACCTGCTGTCCCTCAAG SEQ ID NO: 98 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CTGAACTCCACAGGCTGGTA SEQ ID NO: 99 </dd></dl>

<dl><dt>ATOH1 </dt><dd>NM_005172.1 Direct primer GCAGCCACCTGCAACTTT SEQ ID NO: 100 </dd></dl>

<dl><dt>Probe </dt><dd>CAGGCGAGAGAGCATCCCGTCTAC SEQ ID NO: 101 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TCCAGGAGGGACAGCTCA SEQ ID NO: 102 </dd></dl>

<dl><dt>ATP5A1 </dt><dd>NM_004046.3 Direct primer GATGCTGCCACTCAACAACT SEQ ID NO: 103 </dd></dl>

<dl><dt>Probe </dt><dd>AGTTAGACGCACGCCACGACTCAA SEQ ID NO: 104 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TGTCCTTGCTTCAGCAACTC SEQ ID NO: 105 </dd></dl>

<dl><dt>ATP5E </dt><dd>NM_006886.2 Direct primer CCGCTTTCGCTACAGCAT SEQ ID NO: 106 </dd></dl>

<dl><dt>Probe </dt><dd>TCCAGCCTGTCTCCAGTAGGCCAC SEQ ID NO: 107 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TGGGAGTATCGGATGTAGCTG SEQ ID NO: 108 </dd></dl>

<dl><dt>AURKB </dt><dd>NM_004217.1 Direct primer AGCTGCAGAAGAGCTGCACAT SEQ ID NO: 109 </dd></dl>

<dl><dt>Probe </dt><dd>TGACGAGCAGCGAACAGCCACG SEQ ID NO: 110 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GCATCTGCCAACTCCTCCAT SEQ ID NO: 111 </dd></dl>

<dl><dt>Axina 2 </dt><dd>NM_004655.2 Direct primer GGCTATGTCTTTGCACCAGC SEQ ID NO: 112 </dd></dl>

<dl><dt>Probe </dt><dd>ACCAGCGCCAACGACAGTGAGATA SEQ ID NO: 113 </dd></dl>

<dl><dt>Reverse primer </dt><dd>ATCCGTCAGCGCATCACT SEQ ID NO: 114 </dd></dl>

<dl><dt>axina 1 </dt><dd>NM_003502.2 Direct primer CCGTGTGACAGCATCGTT SEQ ID NO: 115 </dd></dl>

<dl><dt>Probe </dt><dd>CGTACTACTTCTGCGGGGAACCCA SEQ ID NO: 116 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CTCACCAGGGTGCGGTAG SEQ ID NO: 117 </dd></dl>

<dl><dt>B-Catenin </dt><dd>NM_001904.1 Direct primer GGCTCTTGTGCGTACTGTCCTT SEQ ID NO: 118 </dd></dl>

<dl><dt>Probe </dt><dd>AGGCTCAGTGATGTCTTCCCTGTCACCAG SEQ ID NO: 119 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TCAGATGACGAAGAGCACAGATG SEQ ID NO: 120 </dd></dl>

<dl><dt>BAD </dt><dd>NM_032989.1 Direct primer GGGTCAGGTGCCTCGAGAT SEQ ID NO: 121 </dd></dl>

<dl><dt>Probe </dt><dd>TGGGCCCAGAGCATGTTCCAGATC SEQ ID NO: 122 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CTGCTCACTCGGCTCAAACTC SEQ ID NO: 123 </dd></dl>

<dl><dt>BAG1 </dt><dd>NM_004323.2 Direct primer CGTTGTCAGCACTTGGAATACAA SEQ ID NO: 124 </dd></dl>

<dl><dt>Probe </dt><dd>CCCAATTAACATGACCCGGCAACCAT SEQ ID NO: 125 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GTTCAACCTCTTCCTGTGGACTGT SEQ ID NO: 126 </dd></dl>

<dl><dt>BAG2 </dt><dd>NM_004282.2 Direct primer CTAGGGGCAAAAAGCATGA SEQ ID NO: 127 </dd></dl>

<dl><dt>Probe </dt><dd>TTCCATGCCAGACAGGAAAAAGCA SEQ ID NO: 128 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CTAAATGCCCAAGGTGACTG SEQ ID NO: 129 </dd></dl>

<dl><dt>BAG3 </dt><dd>NM_004281.2 Direct primer GAAAGTAAGCCAGGCCCAGTT SEQ ID NO: 130 </dd></dl>

<dl><dt>Probe </dt><dd>CAGAACTCCCTCCTGGACACATCCCAA SEQ ID NO: 131 </dd></dl>

<dl><dt>Reverse primer </dt><dd>ACCTCTTTGCGGATCACTTGA SEQ ID NO: 132 </dd></dl>

<dl><dt>Bak </dt><dd>NM_001188.1 Direct primer CCATTCCCACCATTCTACCT SEQ ID NO: 133 </dd></dl>

<dl><dt>Probe </dt><dd>ACACCCCAGACGTCCTGGCCT SEQ ID NO: 134 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GGGAACATAGACCCACCAAT SEQ ID NO: 135 </dd></dl>

<dl><dt>Bax </dt><dd>NM_004324.1 Direct primer CCGCCGTGGACACAGACT SEQ ID NO: 136 </dd></dl>

<dl><dt>Probe </dt><dd>TGCCACTCGGAAAAAGACCTCTCGG SEQ ID NO: 137 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TTGCCGTCAGAAAACATGTCA SEQ ID NO: 138 </dd></dl>

<dl><dt>BBC3 </dt><dd>NM_014417.1 Direct primer CCTGGAGGGTCCTGTACAAT SEQ ID NO: 139 </dd></dl>

<dl><dt>Probe </dt><dd>CATCATGGGACTCCTGCCCTTACC SEQ ID NO: 140 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CTAATTGGGCTCCATCTCG SEQ ID NO.141 </dd></dl>

<dl><dt>BCAS1 </dt><dd>NM_003657.1 Direct primer CCCCGAGACAACGGAGATAA SEQ ID NO: 142 </dd></dl>

<dl><dt>Probe </dt><dd>CTTTCCGTTGGCATCCGCAACAG SEQ ID NO: 143 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CTCGGGTTTGGCCTCTTTC SEQ ID NO: 144 </dd></dl>

<dl><dt>Bcl2 </dt><dd>NM_000633.1 Direct primer CAGATGGACCTAGTACCCACTGAGA SEQ ID NO: 145 </dd></dl>

<dl><dt>Probe </dt><dd>TTCCACGCCGAAGGACAGCGAT SEQ ID NO: 146 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CCTATGATTTAAGGGCATTTTTCC SEQ ID NO.147 </dd></dl>

<dl><dt>BCL2L10 </dt><dd>NM_020396.2 Direct primer GCTGGGATGGCTTTTGTCA SEQ ID NO: 148 </dd></dl>

<dl><dt>Probe </dt><dd>TCTTCAGGACCCCCTTTCCACTGGC SEQ ID NO: 149 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GCCTGGACCAGCTGTTTTCTC SEQ ID NO: 150 </dd></dl>

<dl><dt>BCL2L11 </dt><dd>NM_138621.1 Direct primer AATTACCAAGCAGCCGAAGA SEQ ID NO: 151 </dd></dl>

<dl><dt>Probe </dt><dd>CCACCCACGAATGGTTATCTTACGACTG SEQ ID NO: 152 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CAGGCGGACAATGTAACGTA SEQ ID NO: 153 </dd></dl>

<dl><dt>BCL2L12 </dt><dd>NM_138639.1 Direct primer AACCCACCCCTGTCTTGG SEQ ID NO: 154 </dd></dl>

<dl><dt>Probe </dt><dd>TCCGGGTAGCTCTCAAACTCGAGG SEQ ID NO: 155 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CTCAGCTGACGGGAAAGG SEQ ID NO: 156 </dd></dl>

<dl><dt>Bclx </dt><dd>NM_001191.1 Direct primer CTTTTGTGGAACTCTATGGGAACA SEQ ID NO: 157 </dd></dl>

<dl><dt>Probe </dt><dd>TTCGGCTCTCGGCTGCTGCA SEQ ID NO: 158 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CAGCGGTTGAAGCGTTCCT SEQ ID NO: 159 </dd></dl>

<dl><dt>BCRP </dt><dd>NM_004827.1 Direct primer TGTACTGGCGAAGAATATTTGGTAAA SEQ ID NO: 160 </dd></dl>

<dl><dt>Probe </dt><dd>CAGGGCATCGATCTCTCACCCTGG SEQ ID NO: 161 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GCCACGTGATTCTTCCACAA SEQ ID NO: 162 </dd></dl>

<dl><dt>BFGF </dt><dd>NM_007083.1 Direct primer CCAGGAAGAATGCTTAAGATGTGA SEQ ID NO: 163 </dd></dl>

<dl><dt>Probe </dt><dd>TTCGCCAGGTCATTGAGATCCATCCA SEQ ID NO: 164 </dd></dl>

<dl><dt>Reverse primer </dt><dd>TGGTGATGGGAGTTGTATTTTCAG SEQ ID NO: 165 </dd></dl>

<dl><dt>BGN </dt><dd>NM_001711.3 Direct primer GAGCTCCGCAAGGATGAC SEQ ID NO: 166 </dd></dl>

<dl><dt>Probe </dt><dd>CAAGGGTCTCCAGCACCTCTACGC SEQ ID NO: 167 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CTTGTTGTTCACCAGGACGA SEQ ID NO: 168 </dd></dl>

<dl><dt>IDB </dt><dd>NM_001196.2 Direct primer GGACTGTGAGGTCAACAACG SEQ ID NO: 169 </dd></dl>

<dl><dt>Probe </dt><dd>TGTGATGCACTCATCCCTGAGGCT SEQ ID NO: 170 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GGAAGCCAAACACCAGTAGG SEQ ID NO: 171 </dd></dl>

<dl><dt>BIK </dt><dd>NM_0011973 Direct primer ATTCCTATGGCTCTGCAATTGTC SEQ ID NO: 172 </dd></dl>

<dl><dt>Probe </dt><dd>CCGGTTAACTGTGGCCTGTGCCC SEQ ID NO: 173 </dd></dl>

<dl><dt>Reverse primer </dt><dd>GGCAGGAGTGAATGGCTCTTC SEQ ID NO: 174 </dd></dl>

<dl><dt>BIN1 </dt><dd>NM_004305.1 Direct primer CCTGCAAAAGGGAACAAGAG SEQ ID NO: 175 </dd></dl>

<dl><dt>Probe </dt><dd>CTTCGCCTCCAGATGGCTCCC SEQ ID NO: 176 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CGTGGTTGACTCTGATCTCG SEQ ID NO: 177 </dd></dl>

<dl><dt>BLMH </dt><dd>NM_000386.2 Direct primer GGTTGCTGCCTCCATCAAAG SEQ ID NO: 178 </dd></dl>

<dl><dt>Probe </dt><dd>ACATCACAGCCAAACCACACAGCCTCT SEQ ID NO: 179 </dd></dl>

<dl><dt>Reverse primer </dt><dd>CCAGCTTGCTATTGAAGTGTTTTC SEQ ID NO: 180 </dd></dl>

<dl><dt>BMP2 </dt><dd>NM_001200.1 Direct primer ATGTGGACGCTCTTTCAATG SEQ ID NO: 181 </dd></dl>

<dl><dt>Probe </dt><dd>ACCGCAGTCCGTCTAAGAAGCACG SEQ ID NO: 182 </dd></dl>

<dl><dt>Reverse primer </dt><dd>ACCATGGTCGACCTTTAGGA SEQ ID NO: 183 </dd></dl>