US20160068916A1

US20160068916A1 - Test kits

Info

Publication number: US20160068916A1
Application number: US14/860,024
Authority: US
Inventors: Hjalmar Nekarda; Jan Friederichs; Bernhard Holzmann; Robert Rosenberg; Anthony Edmund Reeve; Michael Alan Black; John Lindsay McCall; Yu-Hsin Lin; Robert Craig Pollock
Original assignee: Pacific Edge Ltd
Current assignee: Pacific Edge Ltd
Priority date: 2005-12-23
Filing date: 2015-09-21
Publication date: 2016-03-10
Also published as: EP2371972A1; ES2536233T3; CA3015335A1; JP6058780B2; NZ544432A; EP1977237A1; US20200140955A1; EP2392678A3; CA2640352A1; EP2371972B1; AU2006328023A1; WO2007073220A9; CA2640352C; JP6218141B2; EP2392678B1; KR101579934B1; NZ597363A; EP1977237B1; JP5632581B2; NZ586616A

Abstract

This invention relates to prognostic signatures, and compositions and methods for determining the prognosis of cancer in a patient, particularly for colorectal cancer. Specifically, this invention relates to the use of genetic markers for the prediction of the prognosis of cancer, such as colorectal cancer, based on signatures of genetic markers. In various aspects, the invention relates to a method of predicting the likelihood of long-term survival of a cancer patient, a method of determining a treatment regime for a cancer patient, a method of preparing a treatment modality for a cancer patient, among other methods as well as kits and devices for carrying out these methods.

Description

RELATED APPLICATIONS

This application is a Divisional application filed under 35 U.S.C. §120 and 37 C.F.R. 1.53(b), which claims priority to U.S. patent application Ser. No. 13/214,782, which is a Continuation under 35 U.S.C. §1.111(a) of PCT/NZ2006/000343, International Filing Date 22 Dec. 2006, which claims the benefit of New Zealand Provisional Patent Application No. 544432 filed Dec. 23, 2005, each of which is incorporated by reference herein in its entirety.

FIELD OF THE INVENTION

This invention relates to test kits, methods and compositions for determining the prognosis of cancer, particularly colorectal cancer, in a patient. Specifically, this invention relates to the use of genetic markers for determining the prognosis of cancer, such as colorectal cancer, based on prognostic signatures.

BACKGROUND OF THE INVENTION

Colorectal cancer (CRC) is one of the most common cancers in the developed world, and its incidence is continuing to increase. Although the progression of colorectal cancer from benign polyp to adenoma to carcinoma is well studied (1), the molecular events influencing the transition and establishment of metastasis are less well understood. The prognosis and treatment of CRC currently depends on the clinico-pathological stage of disease at the time of diagnosis, and primary surgical treatment. Unfortunately disease stage alone does not allow accurate prediction of outcome for individual patients. If patient outcomes could be predicted more accurately treatments could be tailored to avoid under-treating patients destined to relapse, or over-treating patients who would be helped by surgery alone.
Many attempts have been made to identify markers that predict clinical outcome in CRC. Until recently most studies focused on single proteins or gene mutations with limited success in terms of prognostic information (2). Microarray technology enables the identification of sets of genes, called classifiers or signatures that correlate with cancer outcome. This approach has been applied to a variety of cancers, including CRC (3-5), but methodological problems and a lack of independent validation has cast doubt over the findings (6,7). Furthermore, doubts about the ability of classifiers/signatures to predict outcome have arisen due to poor concordance of identified by different researchers using different array platforms and methodologies (8).
There is a need for further tools to predict the prognosis of colorectal cancer. This invention provides further methods, compositions, kits, and devices based on prognostic cancer markers, specifically colorectal cancer prognostic markers, to aid in the prognosis and treatment of cancer.

SUMMARY OF THE INVENTION

In certain embodiments there is provided a set of markers genes identified to be differentially expressed in recurrent and non-recurrent colorectal tumours. This set of genes and test kits can be used to generate prognostics signatures, comprising two or more markers, capable of predicting the progression of colorectal tumour in a patient.
The individual markers can differentially expressed depending on whether the tumour is recurrent or not. The accuracy of prediction can be enhanced by combining the markers together into a prognostic signature for, providing for much more effective individual tests than single-gene assays. Also provided for is the application of techniques, such as statistics, machine learning, artificial intelligence, and data mining to the prognostics signatures to generate prediction models. In another embodiment, expression levels of the markers of a particular prognostic signature in the tumour of a patient can then be applied to the prediction model to determine the prognosis.
In certain embodiments, the expression level of the markers can be established using microarray methods, quantitative polymerase chain reaction (qPCR), or immunoassays.

BRIEF DESCRIPTION OF THE FIGURES

This invention is described with reference to specific embodiments thereof and with reference to the figures, in which:

FIG. 1 depicts a flow chart showing the methodology for producing the prognostic signatures from 149 New Zealand (NZ) and 55 German (DE) colorectal cancer (CRC) samples. New Zealand RNA samples were hybridized to oligonucleotide spotted arrays, with a 22-gene signature produced via leave one out cross validation (LOOCV), and then independently validated by LOOCV using the 55 sample DE data set. German RNA samples were hybridized to Affymetrix arrays, with a 19-gene signature produced via LOOCV, and then independently validated by LOOCV using the NZ data set.

FIG. 2 depicts a Kaplan-Meier analysis of disease-free survival time with patients predicted as high versus low risk of tumour recurrence: FIG. 2 a, using NZ 22-gene signature on 149 tumours from NZ patients; FIG. 2 b, using DE 19-gene signature on 55 tumours from DE patients; FIG. 2 c, NZ prognostic signature validated on 55 tumours from DE patients; FIG. 2 d, DE prognostic signature validated on 149 tumours from NZ patients. P-values were calculated using the log-rank test.

FIG. 3 depicts a Kaplan-Meier analysis of disease free survival time with patients predicted as high versus low risk of tumour recurrence: FIG. 3 a, using the 22-gene NZ signature on NZ patients with Stage II and Stage III disease; FIG. 3 b, using the 19-gene DE signature on NZ patients with Stage II and Stage III disease.

FIG. 4 shows the predictive value of signatures of varying lengths for prognosis of colorectal cancer. These signatures were derived from 10 replicate runs of 11-fold cross validation. Each replicate 11-fold validation run is indicated by the various dashed lines; the mean across replicates by the bold line. In each fold of the cross-validation, genes were removed if the fold-change across classes was <1.1 (for the remaining samples not removed in that particular fold). The genes were then ranked using a modified t-statistic, obtaining a different set of genes for each fold, and classifiers using the top n− genes (where n=2 to 200) were constructed for each fold. The genes therefore may differ for each fold of each replicate 11-fold cross validation. FIG. 4 (A): Sensitivity (proportion of recurrent tumours correctly classified), with respect to number of genes/signature. FIG. 4 (B): Specificity (proportion of non-recurrent tumours correctly classified), with respect to number of genes/signature. FIG. 4 (C): Classification rate (proportion of tumours correctly classified), with respect to number of genes/signature. The nomenclature applied by the statistician is as follows: I refers to Stage I or Stage II colorectal cancer (with no progression), and IV refers to eventual progression to Stage IV metastases.

FIG. 5 shows the decreased predictive value of signatures for the prognosis of colorectal cancer, in a repeat of the experiment of FIG. 4, except with the two genes, FAS and ME2, removed from the data set. FIG. 5 (A): Sensitivity (proportion of recurrent tumours correctly classified), with respect to number of genes/signature. FIG. 5 (B): Specificity (proportion of non-recurrent tumours correctly classified), with respect to number of genes/signature. FIG. 5 (C): Classification rate (proportion of tumours correctly classified), with respect to number of genes/signature.

FIG. 6 shows a pairs chart of “top counts” (number of times each gene appeared in the “top-n” gene lists, i.e., top 10, top 20, top 100, and top 325 as described in Example 17) using three different normalization methods produced using the R statistical computing package(10,39), in accordance with Example 17, below. The “pairs” chart is described in by Becker et al, in their treatise on the S Language (upon which R is based; see reference 39). To compare methods, use row and column as defined on the diagonal to obtain the scatter plot between those two methods, analogous to reading distances off a distance chart on a map

FIG. 7 shows the pairs chart (39) of top counts (number of times each gene appeared in the “top-n” gene lists, i.e., top 10, top 20, top 100, and top 325 as described in Example 17) using three different filtering statistics: FIG. 7( a) two-sample Wilcoxon test (41), FIG. 7( b) t-test (modified using an ad-hoc correction factor in the denominator to abrogate the effect of low-variance genes falsely appearing as significant) and FIG. 7( c) empirical Bayes as provided by the “limma”(10,40,42) package of Bioconductor (12,40).

DETAILED DESCRIPTION

Definitions

Before describing embodiments of the invention in detail, it will be useful to provide some definitions of terms used herein.
The term “marker” refers to a molecule that is associated quantitatively or qualitatively with the presence of a biological phenomenon. Examples of “markers” include a polynucleotide, such as a gene or gene fragment, RNA or RNA fragment; or a gene product, including a polypeptide such as a peptide, oligopeptide, protein, or protein fragment; or any related metabolites, by products, or any other identifying molecules, such as antibodies or antibody fragments, whether related directly or indirectly to a mechanism underlying the phenomenon. The markers of the invention include the nucleotide sequences (e.g., GenBank sequences) as disclosed herein, in particular, the full-length sequences, any coding sequences, any fragments, or any complements thereof, and any measurable marker thereof as defined above.
The terms “CCPM” or “colorectal cancer prognostic marker” or “CCPM family member” refer to a marker with altered expression that is associated with a particular prognosis, e.g., a higher or lower likelihood of recurrence of cancer, as described herein, but can exclude molecules that are known in the prior art to be associated with prognosis of colorectal cancer. It is to be understood that the term CCPM does not require that the marker be specific only for colorectal tumours. Rather, expression of CCPM can be altered in other types of tumours, including malignant tumours.
The terms “prognostic signature,” “signature,” and the like refer to a set of two or more markers, for example CCPMs, that when analysed together as a set allow for the determination of or prediction of an event, for example the prognostic outcome of colorectal cancer. The use of a signature comprising two or more markers reduces the effect of individual variation and allows for a more robust prediction. Non-limiting examples of CCPMs are set forth in Tables 1, 2, 5, and 9, while non-limiting examples of prognostic signatures are set forth in Tables 3, 4, 8A, 8B, and 9, herein. In the context of the present invention, reference to “at least one,” “at least two,” “at least five,” etc., of the markers listed in any particular set (e.g., any signature) means any one or any and all combinations of the markers listed.
The term “prediction method” is defined to cover the broader genus of methods from the fields of statistics, machine learning, artificial intelligence, and data mining, which can be used to specify a prediction model. These are discussed further in the Detailed Description section.
The term “prediction model” refers to the specific mathematical model obtained by applying a prediction method to a collection of data. In the examples detailed herein, such data sets consist of measurements of gene activity in tissue samples taken from recurrent and non-recurrent colorectal cancer patients, for which the class (recurrent or non-recurrent) of each sample is known. Such models can be used to (1) classify a sample of unknown recurrence status as being one of recurrent or non-recurrent, or (2) make a probabilistic prediction (i.e., produce either a proportion or percentage to be interpreted as a probability) which represents the likelihood that the unknown sample is recurrent, based on the measurement of mRNA expression levels or expression products, of a specified collection of genes, in the unknown sample. The exact details of how these gene-specific measurements are combined to produce classifications and probabilistic predictions are dependent on the specific mechanisms of the prediction method used to construct the model.
“Sensitivity”, “specificity” (or “selectivity”), and “classification rate”, when applied to the describing the effectiveness of prediction models mean the following:
“Sensitivity” means the proportion of truly positive samples that are also predicted (by the model) to be positive. In a test for CRC recurrence, that would be the proportion of recurrent tumours predicted by the model to be recurrent. “Specificity” or “selectivity” means the proportion of truly negative samples that are also predicted (by the model) to be negative. In a test for CRC recurrence, this equates to the proportion of non-recurrent samples that are predicted to by non-recurrent by the model. “Classification Rate” is the proportion of all samples that are correctly classified by the prediction model (be that as positive or negative).
As used herein “antibodies” and like terms refer to immunoglobulin molecules and immunologically active portions of immunoglobulin (Ig) molecules, i.e., molecules that contain an antigen binding site that specifically binds (immunoreacts with) an antigen.
These include, but are not limited to, polyclonal, monoclonal, chimeric, single chain, Fc, Fab, Fab′, and Fab₂fragments, and a Fab expression library. Antibody molecules relate to any of the classes IgG, IgM, IgA, IgE, and IgD, which differ from one another by the nature of heavy chain present in the molecule. These include subclasses as well, such as IgG1, IgG2, and others. The light chain may be a kappa chain or a lambda chain. Reference herein to antibodies includes a reference to all classes, subclasses, and types. Also included are chimeric antibodies, for example, monoclonal antibodies or fragments thereof that are specific to more than one source, e.g., a mouse or human sequence. Further included are camelid antibodies, shark antibodies or nanobodies.
The terms “cancer” and “cancerous” refer to or describe the physiological condition in mammals that is typically characterized by abnormal or unregulated cell growth. Cancer and cancer pathology can be associated, for example, with metastasis, interference with the normal functioning of neighbouring cells, release of cytokines or other secretory products at abnormal levels, suppression or aggravation of inflammatory or immunological response, neoplasia, premalignancy, malignancy, invasion of surrounding or distant tissues or organs, such as lymph nodes, etc. Specifically included are colorectal cancers, such as, bowel (e.g., large bowel), anal, and rectal cancers.
The term “colorectal cancer” includes cancer of the colon, rectum, and/or anus, and especially, adenocarcinomas, and may also include carcinomas (e.g., squamous cloacogenic carcinomas), melanomas, lymphomas, and sarcomas. Epidermoid (nonkeratinizing squamous cell or basaloid) carcinomas are also included. The cancer may be associated with particular types of polyps or other lesions, for example, tubular adenomas, tubulovillous adenomas (e.g., villoglandular polyps), villous (e.g., papillary) adenomas (with or without adenocarcinoma), hyperplastic polyps, hamartomas, juvenile polyps, polypoid carcinomas, pseudopolyps, lipomas, or leiomyomas. The cancer may be associated with familial polyposis and related conditions such as Gardner's syndrome or Peutz-Jeghers syndrome. The cancer may be associated, for example, with chronic fistulas, irradiated anal skin, leukoplakia, lymphogranuloma venereum, Bowen's disease (intraepithelial carcinoma), condyloma acuminatum, or human papillomavirus. In other aspects, the cancer may be associated with basal cell carcinoma, extramammary Paget's disease, cloacogenic carcinoma, or malignant melanoma.
The terms “differentially expressed,” “differential expression,” and like phrases, refer to a gene marker whose expression is activated to a higher or lower level in a subject (e.g., test sample) having a condition, specifically cancer, such as colorectal cancer, relative to its expression in a control subject (e.g., reference sample). The terms also include markers whose expression is activated to a higher or lower level at different stages of the same condition; in recurrent or non-recurrent disease; or in cells with higher or lower levels of proliferation. A differentially expressed marker may be either activated or inhibited at the polynucleotide level or polypeptide level, or may be subject to alternative splicing to result in a different polypeptide product. Such differences may be evidenced by a change in mRNA levels, surface expression, secretion or other partitioning of a polypeptide, for example.
Differential expression may include a comparison of expression between two or more markers (e.g., genes or their gene products); or a comparison of the ratios of the expression between two or more markers (e.g., genes or their gene products); or a comparison of two differently processed products (e.g., transcripts or polypeptides) of the same marker, which differ between normal subjects and diseased subjects; or between various stages of the same disease; or between recurring and non-recurring disease; or between cells with higher and lower levels of proliferation; or between normal tissue and diseased tissue, specifically cancer, or colorectal cancer. Differential expression includes both quantitative, as well as qualitative, differences in the temporal or cellular expression pattern in a gene or its expression products among, for example, normal and diseased cells, or among cells which have undergone different disease events or disease stages, or cells with different levels of proliferation.
The term “expression” includes production of polynucleotides and polypeptides, in particular, the production of RNA (e.g., mRNA) from a gene or portion of a gene, and includes the production of a polypeptide encoded by an RNA or gene or portion of a gene, and the appearance of a detectable material associated with expression. For example, the formation of a complex, for example, from a polypeptide-polypeptide interaction, polypeptide-nucleotide interaction, or the like, is included within the scope of the term “expression”. Another example is the binding of a binding ligand, such as a hybridization probe or antibody, to a gene or other polynucleotide or oligonucleotide, a polypeptide or a protein fragment, and the visualization of the binding ligand. Thus, the intensity of a spot on a microarray, on a hybridization blot such as a Northern blot, or on an immunoblot such as a Western blot, or on a bead array, or by PCR analysis, is included within the term “expression” of the underlying biological molecule.
The terms “expression threshold,” and “defined expression threshold” are used interchangeably and refer to the level of a marker in question outside which the polynucleotide or polypeptide serves as a predictive marker for patient survival without cancer recurrence. The threshold will be dependent on the predictive model established are derived experimentally from clinical studies such as those described in the Examples below. Depending on the prediction model used, the expression threshold may be set to achieve maximum sensitivity, or for maximum specificity, or for minimum error (maximum classification rate). For example a higher threshold may be set to achieve minimum errors, but this may result in a lower sensitivity. Therefore, for any given predictive model, clinical studies will be used to set an expression threshold that generally achieves the highest sensitivity while having a minimal error rate. The determination of the expression threshold for any situation is well within the knowledge of those skilled in the art.
The term “long-term survival” is used herein to refer to survival for at least 5 years, more preferably for at least 8 years, most preferably for at least 10 years following surgery or other treatment.
The term “microarray” refers to an ordered or unordered arrangement of capture agents, preferably polynucleotides (e.g., probes) or polypeptides on a substrate. See, e.g., Microarray Analysis, M. Schena, John Wiley & Sons, 2002; Microarray Biochip Technology, M. Schena, ed., Eaton Publishing, 2000; Guide to Analysis of DNA Microarray Data, S. Knudsen, John Wiley & Sons, 2004; and Protein Microarray Technology, D. Kambhampati, ed., John Wiley & Sons, 2004.
The term “oligonucleotide” refers to a polynucleotide, typically a probe or primer, including, without limitation, single-stranded deoxyribonucleotides, single- or double-stranded ribonucleotides, RNA: DNA hybrids, and double-stranded DNAs. Oligonucleotides, such as single-stranded DNA probe oligonucleotides, are often synthesized by chemical methods, for example using automated oligonucleotide synthesizers that are commercially available, or by a variety of other methods, including in vitro expression systems, recombinant techniques, and expression in cells and organisms.
The term “polynucleotide,” when used in the singular or plural, generally refers to any polyribonucleotide or polydeoxribonucleotide, which may be unmodified RNA or DNA or modified RNA or DNA. This includes, without limitation, single- and double-stranded DNA, DNA including single- and double-stranded regions, single- and double-stranded RNA, and RNA including single- and double-stranded regions, hybrid molecules comprising DNA and RNA that may be single-stranded or, more typically, double-stranded or include single- and double-stranded regions. Also included are triple-stranded regions comprising RNA or DNA or both RNA and DNA. Specifically included are mRNAs, cDNAs, and genomic DNAs, and any fragments thereof. The term includes DNAs and RNAs that contain one or more modified bases, such as tritiated bases, or unusual bases, such as inosine. The polynucleotides of the invention can encompass coding or non-coding sequences, or sense or antisense sequences. It will be understood that each reference to a “polynucleotide” or like term, herein, will include the full-length sequences as well as any fragments, derivatives, or variants thereof.
“Polypeptide,” as used herein, refers to an oligopeptide, peptide, or protein sequence, or fragment thereof, and to naturally occurring, recombinant, synthetic, or semi-synthetic molecules. Where “polypeptide” is recited herein to refer to an amino acid sequence of a naturally occurring protein molecule, “polypeptide” and like terms, are not meant to limit the amino acid sequence to the complete, native amino acid sequence for the full-length molecule. It will be understood that each reference to a “polypeptide” or like term, herein, will include the full-length sequence, as well as any fragments, derivatives, or variants thereof.
The term “prognosis” refers to a prediction of medical outcome, for example, a poor or good outcome (e.g., likelihood of long-term survival); a negative prognosis, or poor outcome, includes a prediction of relapse, disease progression (e.g., tumour growth or metastasis, or drug resistance), or mortality; a positive prognosis, or good outcome, includes a prediction of disease remission, (e.g., disease-free status), amelioration (e.g., tumour regression), or stabilization.
The term “proliferation” refers to the processes leading to increased cell size or cell number, and can include one or more of: tumour or cell growth, angiogenesis, innervation, and metastasis.
The term “qPCR” or “QPCR” refers to quantative polymerase chain reaction as described, for example, in PCR Technique: Quantitative PCR, J. W. Larrick, ed., Eaton Publishing, 1997, and A-Z of Quantitative PCR, S. Bustin, ed., IUL Press, 2004.
The term “tumour” refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues.
“Stringency” of hybridization reactions is readily determinable by one of ordinary skill in the art, and generally is an empirical calculation dependent upon probe length, washing temperature, and salt concentration. In general, longer probes require higher temperatures for proper annealing, while shorter probes need lower temperatures. Hybridization generally depends on the ability of denatured DNA to reanneal when complementary strands are present in an environment below their melting temperature. The higher the degree of desired homology between the probe and hybridisable sequence, the higher the relative temperature which can be used. As a result, it follows that higher relative temperatures would tend to make the reaction conditions more stringent, while lower temperatures less so. Additional details and explanation of stringency of hybridization reactions, are found e.g., in Ausubel et al., Current Protocols in Molecular Biology, Wiley Interscience Publishers, (1995).
“Stringent 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/0.0015 M sodium citrate/0.1% sodium dodecyl sulfate at 50° C.; (2) employ a denaturing agent during hybridization, such as formamide, for example, 50% (v/v) formamide with 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×SSC (0.75 M NaCl, 0.075 M sodium citrate), 50 mM sodium phosphate (pH 6.8), 0.1% sodium pyrophosphate, 5×, Denhardt's solution, sonicated salmon sperm DNA (50 μg/ml), 0.1% SDS, and 10% dextran sulfate at 42° C., with washes at 42° C. in 0.2×SSC (sodium chloride/sodium citrate) and 50% formamide at 55° C., followed by a high-stringency wash comprising 0.1×SSC containing EDTA at 55° C.
“Moderately stringent conditions” may 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 washing solution and hybridization conditions (e.g., temperature, ionic strength, and % SDS) less stringent that those described above. An example of moderately stringent conditions is overnight incubation at 37° C. in a solution comprising: 20% formamide, 5×SSC (150 mM NaCl, 15 mM trisodium citrate), 50 mM sodium phosphate (pH 7.6), 5×Denhardt's solution, 10% dextran sulfate, and 20 mg/ml denatured sheared salmon sperm DNA, followed by washing the filters in 1×SSC at about 37-50° C. The skilled artisan will recognize how to adjust the temperature, ionic strength, etc. as necessary to accommodate factors such as probe length and the like.
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 explained fully in the literature, such as, Molecular Cloning: A Laboratory Manual, 2nd edition, Sambrook et al., 1989; Oligonucleotide Synthesis, M J Gait, ed., 1984; Animal Cell Culture, R. I. Freshney, ed., 1987; Methods in Enzymology, Academic Press, Inc.; Handbook of Experimental Immunology, 4th edition, D. M. Weir & CC. Blackwell, eds., Blackwell Science Inc., 1987; Gene Transfer Vectors for Mammalian Cells, J. M. Miller & M. P. Calos, eds., 1987; Current Protocols in Molecular Biology, F. M. Ausubel et al., eds., 1987; and PCR: The Polymerase Chain Reaction, Mullis et al., eds., 1994.

DESCRIPTION OF EMBODIMENTS OF THE INVENTION

In colorectal cancer, discordant results have been reported for prognostic markers. The present invention discloses the use of microarrays to reach a firmer conclusion, and to determine the prognostic role of specific prognostic signatures in colorectal cancer. The microarray-based studies shown herein indicate that particular prognostic signatures in colorectal cancer are associated with a prognosis. The invention can therefore be used to identify patients at high risk of recurrence of cancer, or patients with a high likelihood of recovery.
The present invention provides for markers for the determination of disease prognosis, for example, the likelihood of recurrence of tumours, including colorectal tumours. Using the methods of the invention, it has been found that numerous markers are associated with the prognosis of colorectal cancer, and can be used to predict disease outcome. Microarray analysis of samples taken from patients with various stages of colorectal tumours has led to the surprising discovery that specific patterns of marker expression are associated with prognosis of the cancer. The present invention therefore provides for a set of genes, outlined in Table 1 and Table 2, that are differentially expressed in recurrent and non-recurrent colorectal cancers. The genes outlined in Table 1 and Table 2 provide for a set of colorectal cancer prognostic makers (CCPMs).
A decrease in certain colorectal cancer prognostic markers (CCPMs), for example, markers associated with immune responses, is indicative of a particular prognosis. This can include increased likelihood of cancer recurrence after standard treatment, especially for colorectal cancer. Conversely, an increase in other CCPMs is indicative of a particular prognosis. This can include disease progression or the increased likelihood of cancer recurrence, especially for colorectal cancer. A decrease or increase in expression can be determined, for example, by comparison of a test sample, e.g., patient's tumour sample, to a reference sample, e.g., a sample associated with a known prognosis. In particular, one or more samples from patient(s) with non-recurrent cancer could be used as a reference sample.
For example, to obtain a prognosis, expression levels in a patient's sample (e.g., tumour sample) can be compared to samples from patients with a known outcome. If the patient's sample shows increased or decreased expression of one or more CCPMs that compares to samples with good outcome (no recurrence), then a positive prognosis, or recurrence is unlikely, is implicated. If the patient's sample shows expression of one or more CCPMs that is comparable to samples with poor outcome (recurrence), then a positive prognosis, or recurrence of the tumour is likely, is implicated.
As further examples, the expression levels of a prognostic signature comprising two or more CCPMS from a patient's sample (e.g., tumour sample) can be compared to samples of recurrent/non-recurrent cancer. If the patient's sample shows increased or decreased expression of CCPMs by comparison to samples of non-recurrent cancer, and/or comparable expression to samples of recurrent cancer, then a negative prognosis is implicated. If the patient's sample shows expression of CCPMs that is comparable to samples of non-recurrent cancer, and/or lower or higher expression than samples of recurrent cancer, then a positive prognosis is implicated.
As one approach, a prediction method can be applied to a panel of markers, for example the panel of CCPMs outlined in Table 1 and Table 2, in order to generate a predictive model. This involves the generation of a prognostic signature, comprising two or more CCPMs.
The disclosed CCPMs in Table 1 and Table 2 therefore provide a useful set of markers to generate prediction signatures for determining the prognosis of cancer, and establishing a treatment regime, or treatment modality, specific for that tumour. In particular, a positive prognosis can be used by a patient to decide to pursue standard or less invasive treatment options. A negative prognosis can be used by a patient to decide to terminate treatment or to pursue highly aggressive or experimental treatments. In addition, a patient can chose treatments based on their impact on the expression of prognostic markers (e.g., CCPMs).
Levels of CCPMs can be detected in tumour tissue, tissue proximal to the tumour, lymph node samples, blood samples, serum samples, urine samples, or faecal samples, using any suitable technique, and can include, but is not limited to, oligonucleotide probes, quantitative PCR, or antibodies raised against the markers. It will be appreciated that by analyzing the presence and amounts of expression of a plurality of CCPMs in the form of prediction signatures, and constructing a prognostic signature (e.g., as set forth in Tables 3, 4, 8A, 8B, and 9), the sensitivity and accuracy of prognosis will be increased. Therefore, multiple markers according to the present invention can be used to determine the prognosis of a cancer.
The invention includes the use of archived paraffin-embedded biopsy material for assay of the markers in the set, and therefore is compatible with the most widely available type of biopsy material. It is also compatible with several different methods of tumour tissue harvest, for example, via core biopsy or fine needle aspiration. In certain aspects, RNA is isolated from a fixed, wax-embedded cancer tissue specimen of the patient. Isolation may be performed by any technique known in the art, for example from core biopsy tissue or fine needle aspirate cells.
In one aspect, the invention relates to a method of predicting a prognosis, e.g., the likelihood of long-term survival of a cancer patient without the recurrence of cancer, comprising determining the expression level of one or more prognostic markers or their expression products in a sample obtained from the patient, normalized against the expression level of other RNA transcripts or their products in the sample, or of a reference set of RNA transcripts or their expression products. In specific aspects, the prognostic marker is one or more markers listed in Tables 1, 2, or 5, or is included as one or more of the prognostic signatures derived from the markers listed in Tables 1, 2, and 5, or the prognostic signatures listed in Tables 3, 4, 8A, 8B, or 9.
In further aspects, the expression levels of the prognostic markers or their expression products are determined, e.g., for the markers listed in Tables 1, 2, or 5, a prognostic signature derived from the markers listed in Tables 1, 2, and 5, e.g., for the prognostic signatures listed in Tables 3, 4, 8A, 8B, or 9. In another aspect, the method comprises the determination of the expression levels of a full set of prognosis markers or their expression products, e.g., for the markers listed in Tables 1, 2, or 5, or, a prognostic signature derived from the markers listed in Tables 1, 2, and 5, e.g., for the prognostic signatures listed in Tables 3, 4, 8A, 8B, or 9.
In an additional aspect, the invention relates to an array (e.g., microarray) comprising polynucleotides hybridizing to two or more markers, e.g., for the markers listed in Tables 1, 2, and 5, or a prognostic signature derived from the markers listed in Tables 1, 2, and 5, e.g., the prognostic signatures listed in Tables 3, 4, 8A, 8B, and 9. In particular aspects, the array comprises polynucleotides hybridizing to prognostic signature derived from the markers listed in Tables 1, 2, and 5, or e.g., for the prognostic signatures listed in Tables 3, 4, 8A, 8B, or 9. In another specific aspect, the array comprises polynucleotides hybridizing to the full set of markers, e.g., for the markers listed in Tables 1, 2, or 5, or, e.g., for the prognostic signatures listed in Tables 3, 4, 8A, 8B, or 9.
For these arrays, the polynucleotides can be cDNAs, or oligonucleotides, and the solid surface on which they are displayed can be glass, for example. The polynucleotides can hybridize to one or more of the markers as disclosed herein, for example, to the full-length sequences, any coding sequences, any fragments, or any complements thereof. In particular aspects, an increase or decrease in expression levels of one or more CCPM indicates a decreased likelihood of long-term survival, e.g., due to cancer recurrence, while a lack of an increase or decrease in expression levels of one or more CCPM indicates an increased likelihood of long-term survival without cancer recurrence.

TABLE 1

Colorectal Cancer Predictive Markers (corresponding to Affymetrix
GeneChip probes that show statistically significant differential expression, P < 0.05,
as ascertained by BRB Array Tools)

						Expression
						Fold
						Difference
					Other	(relapse/
Gene	Affymetrix Probe				Genbank	non-
Symbol	IDs	Refseq Access.	Gene Description	Unigene Access.	Access.	relapse)

ME2	210154_at,	NM_002396	malic enzyme 2,	Hs.233119	M55905,	0.74
	210153_s_at,		NAD(+)-dependent,		BC000147
	209397_at		mitochondrial
STAT1	AFFX-	NM_007315,	signal transducer	Hs.470943	NM_007315,	0.58
	HUMISGF3A/	NM_139266	and activator of		BC002704
	M97935_MA_at,		transcription 1,
	AFFX-		91 kDa
	HUMISGF3A/
	M97935_MB_at,
	AFFX-
	HUMISGF3A/
	M97935_3_at,
	200887_s_at,
	AFFX-
	HUMISGF3A/
	M97935_5_at,
	209969_s_at
CXCL10	204533_at	NM_001565	chemokine (C—X—C	Hs.413924	NM_001565	0.29
			motif) ligand 10
FAS	215719_x_at,	NM_000043,	Fas (TNF receptor	Hs.244139	X83493,	0.68
	216252_x_at,	NM_152871,	superfamily,		Z70519,
	204780_s_at,	NM_152872,	member 6)		AA164751,
	204781_s_at	NM_152873,			NM_000043
		NM_152874,
		NM_152875,
		NM_152876,
		NM_152877
SFRS2	200753_x_at,	NM_003016	splicing factor,	Hs.73965	BE866585,	0.82
	214882_s_at,		arginine/serine-rich 2		BG254869,
	200754_x_at				NM_003016
GUF1	218884_s_at	NM_021927	GUF1 GTPase	Hs.546419	NM_021927	0.71
			homolog (S. cerevisiae)
CXCL9	203915_at	NM_002416	chemokine (C—X—C	Hs.77367	NM_002416	0.33
			motif) ligand 9
TYMS	202589_at	NM_001071	thymidylate	Hs.369762	NM_001071	0.53
			synthetase
SEC10L1	218748_s_at	NM_006544	SEC10-like 1 (S. cerevisiae)	Hs.365863	NM_006544	0.76
PLK4	204887_s_at	NM_014264	polo-like kinase 4	Hs.172052	NM_014264	0.64
			(Drosophila)
MAP2K4	203265_s_at	NM_003010	mitogen-activated	Hs.514681	AA810268	0.76
			protein kinase kinase 4
EIF4E	201435_s_at,	NM_001968	eukaryotic	Hs.249718	AW268640,	0.69
	201436_at		translation initiation		AI742789
			factor 4E
TLK1	210379_s_at	NM_012290	tousled-like kinase 1	Hs.470586	AF162666	0.59
CXCL11	210163_at,	NM_005409	chemokine (C—X—C	Hs.518814	AF030514,	0.15
	211122_s_at		motif) ligand 11		AF002985
PSME2	201762_s_at	NM_002818	proteasome	Hs.434081,	NM_002818	0.68
			(prosome,	Hs.512410
			macropain) activator
			subunit 2 (PA28
			beta)
hCAP-D3	212789_at	NM_015261	non-SMC condensin	Hs.438550	AI796581	0.83
			II complex, subunit
			D3
MPP5	219321_at	NM_022474	membrane protein,	Hs.509699	NM_022474	0.74
			palmitoylated 5
			(MAGUK p55
			subfamily member
			5)
DLGAP4	202570_s_at	NM_014902,	discs, large	Hs.249600	BF346592	1.3
		NM_183006	(Drosophila)
			homolog-associated
			protein 4
WARS	200628_s_at,	NM_004184,	tryptophanyl-tRNA	Hs.497599	M61715,	0.66
	200629_at	NM_173701,	synthetase		NM_004184
		NM_213645,
		NM_213646
ARF6	203312_x_at	NM_001663	ADP-ribosylation	Hs.525330	NM_001663	0.77
			factor 6
PBK	219148_at	NM_018492	PDZ binding kinase	Hs.104741	NM_018492	0.41
GMFB	202543_s_at	NM_004124	glia maturation	Hs.151413	BC005359	0.66
			factor, beta
NDUFA9	208969_at	NM_005002	NADH	Hs.75227	AF050641	0.77
			dehydrogenase
			(ubiquinone) 1 alpha
			subcomplex, 9,
			39 kDa
CDC40	203377_s_at	NM_015891	cell division cycle	Hs.428147	NM_015891	0.8
			40 homolog (yeast)
WHSC1	209053_s_at,	NM_007331,	Wolf-Hirschhorn	Hs.113876	BE793789,	0.75
	209054_s_at,	NM_014919,	syndrome candidate 1		AF083389,
	209052_s_at	NM_133330,			BF111870
		NM_133331,
		NM_133332,
		NM_133333,
		NM_133334,
		NM_133335,
		NM_133336
C1QBP	208910_s_at,	NM_001212	complement	Hs.555866	L04636,	0.71
	214214_s_at		component 1, q		AU151801
			subcomponent
			binding protein
RBM25	212031_at	NM_021239	RNA binding motif	Hs.531106	AV757384	0.83
			protein 25
SLC25A11	209003_at,	NM_003562	solute carrier family	Hs.184877	AF070548,	0.83
	207088_s_at		25 (mitochondrial		NM_003562
			carrier, oxoglutarate
			carrier), member 11
TK1	202338_at	NM_003258	thymidine kinase 1,	Hs.515122	NM_003258	0.73
			soluble
ETNK1	222262_s_at,	NM_018638	ethanolamine kinase 1	Hs.240056	AL137750,	0.66
	219017_at				NM_018638
KLHL24	221985_at	NM_017644	kelch-like 24	Hs.407709	AW006750	1.4
			(Drosophila)
AK2	212175_s_at,	NM_001625,	adenylate kinase 2	Hs.470907	AL513611,	0.8
	205996_s_at,	NM_013411,			NM_013411,
	212174_at				W02312
HNRPD	221481_x_at,	NM_001003810,	heterogeneous	Hs.480073	D55672,	0.8
	209330_s_at,	NM_002138,	nuclear		D55674,
	200073_s_at	NM_031369,	ribonucleoprotein D		M94630
		NM_031370	(AU-rich element
			RNA binding
			protein 1, 37 kDa)
GTPBP3	213835_x_at	NM_032620,	GTP binding protein	Hs.334885	AL524262	0.87
		NM_133644	3 (mitochondrial)
PSAT1	220892_s_at	NM_021154,	phosphoserine	Hs.494261	NM_021154	0.54
		NM_058179	aminotransferase 1
AP1G1	203350_at	NM_001030007,	adaptor-related	Hs.461253	NM_001128	0.89
		NM_001128	protein complex 1,
			gamma 1 subunit
SMCHD1	212577_at		structural	Hs.8118	AA868754	0.74
			maintenance of
			chromosomes
			flexible hinge
			domain containing 1
SLC4A4	210738_s_at,	NM_003759	solute carrier family	Hs.5462	AF011390,	0.7
	203908_at,		4, sodium		NM_003759,
	211494_s_at,		bicarbonate		AF157492,
	210739_x_at		cotransporter,		AF069510
			member 4
RBMS3	206767_at	NM_001003792,	RNA binding motif,	Hs.221436	NM_014483	1.2
		NM_001003793,	single stranded
		NM_014483	interacting protein
LARP4	214155_s_at	NM_052879,	La ribonucleoprotein	Hs.26613	AI743740	0.66
		NM_199188,	domain family,
		NM_199190	member 4
FANCA	203805_s_at	NM_000135,	Fanconi anemia,	Hs.284153	AW083279	0.78
		NM_001018112	complementation
			group A
SOS1	212780_at	NM_005633	son of sevenless	Hs.278733	AA700167	0.84
			homolog 1
			(Drosophila)
IFT20	210312_s_at	NM_174887	intraflagellar	Hs.4187	BC002640	1.2
			transport 20
			homolog
			(Chlamydomonas)
NUP210	212316_at,	NM_024923	nucleoporin 210 kDa	Hs.475525	AA502912,	0.78
	220035_at,				NM_024923,
	213947_s_at				AI867102
IRF8	204057_at	NM_002163	interferon regulatory	Hs.137427	AI073984	0.75
			factor 8
SGPP1	221268_s_at	NM_030791	sphingosine-1-	Hs.24678	NM_030791	0.76
			phosphate
			phosphatase 1
MAD2L1	203362_s_at	NM_002358	MAD2 mitotic arrest	Hs.509523,	NM_002358	0.7
			deficient-like 1	Hs.533185
			(yeast)
PAICS	201013_s_at,	NM_006452	phosphoribosylaminoimidazole	Hs.518774	AA902652,	0.71
	201014_s_at		carboxylase,		NM_006452
			phosphoribosylaminoimidazole
			succinocarboxamide
			synthetase
RPS2	217466_x_at	NM_002952	ribosomal protein S2	Hs.356366,	L48784	0.83
				Hs.381079,
				Hs.498569,
				Hs.506997,
				Hs.556270
TMED5	202195_s_at	NM_016040	transmembrane	Hs.482873	NM_016040	0.86
			emp24 protein
			transport domain
			containing 5
GTSE1	204317_at,	NM_016426	G-2 and S-phase	Hs.386189,	BF305380,	0.8
	204318_s_at		expressed 1	Hs.475140	NM_016426
DCK	203302_at	NM_000788	deoxycytidine kinase	Hs.709	NM_000788	0.77
DKFZp762E1312	218726_at	NM_018410	hypothetical protein	Hs.532968	NM_018410	0.81
			DKFZp762E1312
BAZ1A	217986_s_at	NM_013448,	bromodomain	Hs.509140	NM_013448	0.8
		NM_182648	adjacent to zinc
			finger domain, 1A
HIP2	202346_at	NM_005339	huntingtin	Hs.50308	NM_005339	0.78
			interacting protein 2
HNRPA3P1	206809_s_at		heterogeneous	Hs.524276	NM_005758	0.83
			nuclear
			ribonucleoprotein
			A3 pseudogene 1
CDC42BPA	214464_at	NM_003607,	CDC42 binding	Hs.35433	NM_003607	1.4
		NM_014826	protein kinase alpha
			(DMPK-like)
P15RS	218209_s_at	NM_018170	hypothetical protein	Hs.464912	NM_018170	0.79
			FLJ10656
FLJ10534TSR1	218156_s_at	NM_018128	TSR1, 20S rRNA	Hs.388170	NM_018128	0.75
			accumulation,
			homolog (S. cerevisiae)
RRM1	201476_s_at	NM_001033	ribonucleotide	Hs.383396	AI692974	0.76
			reductase M1
			polypeptide
USP4	202682_s_at	NM_003363,	ubiquitin specific	Hs.77500	NM_003363	1.2
		NM_199443	peptidase 4 (proto-
			oncogene)
ZNF304	207753_at	NM_020657	zinc finger protein	Hs.287374	NM_020657	1.3
			304
CA2	209301_at	NM_000067	carbonic anhydrase	Hs.155097	M36532	0.25
			II
LOC92249	212957_s_at		hypothetical protein	Hs.31532	AU154785	1.1
			LOC92249
MARCH5	218582_at	NM_017824	membrane-	Hs.549165	NM_017824	0.81
			associated ring
			finger (C3HC4) 5
TRMT5	221952_x_at	NM_020810	TRM5 tRNA	Hs.380159	AB037814	0.81
			methyltransferase 5
			homolog (S. cerevisiae)
PRDX3	201619_at	NM_006793,	peroxiredoxin 3	Hs.523302	NM_006793	0.73
		NM_014098
RAP1GDS1	217457_s_at	NM_021159	RAP1, GTP-GDP	Hs.132858	X63465	0.82
			dissociation
			stimulator 1
NUMB	209073_s_at	NM_001005743,	numb homolog	Hs.509909	AF015040	0.82
		NM_001005744,	(Drosophila)
		NM_001005745,
		NM_003744
KIF2	203087_s_at	NM_004520	kinesin heavy chain	Hs.533222	NM_004520	0.72
			member 2
ACADSB	205355_at	NM_001609	acyl-Coenzyme A	Hs.81934	NM_001609	0.87
			dehydrogenase,
			short/branched chain
IBRDC3	213038_at	NM_153341	IBR domain	Hs.546478	AL031602	0.88
			containing 3
TES	202719_s_at	NM_015641,	testis derived	Hs.533391	BC001451	1.3
		NM_152829	transcript (3 LIM
			domains)
YDD19	37079_at		YDD19 protein	Hs.525826	U82319	0.92
GZMB	210164_at	NM_004131	granzyme B	Hs.1051	J03189	0.66
			(granzyme 2,
			cytotoxic T-
			lymphocyte-
			associated serine
			esterase 1)
LAP3	217933_s_at	NM_015907	leucine	Hs.479264	NM_015907	0.67
			aminopeptidase 3
C17orf25	209092_s_at	NM_016080	chromosome 17	Hs.279061	AF061730	0.72
			open reading frame
			25
ZNF345	207236_at	NM_003419	zinc finger protein	Hs.362324	NM_003419	1.1
			345
KITLG	207029_at,	NM_000899,	KIT ligand	Hs.1048	NM_000899,	0.75
	211124_s_at	NM_003994			AF119835
CAMSAP1L1	212765_at	NM_203459	calmodulin regulated	Hs.23585	AB029001	1.3
			spectrin-associated
			protein 1-like 1
YTHDC2	205835_s_at,	NM_022828	YTH domain	Hs.231942	AW975818,	0.84
	205836_s_at		containing 2		NM_022828
RABIF	204477_at	NM_002871	RAB interacting	Hs.90875	U74324	1.2
			factor
SERBP1	217725_x_at	NM_001018067,	SERPINE1 mRNA	Hs.369448,	NM_015640	0.81
		NM_001018068,	binding protein 1	Hs.519284,
		NM_001018069,		Hs.530412
		NM_015640
KPNB1	208975_s_at	NM_002265	karyopherin	Hs.532793	L38951	0.74
			(importin) beta 1
BRIP1	221703_at	NM_032043	BRCA1 interacting	Hs.532799	AF360549	0.86
			protein C-terminal
			helicase 1
IRF1	202531_at	NM_002198	interferon regulatory	Hs.436061	NM_002198	0.62
			factor 1
TIPIN	219258_at	NM_017858	TIMELESS	Hs.426696	NM_017858	0.73
			interacting protein
SPFH1	202444_s_at	NM_006459	SPFH domain	Hs.150087	NM_006459	0.76
			family, member 1
SFPQ	201586_s_at	NM_005066	splicing factor	Hs.355934	NM_005066	0.83
			proline/glutamine-
			rich (polypyrimidine
			tract binding protein
			associated)
MGAT2	211061_s_at	NM_001015883,	mannosyl (alpha-	Hs.93338	BC006390	0.79
		NM_002408	1,6-)-glycoprotein
			beta-1,2-N-
			acetylglucosaminyltransferase
MCCC2	209624_s_at	NM_022132	methylcrotonoyl-	Hs.167531	AB050049	0.6
			Coenzyme A
			carboxylase 2 (beta)
DDAH2	215537_x_at,	NM_013974	dimethylarginine	Hs.247362	AJ012008, AK026191	1.2
	214909_s_at		dimethylaminohydrolase 2
NP	201695_s_at	NM_000270	nucleoside	Hs.75514	NM_000270	0.79
			phosphorylase
CHEK1	205393_s_at,	NM_001274	CHK1 checkpoint	Hs.24529	NM_001274	0.7
	205394_at		homolog (S. pombe)
MYO1B	212365_at	NM_012223	myosin IB	Hs.439620	BF215996	0.85
ATP5A1	213738_s_at	NM_001001935,	ATP synthase, H+	Hs.298280,	AI587323	0.82
		NM_001001937,	transporting,	Hs.551998
		NM_004046	mitochondrial F1
			complex, alpha
			subunit, isoform 1,
			cardiac muscle
IL2RB	205291_at	NM_000878	interleukin 2	Hs.474787	NM_000878	0.73
			receptor, beta
RPL39	217665_at	NM_001000	ribosomal protein	Hs.558387	AA420614	1.3
			L39 (RPL39)
CD59	212463_at	NM_000611,	CD59 antigen p18-20	Hs.278573	BE379006	1.5
		NM_203329,	(antigen
		NM_203330,	identified by
		NM_203331	monoclonal
			antibodies 16.3A5,
			EJ16, EJ30, EL32
			and G344)
AMD1	201196_s_at	NM_001033059,	adenosylmethionine	Hs.159118	M21154	0.74
		NM_001634	decarboxylase 1
GGA2	210658_s_at	NM_015044,	golgi associated,	Hs.460336	BC000284	0.82
		NM_138640	gamma adaptin ear
			containing, ARF
			binding protein 2
MCM6	201930_at	NM_005915	MCM6	Hs.444118	NM_005915	0.75
			minichromosome
			maintenance
			deficient 6 (MIS5
			homolog, S. pombe)
			(S. cerevisiae)
SCC-112	213983_s_at,	NM_015200	SCC-112 protein	Hs.331431	AW991219,	0.8
	212138_at				AK021757
BCL7C	219072_at	NM_004765	B-cell	Hs.303197	NM_004765	1.2
			CLL/lymphoma 7C
HMGN2	208668_x_at	NM_005517	high-mobility group	Hs.181163	BC003689	0.9
			nucleosomal binding
			domain 2
RBBP4	210371_s_at,	NM_005610	retinoblastoma	Hs.555890	BC003092,	0.8
	217301_x_at		binding protein 4		X71810
KIAA0090	212396_s_at	NM_015047	KIAA0090	Hs.439200	AI143233	0.81
SYNPO	202796_at	NM_007286	synaptopodin	Hs.435228	NM_007286	1.2
GPR161	214104_at	NM_007369,	G protein-coupled	Hs.271809	AI703188	1.5
		NM_153832	receptor 161
TMEM113	215509_s_at	NM_025222	transmembrane	Hs.194110	AL137654	0.72
			protein 113
SMC2L1	204240_s_at	NM_006444	SMC2 structural	Hs.119023	NM_006444	0.65
			maintenance of
			chromosomes 2-like
			1 (yeast)
CCNA2	203418_at	NM_001237	cyclin A2	Hs.85137	NM_001237	0.6
VAPB	202549_at	NM_004738	VAMP (vesicle-	Hs.182625	AK025720	1.2
			associated
			membrane protein)-
			associated protein B
			and C
EXOSC9	213226_at	NM_005033	exosome component 9	Hs.91728	AI346350	0.73
TRIM25	206911_at	NM_005082	tripartite motif-	Hs.528952,	NM_005082	0.88
			containing 25	Hs.551516
SCYL2	221220_s_at	NM_017988	SCY1-like 2 (S. cerevisiae)	Hs.506481	NM_017988	0.85
RYK	214172_x_at	NM_001005861,	RYK receptor-like	Hs.245869	BG032035	1.2
		NM_002958	tyrosine kinase
MTHFD1	202309_at	NM_005956	methylenetetrahydro	Hs.435974	NM_005956	0.74
			folate
			dehydrogenase
			(NADP+ dependent)
			1,
			methenyltetrahydrofolate
			cyclohydrolase,
			formyltetrahydrofolate
			synthetase
RUNX1	211180_x_at	NM_001001890,	runt-related	Hs.149261,	D89788	1.1
		NM_001754	transcription factor 1	Hs.278446
			(acute myeloid
			leukemia 1, aml1
			oncogene)
KPNA2	201088_at,	NM_002266	karyopherin alpha 2	Hs.159557,	NM_002266,	0.77
	211762_s_at		(RAG cohort 1,	Hs.252712	BC005978
			importin alpha 1)
PSME1	200814_at	NM_006263,	proteasome	Hs.75348	NM_006263	0.76
		NM_176783	(prosome,
			macropain) activator
			subunit 1 (PA28
			alpha)
TACC3	218308_at	NM_006342	transforming, acidic	Hs.104019	NM_006342	0.78
			coiled-coil
			containing protein 3
FEN1	204768_s_at	NM_004111	flap structure-	Hs.409065	NM_004111	0.73
			specific
			endonuclease 1
GTF3C4	219198_at	NM_012204	general transcription	Hs.549088	NM_012204	0.87
			factor IIIC,
			polypeptide 4,
			90 kDa
GEMIN4	217099_s_at	NM_015721	gem (nuclear	Hs.499620	AF258545	0.76
			organelle) associated
			protein 4
CTSS	202902_s_at	NM_004079	cathepsin S	Hs.181301	NM_004079	0.74
MCM2	202107_s_at	NM_004526	MCM2	Hs.477481	NM_004526	0.71
			minichromosome
			maintenance
			deficient 2, mitotin
			(S. cerevisiae)
GPHN	220773_s_at	NM_001024218,	gephyrin	Hs.208765	NM_020806	0.67
		NM_020806
NUP50	218295_s_at	NM_007172,	nucleoporin 50 kDa	Hs.475103	NM_007172	0.78
		NM_153645,
		NM_153684
RANBP2L1	210676_x_at	NM_005054,	RAN binding	Hs.469630	U64675	0.83
		NM_032260	protein 2-like 1
NR5A2	208337_s_at	NM_003822,	nuclear receptor	Hs.33446	NM_003822	0.77
		NM_205860	subfamily 5, group
			A, member 2
PGD	201118_at	NM_002631	phosphogluconate	Hs.464071	NM_002631	0.75
			dehydrogenase
FUT4	209892_at,	NM_002033	fucosyltransferase 4	Hs.390420	AF305083,	0.78
	209893_s_at		(alpha (1,3)		M58596
			fucosyltransferase,
			myeloid-specific)
RAB6A	201048_x_at	NM_002869,	RAB6A, member	Hs.503222,	NM_002869	0.81
		NM_198896	RAS oncogene	Hs.535586
			family
CCNT2	204645_at	NM_001241,	cyclin T2	Hs.292754	NM_001241	0.87
		NM_058241
TFRC	207332_s_at	NM_003234	transferrin receptor	Hs.529618	NM_003234	0.63
			(p90, CD71)
BIRC5	202095_s_at	NM_001012270,	baculoviral IAP	Hs.514527	NM_001168	0.7
		NM_001012271,	repeat-containing 5
		NM_001168	(survivin)
PGGT1B	206288_at	NM_005023	protein	Hs.254006	NM_005023	0.8
			geranylgeranyltransferase
			type I, beta
			subunit
USP14	201672_s_at	NM_005151	ubiquitin specific	Hs.464416	NM_005151	0.81
			peptidase 14 (tRNA-
			guanine
			transglycosylase)
PURA	204020_at	NM_005859	purine-rich element	Hs.443121	BF739943	1.2
			binding protein A
LMAN1	203293_s_at,	NM_005570	lectin, mannose-	Hs.465295	NM_005570,	0.82
	203294_s_at		binding, 1		U09716
WDR45L	209076_s_at	NM_019613	WDR45-like	Hs.201390	BC000974	0.82
SGCD	213543_at	NM_000337,	sarcoglycan, delta	Hs.387207	AA570453	1.2
		NM_172244	(35 kDa dystrophin-
			associated
			glycoprotein)
LRP8	205282_at	NM_001018054,	low density	Hs.444637	NM_004631	0.78
		NM_004631,	lipoprotein receptor-
		NM_017522,	related protein 8,
		NM_033300	apolipoprotein e
			receptor
ITGA4	205885_s_at	NM_000885	integrin, alpha 4	Hs.555880	L12002	0.74
			(antigen CD49D,
			alpha 4 subunit of
			VLA-4 receptor)
BUB3	201458_s_at	NM_001007793,	BUB3 budding	Hs.418533	NM_004725	0.79
		NM_004725	uninhibited by
			benzimidazoles 3
			homolog (yeast)
KIF18A	221258_s_at	NM_031217	kinesin family	Hs.301052	NM_031217	0.83
			member 18A
FKBP9	212169_at	NM_007270	FK506 binding	Hs.103934	AL050187	1.2
			protein 9, 63 kDa
ATF6	217550_at	NM_007348	activating	Hs.492740	AA576497	1.4
			transcription factor 6
TNFRSF11A	207037_at	NM_003839	tumor necrosis	Hs.204044	NM_003839	0.68
			factor receptor
			superfamily,
			member 11a, NFKB
			activator
KIAA0841	213054_at		KIAA0841	Hs.7426	AA845355	0.9
TGFB2	209909_s_at	NM_003238	transforming growth	Hs.133379	M19154	1.1
			factor, beta 2
ITGB5	201125_s_at,	NM_002213	integrin, beta 5	Hs.13155	NM_002213,	1.2
	201124_at,				AL048423,
	214021_x_at				AI335208
RABGEF1	218310_at	NM_014504	RAB guanine	Hs.530053	NM_014504	1.2
			nucleotide exchange
			factor (GEF) 1
PBX1	205253_at,	NM_002585	pre-B-cell leukemia	Hs.493096	NM_002585,	1.2
	212148_at		transcription factor 1		AL049381
ZNF148	203318_s_at	NM_021964	zinc finger protein	Hs.380334	NM_021964	1.2
			148 (pHZ-52)
ZWINT	204026_s_at	NM_001005413,	ZW10 interactor	Hs.42650	NM_007057	0.66
		NM_001005414,
		NM_007057,
		NM_032997
ZDHHC3	213675_at	NM_016598	zinc finger, DHHC-	Hs.61430	W61005	1.3
			type containing 3
CDCA8	221520_s_at	NM_018101	cell division cycle	Hs.524571	BC001651	0.76
			associated 8
CUTL1	214743_at	NM_001913,	cut-like 1, CCAAT	Hs.438974	BE046521	1.3
		NM_181500,	displacement protein
		NM_181552	(Drosophila)
C18orf9	219311_at	NM_024899	chromosome 18	Hs.236940	NM_024899	0.73
			open reading frame 9
TXNDC	209476_at	NM_030755	thioredoxin domain	Hs.125221	AL080080	0.75
			containing
POLE2	205909_at	NM_002692	polymerase (DNA	Hs.162777	NM_002692	0.73
			directed), epsilon 2
			(p59 subunit)
SPCS3	218817_at	NM_021928	signal peptidase	Hs.42194	NM_021928	0.7
			complex subunit 3
			homolog (S. cerevisiae)
CAND1	208839_s_at	NM_018448	cullin-associated and	Hs.546407	AL136810	0.84
			neddylation-
			dissociated 1
U2AF2	218381_s_at	NM_001012478,	U2 (RNU2) small	Hs.528007	NM_007279	0.83
		NM_007279	nuclear RNA
			auxiliary factor 2
WDHD1	204728_s_at	NM_001008396,	WD repeat and	Hs.385998	NM_007086	0.73
		NM_007086	HMG-box DNA
			binding protein 1
HEM1	209734_at	NM_005337	hematopoietic	Hs.182014	BC001604	0.9
			protein 1
RABEP1	214552_s_at	NM_004703	rabaptin, RAB	Hs.551518	AF098638	0.84
			GTPase binding
			effector protein 1
SYDE1	44702_at	NM_033025	synapse defective 1,	Hs.528701	R77097	1.1
			Rho GTPase,
			homolog 1 (C. elegans)
WFDC1	219478_at	NM_021197	WAP four-disulfide	Hs.36688	NM_021197	1.2
			core domain 1
TBX2	40560_at	NM_005994	T-box 2	Hs.531085	U28049	1.1
GART	210005_at	NM_000819,	phosphoribosylglycinamide	Hs.473648	D32051	0.84
		NM_175085	formyltransferase,
			phosphoribosylglycinamide
			synthetase,
			phosphoribosylaminoimidazole
			synthetase
H2AFZ	213911_s_at,	NM_002106	H2A histone family,	Hs.119192	BF718636,	0.8
	200853_at		member Z		NM_002106
CD7	214551_s_at	NM_006137	CD7 antigen (p41)	Hs.36972	NM_006137	0.8
ELOVL6	210868_s_at	NM_024090	ELOVL family	Hs.412939	BC001305	0.81
			member 6,
			elongation of long
			chain fatty acids
			(FEN1/Elo2,
			SUR4/Elo3-like,
			yeast)
CACNB3	34726_at	NM_000725	calcium channel,	Hs.250712	U07139	1.2
			voltage-dependent,
			beta 3 subunit
TAP1	202307_s_at	NM_000593	transporter 1, ATP-	Hs.352018	NM_000593	0.68
			binding cassette,
			sub-family B
			(MDR/TAP)
NUP98	210793_s_at	NM_005387,	nucleoporin 98 kDa	Hs.524750	U41815	0.75
		NM_016320,
		NM_139131,
		NM_139132
CHAF1A	214426_x_at,	NM_005483	chromatin assembly	Hs.79018	BF062223,	0.83
	203976_s_at		factor 1, subunit A		NM_005483
			(p150)
EPAS1	200878_at	NM_001430	endothelial PAS	Hs.468410	AF052094	1.3
			domain protein 1
RNGTT	204207_s_at	NM_003800	RNA	Hs.127219	AB012142	0.8
			guanylyltransferase
			and 5′-phosphatase
KLF7	204334_at	NM_003709	Kruppel-like factor 7	Hs.471221	AA488672	1.1
			(ubiquitous)
C4orf16	219023_at	NM_018569	chromosome 4 open	Hs.435991	NM_018569	0.77
			reading frame 16
YBX2	219704_at	NM_015982	Y box binding	Hs.380691	NM_015982	0.75
			protein 2
IVD	216958_s_at	NM_002225	isovaleryl Coenzyme	Hs.513646	AK022777	0.81
			A dehydrogenase
PEG3	209242_at	NM_006210	paternally expressed 3	Hs.201776	AL042588	1.2
FBXL14	213145_at	NM_152441	F-box and leucine-	Hs.367956	BF001666	0.83
			rich repeat protein
			14
TMEPAI	217875_s_at	NM_020182,	transmembrane,	Hs.517155	NM_020182	1.4
		NM_199169,	prostate androgen
		NM_199170,	induced RNA
		NM_199171
RNF138	218738_s_at	NM_016271,	ring finger protein	Hs.302408,	NM_016271	0.82
		NM_198128	138	Hs.501040
DNM1L	203105_s_at	NM_005690,	dynamin 1-like	Hs.550499	NM_012062	0.87
		NM_012062,
		NM_012063
LHCGR	215306_at	NM_000233	luteinizing	Hs.468490	AL049443	1.3
			hormone/choriogonadotropin
			receptor
SOCS6	214462_at,	NM_004232	suppressor of	Hs.591068	NM_004232,	0.85
	206020_at		cytokine signaling 6		NM_016387
			(SOCS6)
CEP350	213956_at	NM_014810	centrosomal protein	Hs.413045	AW299294	1.3
			350 kDa
PTGER3	210374_x_at,	NM_000957,	prostaglandin E	Hs.445000	D38300,	1.1
	210831_s_at	NM_198712,	receptor 3 (subtype		L27489
		NM_198713,	EP3)
		NM_198714,
		NM_198715,
		NM_198716,
		NM_198717,
		NM_198718,
		NM_198719,
		NM_198720
M11S1	200723_s_at	NM_005898,	membrane	Hs.471818	NM_005898	0.9
		NM_203364	component,
			chromosome 11,
			surface marker 1
RFC5	203210_s_at	NM_007370,	replication factor C	Hs.506989	NM_007370	0.79
		NM_181578	(activator 1) 5,
			36.5 kDa
INDO	210029_at	NM_002164	indoleamine-pyrrole	Hs.840	M34455	0.74
			2,3 dioxygenase
KIAA0286	212619_at	NM_015257	NA	Hs.533787	AW205215	0.77
MOBK1B	201298_s_at	NM_018221	MOB1, Mps One	Hs.196437	BC003398	0.84
			Binder kinase
			activator-like 1B
			(yeast)
FLJ20273	218035_s_at	NM_019027	RNA-binding	Hs.518727	NM_019027	0.73
			protein
HADHSC	211569_s_at	NM_005327	L-3-hydroxyacyl-	Hs.438289	AF001903	0.62
			Coenzyme A
			dehydrogenase,
			short chain
SSPN	204964_s_at	NM_005086	sarcospan (Kras	Hs.183428	NM_005086	1.6
			oncogene-associated
			gene)
AP2B1	200615_s_at	NM_001030006,	adaptor-related	Hs.514819	AL567295	0.77
		NM_001282	protein complex 2,
			beta 1 subunit
EIF4A1	201530_x_at,	NM_001416	eukaryotic	Hs.129673	NM_001416,	0.79
	214805_at		translation initiation		U79273
			factor 4A, isoform 1
DEPDC1	220295_x_at	NM_017779	DEP domain	Hs.445098	NM_017779	0.66
			containing 1
AGPAT5	218096_at	NM_018361	1-acylglycerol-3-	Hs.490899	NM_018361	0.68
			phosphate O-
			acyltransferase 5
			(lysophosphatidic
			acid acyltransferase,
			epsilon)
HNRPDL	201993_x_at	NM_005463,	heterogeneous	Hs.527105	NM_005463	0.86
		NM_031372	nuclear
			ribonucleoprotein D-
			like
GBP1	202270_at	NM_002053	guanylate binding	Hs.62661,	NM_002053	0.61
			protein 1, interferon-	Hs.443527
			inducible, 67 kDa
AMIGO2	222108_at	NM_181847	adhesion molecule	Hs.121520	AC004010	1.6
			with Ig-like domain 2
XPO7	208459_s_at	NM_015024	exportin 7	Hs.172685	NM_015024	0.78
PAWR	204005_s_at	NM_002583	PRKC, apoptosis,	Hs.406074	NM_002583	0.71
			WT1, regulator
NARS	200027_at	NM_004539	asparaginyl-tRNA	Hs.465224	NM_004539	0.84
			synthetase
CENPA	204962_s_at	NM_001809	centromere protein	Hs.1594	NM_001809	0.69
			A, 17 kDa
KIF15	219306_at	NM_020242	kinesin family	Hs.307529	NM_020242	0.78
			member 15
ZNF518	204291_at	NM_014803	zinc finger protein	Hs.147895	NM_014803	0.88
			518
LPP	202821_s_at	NM_005578	LIM domain	Hs.444362	AL044018	1.3
			containing preferred
			translocation partner
			in lipoma
BRRN1	212949_at	NM_015341	barren homolog	Hs.308045	D38553	0.76
			(Drosophila)
C5orf4	48031_r_at	NM_016348,	chromosome 5 open	Hs.519694	H93077	1.2
		NM_032385	reading frame 4
UBAP1	46270_at	NM_016525	ubiquitin associated	Hs.268963	AL039447	1.1
			protein 1
SH3GLB1	209090_s_at	NM_016009	SH3-domain GRB2-	Hs.136309	AL049597	1.2
			like endophilin B1
CDKN1C	213182_x_at	NM_000076	cyclin-dependent	Hs.106070	R78668	1.4
			kinase inhibitor 1C
			(p57, Kip2)
MCM10	220651_s_at	NM_018518,	MCM10	Hs.198363	NM_018518	0.74
		NM_182751	minichromosome
			maintenance
			deficient 10 (S. cerevisiae)
KIAA0265	209254_at	NM_014997	KIAA0265 protein	Hs.520710	AI808625	1.2
BUB1	209642_at	NM_004336	BUB1 budding	Hs.469649	AF043294	0.68
			uninhibited by
			benzimidazoles 1
			homolog (yeast)
LGALS3BP	200923_at	NM_005567	lectin, galactoside-	Hs.514535	NM_005567	0.8
			binding, soluble, 3
			binding protein
NCAPD2	201774_s_at	NM_014865	non-SMC condensin	Hs.5719	AK022511	0.73
			I complex, subunit
			D2
CD86	205686_s_at	NM_006889,	CD86 antigen	Hs.171182	NM_006889	0.88
		NM_175862	(CD28 antigen
			ligand 2, B7-2
			antigen)
C16orf30	219315_s_at	NM_024600	chromosome 16	Hs.459652	NM_024600	1.2
			open reading frame
			30
RBBP8	203344_s_at	NM_002894,	retinoblastoma	Hs.546282	NM_002894	0.79
		NM_203291,	binding protein 8
		NM_203292
FEM1C	213341_at	NM_020177	fem-1 homolog c	Hs.47367	AI862658	0.82
			(C. elegans)
NUP160	214962_s_at	NM_015231	nucleoporin 160 kDa	Hs.372099	AK026236	0.84
VAMP4	213480_at	NM_003762,	vesicle-associated	Hs.6651	AF052100	1.1
		NM_201994	membrane protein 4
C9orf76	218979_at	NM_024945	chromosome 9 open	Hs.284137	NM_024945	0.8
			reading frame 76
DHX15	201386_s_at	NM_001358	DEAH (Asp-Glu-	Hs.5683	AF279891	0.83
			Ala-His) box
			polypeptide 15
RIG	221127_s_at		regulated in glioma	Hs.292156	NM_006394	1.2
HBP1	209102_s_at	NM_012257	HMG-box	Hs.162032	AF019214	1.2
			transcription factor 1
ABCE1	201873_s_at,	NM_002940	ATP-binding	Hs.12013	NM_002940,	0.79
	201872_s_at		cassette, sub-family,		AI002002
			E (OABP), member 1
PPA2	220741_s_at	NM_006903,	pyrophosphatase	Hs.480452	NM_006903	0.81
		NM_176866,	(inorganic) 2
		NM_176867,
		NM_176869
CPD	201942_s_at	NM_001304	carboxypeptidase D	Hs.446079	D85390	0.68
KIAA0828	215672_s_at	NM_015328	adenosylhomocysteinase 3	Hs.195058	AK025372	0.73
K-	211058_x_at	NM_006082	alpha tubulin	Hs.524390	BC006379	0.85
ALPHA-1
RNMT	202684_s_at	NM_003799	RNA (guanine-7-)	Hs.8086	AB020966	0.9
			methyltransferase
MIS12	221559_s_at	NM_024039	MIS12 homolog	Hs.267194	BC000229	0.8
			(yeast)
AURKB	209464_at	NM_004217	aurora kinase B	Hs.442658	AB011446	0.71
FAM64A	221591_s_at	NM_019013	family with	Hs.404323	BC005004	0.8
			sequence similarity
			64, member A
TAP2	204770_at	NM_000544,	transporter 2, ATP-	Hs.502	NM_000544	0.82
		NM_018833	binding cassette,
			sub-family B
			(MDR/TAP)
PCDHGC3	205717_x_at	NM_002588,	protocadherin	Hs.368160	NM_002588	1.2
		NM_032402,	gamma subfamily C, 3
		NM_032403
AVEN	219366_at	NM_020371	apoptosis, caspase	Hs.555966	NM_020371	1.1
			activation inhibitor
HMGB2	208808_s_at	NM_002129	high-mobility group	Hs.434953	BC000903	0.76
			box 2
CDC2	203214_x_at	NM_001786,	cell division cycle 2,	Hs.334562	NM_001786	0.72
		NM_033379	G1 to S and G2 to M
RIF1	214700_x_at	NM_018151	RAP1 interacting	Hs.536537	AK000323	0.84
			factor homolog
			(yeast)
TCF7L2	216511_s_at	NM_030756	transcription factor	Hs.501080	AJ270770	0.8
			7-like 2 (T-cell
			specific, HMG-box)
KIF11	204444_at	NM_004523	kinesin family	Hs.8878	NM_004523	0.68
			member 11
TTC19	217964_at	NM_017775	tetratricopeptide	Hs.462316	NM_017775	0.67
			repeat domain 19
MDS032	221706_s_at	NM_018467	uncharacterized	Hs.16187	BC006005	1.2
			hematopoietic
			stem/progenitor cells
			protein MDS032
PSMA3	201532_at	NM_002788,	proteasome	Hs.531089	NM_002788	0.76
		NM_152132	(prosome,
			macropain) subunit,
			alpha type, 3
PDGFA	205463_s_at		platelet-derived	Hs.376032,	NM_002607	1.3
			growth factor alpha	Hs.521331
			polypeptide
GTF2H2	221540_x_at	NM_001515	general transcription	Hs.191356,	AF078847	0.86
			factor IIH,	Hs.398348
			polypeptide 2,
			44 kDa
CXCL13	205242_at	NM_006419	chemokine (C—X—C	Hs.100431	NM_006419	0.36
			motif) ligand 13 (B-
			cell chemoattractant)
FOXM1	202580_x_at	NM_021953,	forkhead box M1	Hs.239	NM_021953	0.7
		NM_202002,
		NM_202003
YARS	212048_s_at	NM_003680	tyrosyl-tRNA	Hs.213264	AW245400	0.87
			synthetase
SE57-1	220180_at	NM_025214	coiled-coil domain	Hs.120790	NM_025214	0.77
			containing 68
CLCA4	220026_at	NM_012128	chloride channel,	Hs.546343	NM_012128	0.64
			calcium activated,
			family member 4
MCAM	211340_s_at	NM_006500	melanoma cell	Hs.511397	M28882	1.2
			adhesion molecule
PBXIP1	214177_s_at	NM_020524	pre-B-cell leukemia	Hs.505806	AI935162	1.2
			transcription factor
			interacting protein 1
PPM1D	204566_at	NM_003620	protein phosphatase	Hs.286073	NM_003620	0.88
			1D magnesium-
			dependent, delta
			isoform
FLJ22471	218175_at	NM_025140	NA	Hs.114111	NM_025140	1.2
ZBTB20	205383_s_at	NM_015642	zinc finger and BTB	Hs.122417	NM_015642	1.4
			domain containing
			20
RRM2	209773_s_at	NM_001034	ribonucleotide	Hs.226390	BC001886	0.69
		reductase M2
		polypeptide

TABLE 2

Markers with expression correlating to that of the 22 genes from NZ
signature.

						Expression
						Fold
						Difference
						(relapse/
	Affymetrix	Refseq		Unigene	Genbank	non-
Gene Symbol	Probe IDs	Access	Gene Description	Access	Access	relapse)

CCL5	1405_i_at,	NM_002985	chemokine (C-C motif)	Hs.514821	M21121,	0.69
	204655_at		ligand 5		NM_002985
SFRS10	200893_at	NM_004593	splicing factor,	Hs.533122	NM_004593	0.96
			arginine/serine-rich 10
			(transformer 2 homolog,
			Drosophila)
HLA-E	200904_at	NM_005516	major histocompatibility	Hs.381008	X56841	1
			complex, class I, E
K-ALPHA-1	201090_x_at	NM_006082	alpha tubulin	Hs.524390	NM_006082	0.87
PSMA5	201274_at	NM_002790	proteasome (prosome,	Hs.485246	NM_002790	0.95
			macropain) subunit,
			alpha type, 5
TOP2A	201292_at	NM_001067	topoisomerase (DNA) II	Hs.156346	AL561834	0.77
			alpha 170 kDa
EBNA1BP2	201323_at	NM_006824	EBNA1 binding protein 2	Hs.346868	NM_006824	0.98
SNRPC	201342_at	NM_003093	small nuclear	Hs.1063	NM_003093	1
			ribonucleoprotein
			polypeptide C
UBE2L6	201649_at	NM_004223,	ubiquitin-conjugating	Hs.425777	NM_004223	0.75
		NM_198183	enzyme E2L 6
LAPTM5	201720_s_at	NM_006762	lysosomal associated	Hs.371021	AI589086	0.89
			multispanning membrane
			protein 5
CTSL	202087_s_at	NM_001912,	cathepsin L	Hs.418123	NM_001912	0.97
		NM_145918
GBP1	202269_x_at	NM_002053	guanylate binding protein	Hs.62661,	BC002666	0.69
			1, interferon-inducible,	Hs.443527
			67 kDa
TNFAIP2	202510_s_at	NM_006291	tumor necrosis factor,	Hs.525607	NM_006291	0.91
			alpha-induced protein 2
CCNB2	202705_at	NM_004701	cyclin B2	Hs.194698	NM_004701	0.83
GBP2	202748_at	NM_004120	guanylate binding protein	Hs.386567	NM_004120	0.87
			2, interferon-inducible
CDC20	202870_s_at	NM_001255	CDC20 cell division	Hs.524947	NM_001255	0.78
			cycle 20 homolog (S. cerevisiae)
HAT1	203138_at	NM_001033085,	histone acetyltransferase 1	Hs.470611	NM_003642	0.95
		NM_003642
SPAG5	203145_at	NM_006461	sperm associated antigen 5	Hs.514033	NM_006461	0.87
RFC5	203209_at	NM_007370,	replication factor C	Hs.506989	BC001866	0.79
		NM_181578	(activator 1) 5, 36.5 kDa
MYCBP	203360_s_at	NM_012333	c-myc binding protein	Hs.370040	D50692	1
BUB1B	203755_at	NM_001211	BUB1 budding	Hs.36708	NM_001211	0.85
			uninhibited by
			benzimidazoles 1
			homolog beta (yeast)
SLA	203761_at	NM_006748	Src-like-adaptor	Hs.75367	NM_006748	0.97
VRK1	203856_at	NM_003384	vaccinia related kinase 1	Hs.422662	NM_003384	0.72
PIK3CD	203879_at	NM_005026	phosphoinositide-3-	Hs.518451	U86453	0.99
			kinase, catalytic, delta
			polypeptide
HLA-DMB	203932_at	NM_002118	major histocompatibility	Hs.1162	NM_002118	0.82
			complex, class II, DM
			beta
TRIP13	204033_at	NM_004237	thyroid hormone receptor	Hs.436187	NM_004237	0.78
			interactor 13
RARRES3	204070_at	NM_004585	retinoic acid receptor	Hs.17466	NM_004585	0.96
			responder (tazarotene
			induced) 3
CKS2	204170_s_at	NM_001827	CDC28 protein kinase	Hs.83758	NM_001827	0.8
			regulatory subunit 2
APOBEC3G	204205_at	NM_021822	apolipoprotein B mRNA	Hs.474853	NM_021822	0.74
			editing enzyme, catalytic
			polypeptide-like 3G
PSMB9	204279_at	NM_002800,	proteasome (prosome,	Hs.381081	NM_002800	0.63
		NM_148954	macropain) subunit, beta
			type, 9 (large
			multifunctional peptidase
			2)
FUSIP1	204299_at	NM_054016	FUS interacting protein	Hs.3530	NM_021993	0.9
			(serine/arginine-rich) 1
SELL	204563_at	NM_000655	selectin L (lymphocyte	Hs.82848	NM_000655	0.88
			adhesion molecule 1)
DKK1	204602_at	NM_012242	dickkopf homolog 1	Hs.40499	NM_012242	0.95
			(Xenopus laevis)
KIF23	204709_s_at	NM_004856,	kinesin family member	Hs.270845	NM_004856	0.9
		NM_138555	23
TTK	204822_at	NM_003318	TTK protein kinase	Hs.169840	NM_003318	0.8
ECGF1	204858_s_at	NM_001953	endothelial cell growth	Hs.546251	NM_001953	0.85
			factor 1 (platelet-derived)
LCP2	205269_at,	NM_005565	lymphocyte cytosolic	Hs.304475	AI123251,	0.91
	205270_s_at		protein 2 (SH2 domain		NM_005565
			containing leukocyte
			protein of 76 kDa)
BTN2A2	205298_s_at	NM_006995,	butyrophilin, subfamily	Hs.373938	W58757	0.94
		NM_181531	2, member A2
BMP5	205431_s_at	NM_021073	bone morphogenetic	Hs.296648	NM_021073	0.9
			protein 5
GZMA	205488_at	NM_006144	granzyme A (granzyme	Hs.90708	NM_006144	0.68
			1, cytotoxic T-
			lymphocyte-associated
			serine esterase 3)
SMURF2	205596_s_at	NM_022739	SMAD specific E3	Hs.515011	AY014180	1
			ubiquitin protein ligase 2
CD8A	205758_at	NM_001768,	CD8 antigen, alpha	Hs.85258	AW006735	0.78
		NM_171827	polypeptide (p32)
CD2	205831_at	NM_001767	CD2 antigen (p50), sheep	Hs.523500	NM_001767	0.87
			red blood cell receptor
JAK2	205842_s_at	NM_004972	Janus kinase 2 (a protein	Hs.434374	AF001362	0.86
			tyrosine kinase)
UBD	205890_s_at	NM_006398	ubiquitin D	Hs.44532	NM_006398	0.41
ADH1C	206262_at	NM_000669	alcohol dehydrogenase	Hs.2523	NM_000669	0.33
			1C (class I), gamma
			polypeptide
AIM2	206513_at	NM_004833	absent in melanoma 2	Hs.281898	NM_004833	0.91
SI	206664_at	NM_001041	sucrase-isomaltase	Hs.429596	NM_001041	0.39
			(alpha-glucosidase)
NAT2	206797_at	NM_000015	N-acetyltransferase 2	Hs.2	NM_000015	0.82
			(arylamine N-
			acetyltransferase)
SP110	208012_x_at	NM_004509,	SP110 nuclear body	Hs.145150	NM_004509	0.95
		NM_004510,	protein
		NM_080424
PRDX1	208680_at	NM_002574,	peroxiredoxin 1	Hs.180909	L19184	1
		NM_181696,
		NM_181697
PSMA6	208805_at	NM_002791	proteasome (prosome,	Hs.446260	BC002979	0.87
			macropain) subunit,
			alpha type, 6
IFI16	208966_x_at	NM_005531	interferon, gamma-	Hs.380250	AF208043	1.2
			inducible protein 16
PPIG	208995_s_at	NM_004792	peptidyl-prolyl isomerase	Hs.470544	U40763	0.98
			G (cyclophilin G)
KIF2C	209408_at,	NM_006845	kinesin family member	Hs.69360	U63743,	0.75
	211519_s_at		2C		AY026505
APOL1	209546_s_at	NM_003661,	apolipoprotein L, 1	Hs.114309	AF323540	0.98
		NM_145343,
		NM_145344
CD74	209619_at	NM_001025158,	CD74 antigen (invariant	Hs.436568	K01144	0.76
		NM_001025159,	polypeptide of major
		NM_004355	histocompatibility
			complex, class II antigen-
			associated)
HMMR	209709_s_at	NM_012484,	hyaluronan-mediated	Hs.72550	U29343	0.84
		NM_012485	motility receptor
			(RHAMM)
CDKN3	209714_s_at	NM_005192	cyclin-dependent kinase	Hs.84113	AF213033	0.71
			inhibitor 3 (CDK2-
			associated dual
			specificity phosphatase)
BUB3	209974_s_at	NM_001007793,	BUB3 budding	Hs.418533	AF047473	0.84
		NM_004725	uninhibited by
			benzimidazoles 3
			homolog (yeast)
SOCS1	210001_s_at	NM_003745	suppressor of cytokine	Hs.50640	AB005043	0.93
			signaling 1
CD3Z	210031_at	NM_000734,	CD3Z antigen, zeta	Hs.156445	J04132	0.87
		NM_198053	polypeptide (TiT3
			complex)
CACYBP	210691_s_at	NM_001007214,	calcyclin binding protein	Hs.508524	AF275803	0.97
		NM_014412
HLA-DRA	210982_s_at	NM_019111	major histocompatibility	Hs.520048	M60333	0.74
			complex, class II, DR
			alpha
NEK2	211080_s_at	NM_002497	NIMA (never in mitosis	Hs.153704	Z25425	0.77
			gene a)-related kinase 2
NF2	211091_s_at	NM_000268,	neurofibromin 2	Hs.187898	AF122828	0.96
		NM_016418,	(bilateral acoustic
		NM_181825,	neuroma)
		NM_181826,
		NM_181827,
		NM_181828,
		NM_181829,
		NM_181830,
		NM_181831,
		NM_181832,
		NM_181833,
		NM_181834,
		NM_181835
FYB	211795_s_at	NM_001465,	FYN binding protein	Hs.370503	AF198052	0.83
		NM_199335	(FYB-120/130)
HLA-DPA1	211991_s_at	NM_033554	major histocompatibility	Hs.347270	M27487	0.75
			complex, class II, DP
			alpha 1
PTPRC	212587_s_at,	NM_002838,	protein tyrosine	Hs.192039	AI809341,	0.77
	212588_at	NM_080921,	phosphatase, receptor		Y00062
		NM_080922,	type, C
		NM_080923
SP3	213168_at	NM_001017371,	Sp3 transcription factor	Hs.531587	AU145005	0.98
		NM_003111
ITGAL	213475_s_at	NM_002209	integrin, alpha L (antigen	Hs.174103	AC002310	0.85
			CD11A (p180),
			lymphocyte function-
			associated antigen 1,
			alpha polypeptide)
RAC2	213603_s_at	NM_002872	ras-related C3 botulinum	Hs.517601	BE138888	0.92
			toxin substrate 2 (rho
			family, small GTP
			binding protein Rac2)
DNA2L	213647_at		DNA2 DNA replication	Hs.532446	D42046	0.87
			helicase 2-like (yeast)
TRAF3IP3	213888_s_at	NM_025228	TRAF3 interacting	Hs.147434	AL022398	0.86
			protein 3
NKG7	213915_at	NM_005601	natural killer cell group 7	Hs.10306	NM_005601	0.72
			sequence
SFRS7	214141_x_at	NM_001031684,	splicing factor,	Hs.309090	BF033354	0.88
		NM_006276	arginine/serine-rich 7,
			35 kDa
ZG16	214142_at	NM_152338	zymogen granule protein	Hs.184507	AI732905	0.18
			16
PRF1	214617_at	NM_005041	perforin 1 (pore forming	Hs.2200	AI445650	0.81
			protein)
CCNB1	214710_s_at	NM_031966	cyclin B1	Hs.23960	BE407516	0.63
KIAA0907	214995_s_at	NM_014949	KIAA0907	Hs.24656	BF508948	0.82
GTSE1	215942_s_at	NM_016426	G-2 and S-phase	Hs.386189,	BF973178	0.86
			expressed 1	Hs.475140
HMGB3	216548_x_at	NM_005342	high-mobility group box 3	Hs.19114	AL049709	0.97
HLA-DMA	217478_s_at	NM_006120	major histocompatibility	Hs.351279	X76775	0.8
			complex, class II, DM
			alpha
C20orf45	217851_s_at	NM_016045	chromosome 20 open	Hs.3945	NM_016045	1.1
			reading frame 45
MRPL42	217919_s_at	NM_014050,	mitochondrial ribosomal	Hs.199579	BE782148	0.79
		NM_172177,	protein L42
		NM_172178
NUSAP1	218039_at,	NM_016359,	nucleolar and spindle	Hs.511093	NM_016359,	0.92
	219978_s_at	NM_018454	associated protein 1		NM_018454
TMEM48	218073_s_at	NM_018087	transmembrane protein 48	Hs.476525	NM_018087	0.71
DHX40	218277_s_at	NM_024612	DEAH (Asp-Glu-Ala-	Hs.29403	NM_024612	1.1
			His) box polypeptide 40
NFS1	218455_at	NM_021100,	NFS1 nitrogen fixation 1	Hs.194692	NM_021100	1
		NM_181679	(S. cerevisiae)
C10orf3	218542_at	NM_018131	chromosome 10 open	Hs.14559	NM_018131	0.77
			reading frame 3
NCAPG	218663_at	NM_022346	non-SMC condensin I	Hs.446201,	NM_022346	0.73
			complex, subunit G	Hs.479270
FBXO5	218875_s_at	NM_012177	F-box protein 5	Hs.520506	NM_012177	0.89
SLAMF8	219385_at	NM_020125	SLAM family member 8	Hs.438683	NM_020125	0.94
CENPN	219555_s_at	NM_018455	centromere protein N	Hs.283532	NM_018455	0.81
ATP13A3	219558_at		ATPase type 13A3	Hs.529609	NM_024524	0.75
ECT2	219787_s_at	NM_018098	epithelial cell	Hs.518299	NM_018098	0.75
			transforming sequence 2
			oncogene
ASPM	219918_s_at	NM_018136	asp (abnormal spindle)-	Hs.121028	NM_018123	0.89
			like, microcephaly
			associated (Drosophila)
ZC3HAV1	220104_at	NM_020119,	zinc finger CCCH-type,	Hs.133512	NM_020119	0.93
		NM_024625	antiviral 1
CLEC2D	220132_s_at	NM_001004419,	C-type lectin superfamily	Hs.268326	NM_013269	0.91
		NM_001004420,	2, member D
		NM_013269
MS4A12	220834_at	NM_017716	membrane-spanning 4-	Hs.272789	NM_017716	0.5
			domains, subfamily A,
			member 12
C1orf112	220840_s_at	NM_018186	chromosome 1 open	Hs.443551	NM_018186	0.96
			reading frame 112
TPRT	220865_s_at	NM_014317	trans-prenyltransferase	Hs.555924	NM_014317	0.92
APOL3	221087_s_at	NM_014349,	apolipoprotein L, 3	Hs.474737	NM_014349	0.84
		NM_030644,
		NM_145639,
		NM_145640,
		NM_145641,
		NM_145642
C14orf156	221434_s_at	NM_031210	chromosome 14 open	Hs.324521	NM_031210	0.9
			reading frame 156
YTHDF3	221749_at	NM_152758	YTH domain family,	Hs.491861	AU157915	0.95
			member 3
LOC146909	222039_at		hypothetical protein	Hs.135094	AA292789	0.83
			LOC146909
TRAFD1	35254_at	NM_006700	TRAF-type zinc finger	Hs.5148	AB007447	0.98
			domain containing 1
ESPL1	38158_at	NM_012291	extra spindle poles like 1	Hs.153479	D79987	0.87
			(S. cerevisiae)
BTN3A3	38241_at	NM_006994,	butyrophilin, subfamily	Hs.167741	U90548	0.9
		NM_197974	3, member A3

General Approaches to Prognostic Marker Detection

The following approaches are non-limiting methods that can be used to detect the proliferation markers, including CCPM family members: microarray approaches using oligonucleotide probes selective for a CCPM; real-time qPCR on tumour samples using CCPM specific primers and probes; real-time qPCR on lymph node, blood, serum, faecal, or urine samples using CCPM specific primers and probes; enzyme-linked immunological assays (ELISA); immunohistochemistry using anti-marker antibodies; and analysis of array or qPCR data using computers.
Other useful methods include northern blotting and in situ hybridization (Parker and Barnes, Methods in Molecular Biology 106: 247-283 (1999)); RNase protection assays (Hod, BioTechniques 13: 852-854 (1992)); reverse transcription polymerase chain reaction (RT-PCR; Weis et al., Trends in Genetics 8: 263-264 (1992)); serial analysis of gene expression (SAGE; Velculescu et al., Science 270: 484-487 (1995); and Velculescu et al., Cell 88: 243-51 (1997)), MassARRAY technology (Sequenom, San Diego, Calif.), and gene expression analysis by massively parallel signature sequencing (MPSS; Brenner et al., Nature Biotechnology 18: 630-634 (2000)). Alternatively, antibodies may be employed that can recognize specific complexes, including DNA duplexes, RNA duplexes, and DNA-RNA hybrid duplexes or DNA-polypeptide duplexes.
Primary data can be collected and fold change analysis can be performed, for example, by comparison of marker expression levels in tumour tissue and non-tumour tissue; by comparison of marker expression levels to levels determined in recurring tumours and non-recurring tumours; by comparison of marker expression levels to levels determined in tumours with or without metastasis; by comparison of marker expression levels to levels determined in differently staged tumours; or by comparison of marker expression levels to levels determined in cells with different levels of proliferation. A negative or positive prognosis is determined based on this analysis. Further analysis of tumour marker expression includes matching those markers exhibiting increased or decreased expression with expression profiles of known colorectal tumours to provide a prognosis.
A threshold for concluding that expression is increased will be dependent on the particular marker and also the particular predictive model that is to be applied. The threshold is generally set to achieve the highest sensitivity and selectivity with the lowest error rate, although variations may be desirable for a particular clinical situation. The desired threshold is determined by analysing a population of sufficient size taking into account the statistical variability of any predictive model and is calculated from the size of the sample used to produce the predictive model. The same applies for the determination of a threshold for concluding that expression is decreased. It can be appreciated that other thresholds, or methods for establishing a threshold, for concluding that increased or decreased expression has occurred can be selected without departing from the scope of this invention.
It is also possible that a prediction model may produce as it's output a numerical value, for example a score, likelihood value or probability. In these instances, it is possible to apply thresholds to the results produced by prediction models, and in these cases similar principles apply as those used to set thresholds for expression values.
Once the expression level, or output of a prediction model, of a predictive signature in a tumour sample has been obtained, the likelihood of the cancer recurring can then be determined.
From the markers identified, prognostic signatures comprising one or more CCPMs can be used to determine the prognosis of a cancer, by comparing the expression level of the one or more markers to the disclosed prognostic signature. By comparing the expression of one or more of the CCPMs in a tumour sample with the disclosed prognostic signature, the likelihood of the cancer recurring can be determined. The comparison of expression levels of the prognostic signature to establish a prognosis can be done by applying a predictive model as described previously.
Determining the likelihood of the cancer recurring is of great value to the medical practitioner. A high likelihood of re-occurrence means that a longer or higher dose treatment should be given, and the patient should be more closely monitored for signs of recurrence of the cancer. An accurate prognosis is also of benefit to the patient. It allows the patient, along with their partners, family, and friends to also make decisions about treatment, as well as decisions about their future and lifestyle changes. Therefore, the invention also provides for a method establishing a treatment regime for a particular cancer based on the prognosis established by matching the expression of the markers in a tumour sample with the differential expression signature.
It will be appreciated that the marker selection, or construction of a prognostic signature, does not have to be restricted to the CCPMs disclosed in Tables 1, 2, or 5, herein, or the prognostic signatures disclosed in Tables 3, 4, 8A, 8B, and 9, but could involve the use of one or more CCPMs from the disclosed signatures, or a new signature may be established using CCPMs selected from the disclosed marker lists. The requirement of any signature is that it predicts the likelihood of recurrence with enough accuracy to assist a medical practitioner to establish a treatment regime.

Reverse Transcription PCR (RT-PCR)

Of the techniques listed above, the most sensitive and most flexible quantitative method is RT-PCR, which can be used to compare RNA levels in different sample populations, in normal and tumour tissues, with or without drug treatment, to characterize patterns of expression, to discriminate between closely related RNAs, and to analyze RNA structure.
For RT-PCR, the first step is the isolation of RNA from a target sample. The starting material is typically total RNA isolated from human tumours or tumour cell lines, and corresponding normal tissues or cell lines, respectively. RNA can be isolated from a variety of samples, such as tumour samples from breast, lung, colon (e.g., large bowel or small bowel), colorectal, gastric, esophageal, anal, rectal, prostate, brain, liver, kidney, pancreas, spleen, thymus, testis, ovary, uterus, etc., tissues, from primary tumours, or tumour cell lines, and from pooled samples from healthy donors. If the source of RNA is a tumour, RNA can be extracted, for example, from frozen or archived paraffin-embedded and fixed (e.g., formalin-fixed) tissue samples.
The first step in gene expression profiling by RT-PCR is the reverse transcription of the RNA template into cDNA, followed by its exponential amplification in a PCR reaction. The two most commonly used reverse transcriptases are avian myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukaemia virus reverse transcriptase (MMLV-RT). The reverse transcription step is typically primed using specific primers, random hexamers, or oligo-dT primers, depending on the circumstances and the goal of expression profiling. For example, extracted RNA can be reverse-transcribed 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, it typically employs the Taq DNA polymerase, which has a 5′-3′ nuclease activity but lacks a 3′-5′ proofreading endonuclease activity. Thus, TaqMan (q) PCR typically utilizes the 5′ nuclease activity of Taq or Tth polymerase to hydrolyze 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 an amplicon typical of a PCR reaction. A third oligonucleotide, or probe, is designed to detect nucleotide sequence located between the two PCR primers. The probe is non-extendible by Taq DNA polymerase enzyme, and is labeled with a reporter fluorescent dye and a quencher fluorescent dye. Any laser-induced emission from the reporter dye is quenched by the quenching dye when the two dyes are located close together as they are on the probe. During the amplification reaction, the Taq DNA polymerase enzyme cleaves the probe in a template-dependent manner. The resultant probe fragments disassociate in solution, and signal from the released reporter dye is free from the quenching effect of the second fluorophore. One molecule of reporter dye is liberated for each new molecule synthesized, and detection of the unquenched reporter 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, Calif., USA), or Lightcycler (Roche Molecular Biochemicals, Mannheim, Germany). In a preferred embodiment, the 5′ nuclease procedure is run on a real-time quantitative PCR device such as the ABI PRISM 7700tam Sequence Detection System. The system consists of a thermocycler, laser, charge-coupled device (CCD), camera, and computer. The system amplifies samples in a 96-well format on a thermocycler. During amplification, laser-induced fluorescent signal is collected in real-time through fibre optics cables for all 96 wells, and detected at the CCD. The system includes software for running the instrument and for analyzing the data.
5′ nuclease assay data are initially expressed as Ct, or the threshold cycle. As discussed above, fluorescence values are recorded during every cycle and represent the amount of product amplified to that point in the amplification reaction. The point when the fluorescent signal is first recorded as statistically significant is the threshold cycle.
To minimize errors and the effect of sample-to-sample variation, RT-PCR is usually performed using an internal standard. The ideal internal standard is expressed at a constant level among different tissues, and is unaffected by the experimental treatment. RNAs most frequently used to normalize patterns of gene expression are mRNAs for the housekeeping genes glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) and-actin.
Real-Time Quantitative PCR (qPCR)
A more recent variation of the RT-PCR technique is the real time quantitative PCR, which measures PCR product accumulation through a dual-labeled fluorigenic probe (i.e., TaqMan probe). Real time PCR is compatible both with quantitative competitive PCR and with quantitative comparative PCR. The former uses an internal competitor for each target sequence for normalization, while the latter uses a normalization gene contained within the sample, or a housekeeping gene for RT-PCR. Further details are provided, e.g., by Held et al., Genome Research 6: 986-994 (1996).
Expression levels can be determined using fixed, paraffin-embedded tissues as the RNA source. According to one aspect of the present invention, PCR primers and probes are designed based upon intron sequences present in the gene to be amplified. In this embodiment, the first step in the primer/probe design is the delineation of intron sequences within the genes. This can be done by publicly available software, such as the DNA BLAT software developed by Kent, W. J., Genome Res. 12 (4): 656-64 (2002), or by the BLAST software including its variations. Subsequent steps follow well established methods of PCR primer and probe design.
In order to avoid non-specific signals, it is useful to mask repetitive sequences within the introns when designing the primers and probes. This can be easily accomplished by using the Repeat Masker program available on-line through the Baylor College of Medicine, which screens DNA sequences against a library of repetitive elements and returns a query sequence in which the repetitive elements are masked. The masked sequences can then be used to design primer and probe sequences using any commercially or otherwise publicly available primer/probe design packages, 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 Biology. Humana Press, Totowa, N.J., pp 365-386).
The most important factors considered in PCR primer design include primer length, melting temperature (T_m), 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 contain about 20-80%, such as, for example, about 50-60% G+C bases. Melting temperatures between 50 and 80° C., e.g., about 50 to 70° C., are typically preferred. For further guidelines for PCR primer and probe design see, e.g., Dieffenbach, C. W. et al., General Concepts for PCR Primer Design in: PCR Primer, A Laboratory Manual, Cold Spring Harbor Laboratory Press, New York, 1995, pp. 133-155; Innis and Gelfand, Optimization of PCRs in: PCR Protocols, A Guide to Methods and Applications, CRC Press, London, 1994, pp. 5-11; and Plasterer, T. N. Primerselect: Primer and probe design. Methods Mol. Biol. 70: 520-527 (1997), the entire disclosures of which are hereby expressly incorporated by reference.

Microarray Analysis

Differential expression can also be identified, or confirmed using the microarray technique. Thus, the expression profile of CCPMs can be measured in either fresh or paraffin-embedded tumour tissue, using microarray technology. In this method, polynucleotide sequences of interest (including cDNAs and oligonucleotides) are plated, or arrayed, on a microchip substrate. The arrayed sequences (i.e., capture probes) are then hybridized with specific polynucleotides from cells or tissues of interest (i.e., targets). Just as in the RT-PCR method, the source of RNA typically is total RNA isolated from human tumours or tumour cell lines, and corresponding normal tissues or cell lines. Thus RNA can be isolated from a variety of primary tumours or tumour cell lines. If the source of RNA is a primary tumour, RNA can be extracted, for example, from frozen or archived formalin fixed paraffin-embedded (FFPE) tissue samples and fixed (e.g., formalin-fixed) tissue samples, which are routinely prepared and preserved in everyday clinical practice.
In a specific embodiment of the microarray technique, PCR amplified inserts of cDNA clones are applied to a substrate. The substrate can include up to 1, 2, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, or 75 nucleotide sequences. In other aspects, the substrate can include at least 10,000 nucleotide sequences. The microarrayed sequences, immobilized on the microchip, are suitable for hybridization under stringent conditions. As other embodiments, the targets for the microarrays can be at least 50, 100, 200, 400, 500, 1000, or 2000 bases in length; or 50-100, 100-200, 100-500, 100-1000, 100-2000, or 500-5000 bases in length. As further embodiments, the capture probes for the microarrays can be at least 10, 15, 20, 25, 50, 75, 80, or 100 bases in length; or 10-15, 10-20, 10-25, 10-50, 10-75, 10-80, or 20-80 bases in length.
Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array. After stringent washing to remove non-specifically bound probes, the chip is scanned by confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance. With dual colour fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pairwise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously. An exemplary protocol for this is described in detail in Example 4.
The miniaturized scale of the hybridization affords a convenient and rapid evaluation of the expression pattern for large numbers of genes. Such methods have been shown to have the sensitivity required to detect rare transcripts, which are expressed at a few copies per cell, and to reproducibly detect at least approximately two-fold differences in the expression levels (Schena et al., Proc. Natl. Acad. Sci. USA 93 (2): 106-149 (1996)). Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip technology, IIlumina microarray technology or Incyte's microarray technology. The development of microarray methods for large-scale analysis of gene expression makes it possible to search systematically for molecular markers of cancer classification and outcome prediction in a variety of tumour types.

RNA Isolation, Purification, and Amplification

General methods for mRNA extraction are well known in the art and are disclosed in standard textbooks of molecular biology, including Ausubel et al., Current Protocols of Molecular Biology, John Wiley and Sons (1997). Methods for RNA extraction from paraffin embedded tissues are disclosed, for example, in Rupp and Locker, Lab Invest. 56: A67 (1987), and De Sandres et al., BioTechniques 18: 42044 (1995). In particular, RNA isolation can be performed using purification kit, buffer set, and 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 Qiagen RNeasy mini-columns. Other commercially available RNA isolation kits include MasterPure Complete DNA and RNA Purification Kit (EPICENTRE (D, Madison, Wis.), and Paraffin Block RNA Isolation Kit (Ambion, Inc.). Total RNA from tissue samples can be isolated using RNA Stat-60 (Tel-Test). RNA prepared from tumour can be isolated, for example, by cesium chloride density gradient centrifugation.
The steps of a representative protocol for profiling gene expression using fixed, paraffin-embedded tissues as the RNA source, including mRNA isolation, purification, primer extension and amplification are given in various published journal articles (for example: T. E. Godfrey et al. J. Molec. Diagnostics 2: 84-91 (2000); K. Specht et al., Am. J. Pathol. 158: 419-29 (2001)). Briefly, a representative process starts with cutting about 10 μm thick sections of paraffin-embedded tumour tissue samples. The RNA is then extracted, and protein and DNA are removed. After analysis of the RNA concentration, RNA repair and/or amplification steps may be included, if necessary, and RNA is reverse transcribed using gene specific promoters followed by RT-PCR. Finally, the data are analyzed to identify the best treatment option(s) available to the patient on the basis of the characteristic gene expression pattern identified in the tumour sample examined.

Immunohistochemistry and Proteomics

Immunohistochemistry methods are also suitable for detecting the expression levels of the proliferation markers of the present invention. Thus, antibodies or antisera, preferably polyclonal antisera, and most preferably monoclonal antibodies specific for each marker, are used to detect expression. The antibodies can be detected by direct labeling of the antibodies themselves, for example, with radioactive labels, fluorescent labels, hapten labels such as, biotin, or an enzyme such as horse radish peroxidase or alkaline phosphatase. Alternatively, unlabeled primary antibody is used in conjunction with a labeled secondary antibody, comprising antisera, polyclonal antisera or a monoclonal antibody specific for the primary antibody. Immunohistochemistry protocols and kits are well known in the art and are commercially available.
Proteomics can be used to analyze the polypeptides present in a sample (e.g., tissue, organism, or cell culture) at a certain point of time. In particular, proteomic techniques can be used to assess the global changes of polypeptide expression in a sample (also referred to as expression proteomics). Proteomic analysis typically includes: (1) separation of individual polypeptides in a sample by 2-D gel electrophoresis (2-D PAGE); (2) identification of the individual polypeptides recovered from the gel, e.g., by mass spectrometry or N-terminal sequencing, and (3) analysis of the data using bioinformatics. Proteomics methods are valuable supplements to other methods of gene expression profiling, and can be used, alone or in combination with other methods, to detect the products of the proliferation markers of the present invention.
Once the expression level of one or more prognostic markers in a tumour sample has been assessed the likelihood of the cancer recurring can then be determined. The inventors have identified a number of markers that are differentially expressed in non-recurring colorectal cancers compared to recurring colorectal cancers in patient data sets. The markers are set out in Tables 1, 2, and 9, in the examples below.
Selection of Differentially Expressed Genes.
An early approach to the selection of genes deemed significant involved simply looking at the “fold change” of a given gene between the two groups of interest. While this approach hones in on genes that seem to change the most spectacularly, consideration of basic statistics leads one to realize that if the variance (or noise level) is quite high (as is often seen in microarray experiments), then seemingly large fold-change can happen frequently by chance alone.
Microarray experiments, such as those described here, typically involve the simultaneous measurement of thousands of genes. If one is comparing the expression levels for a particular gene between two groups (for example recurrent and non-recurrent tumours), the typical tests for significance (such as the t-test) are not adequate. This is because, in an ensemble of thousands of experiments (in this context each gene constitutes an “experiment”), the probability of at least one experiment passing the usual criteria for significance by chance alone is essentially unity. In a test for significance, one typically calculates the probability that the “null hypothesis” is correct. In the case of comparing two groups, the null hypothesis is that there is no difference between the two groups. If a statistical test produces a probability for the null hypothesis below some threshold (usually 0.05 or 0.01), it is stated that we can reject the null hypothesis, and accept the hypothesis that the two groups are significantly different. Clearly, in such a test, a rejection of the null hypothesis by chance alone could be expected 1 in 20 times (or 1 in 100). The use of t-tests, or other similar statistical tests for significance, fail in the context of microarrays, producing far too many false positives (or type I errors)
In this type of situation, where one is testing multiple hypotheses at the same time, one applies typical multiple comparison procedures, such as the Bonferroni Method (43). However such tests are too conservative for most microarray experiments, resulting in too many false negative (type II) errors.
A more recent approach is to do away with attempting to apply a probability for a given test being significant, and establish a means for selecting a subset of experiments, such that the expected proportion of Type I errors (or false discovery rate; 47) is controlled for. It is this approach that has been used in this investigation, through various implementations, namely the methods provided with BRB Array Tools (48), and the limma (11,42) package of Bioconductor (that uses the R statistical environment; 10,39).

General Methodology for Data Mining: Generation of Prognostic Signatures

Data Mining is the term used to describe the extraction of “knowledge”, in other words the “know-how”, or predictive ability from (usually) large volumes of data (the dataset). This is the approach used in this study to generate prognostic signatures. In the case of this study the “know-how” is the ability to accurately predict prognosis from a given set of gene expression measurements, or “signature” (as described generally in this section and in more detail in the examples section).
The specific details used for the methods used in this study are described in Examples 17-20. However, application of any of the data mining methods (both those described in the Examples, and those described here) can follow this general protocol.
Data mining (49), and the related topic machine learning (40) is a complex, repetitive mathematical task that involves the use of one or more appropriate computer software packages (see below). The use of software is advantageous on the one hand, in that one does not need to be completely familiar with the intricacies of the theory behind each technique in order to successfully use data mining techniques, provided that one adheres to the correct methodology. The disadvantage is that the application of data mining can often be viewed as a “black box”: one inserts the data and receives the answer. How this is achieved is often masked from the end-user (this is the case for many of the techniques described, and can often influence the statistical method chosen for data mining. For example, neural networks and support vector machines have a particularly complex implementation that makes it very difficult for the end user to extract out the “rules” used to produce the decision. On the other hand, k-nearest neighbours and linear discriminant analysis have a very transparent process for decision making that is not hidden from the user.
There are two types of approach used in data mining: supervised and unsupervised approaches. In the supervised approach, the information that is being linked to the data is known, such as categorical data (e.g. recurrent vs. non recurrent tumours). What is required is the ability to link the observed response (e.g. recurrence vs. non-recurrence) to the input variables. In the unsupervised approach, the classes within the dataset are not known in advance, and data mining methodology is employed to attempt to find the classes or structure within the dataset.
In the present example the supervised approach was used and is discussed in detail here, although it will be appreciated that any of the other techniques could be used.
The overall protocol involves the following steps:

- Data representation. This involves transformation of the data into a form that is most likely to work successfully with the chosen data mining technique. In where the data is numerical, such as in this study where the data being investigated represents relative levels of gene expression, this is fairly simple. If the data covers a large dynamic range (i.e. many orders of magnitude) often the log of the data is taken. If the data covers many measurements of separate samples on separate days by separate investigators, particular care has to be taken to ensure systematic error is minimised. The minimisation of systematic error (i.e. errors resulting from protocol differences, machine differences, operator differences and other quantifiable factors) is the process referred to here as “normalisation”.
- Feature Selection. Typically the dataset contains many more data elements than would be practical to measure on a day-to-day basis, and additionally many elements that do not provide the information needed to produce a prediction model. The actual ability of a prediction model to describe a dataset is derived from some subset of the full dimensionality of the dataset. These dimensions the most important components (or features) of the dataset. Note in the context of microarray data, the dimensions of the dataset are the individual genes. Feature selection, in the context described here, involves finding those genes which are most “differentially expressed”. In a more general sense, it involves those groups which pass some statistical test for significance, i.e. is the level of a particular variable consistently higher or lower in one or other of the groups being investigated. Sometimes the features are those variables (or dimensions) which exhibit the greatest variance. The application of feature selection is completely independent of the method used to create a prediction model, and involves a great deal of experimentation to achieve the desired results. Within this invention, the selection of significant genes, and those which correlated with the earlier successful model (the NZ classifier), entailed feature selection. In addition, methods of data reduction (such as principal component analysis) can be applied to the dataset.
- Training. Once the classes (e.g. recurrence/non-recurrence) and the features of the dataset have been established, and the data is represented in a form that is acceptable as input for data mining, the reduced dataset (as described by the features) is applied to the prediction model of choice. The input for this model is usually in the form a multi-dimensional numerical input, (known as a vector), with associated output information (a class label or a response). In the training process, selected data is input into the prediction model, either sequentially (in techniques such as neural networks) or as a whole (in techniques that apply some form of regression, such as linear models, linear discriminant analysis, support vector machines). In some instances (e.g. k-nearest neighbours) the dataset (or subset of the dataset obtained after feature selection) is itself the model. As discussed, effective models can be established with minimal understanding of the detailed mathematics, through the use of various software packages where the parameters of the model have been pre-determined by expert analysts as most likely to lead to successful results.
- Validation. This is a key component of the data-mining protocol, and the incorrect application of this frequently leads to errors. Portions of the dataset are to be set aside, apart from feature selection and training, to test the success of the prediction model. Furthermore, if the results of validation are used to effect feature selection and training of the model, then one obtains a further validation set to test the model before it is applied to real-life situations. If this process is not strictly adhered to the model is likely to fail in real-world situations. The methods of validation are described in more detail below.
- Application. Once the model has been constructed, and validated, it must be packaged in some way as it is accessible to end users. This often involves implementation of some form a spreadsheet application, into which the model has been imbedded, scripting of a statistical software package, or refactoring of the model into a hard-coded application by information technology staff.

Examples of software packages that are frequently used are:

- Spreadsheet plugins, obtained from multiple vendors.
- The R statistical environment.
- The commercial packages MatLab, S-plus, SAS, SPSS, STATA.
- Free open-source software such as Octave (a MatLab clone)
- many and varied C++ libraries, which can be used to implement prediction models in a commercial, closed-source setting.

Examples of Data Mining Methods.

The methods can be by first performing the step of data mining process (above), and then applying the appropriate known software packages. Further description of the process of data mining is described in detail in many extremely well-written texts.(49)

- Linear models (49, 50): The data is treated as the input of a linear regression model, of which the class labels or responses variables are the output. Class labels, or other categorical data, must be transformed into numerical values (usually integer). In generalised linear models, the class labels or response variables are not themselves linearly related to the input data, but are transformed through the use of a “link function”. Logistic regression is the most common form of generalized linear model.
- Linear Discriminant analysis (49, 51, 52). Provided the data is linearly separable (i.e. the groups or classes of data can be separated by a hyperplane, which is an n-dimensional extension of a threshold), this technique can be applied. A combination of variables is used to separate the classes, such that the between group variance is maximised, and the within-group variance is minimised. The byproduct of this is the formation of a classification rule. Application of this rule to samples of unknown class allows predictions or classification of class membership to be made for that sample. There are variations of linear discriminant analysis such as nearest shrunken centroids which are commonly used for microarray analysis.
- Support vector machines (53): A collection of variables is used in conjunction with a collection of weights to determine a model that maximizes the separation between classes in terms of those weighted variables. Application of this model to a sample then produces a classification or prediction of class membership for that sample.
- Neural networks (52): The data is treated as input into a network of nodes, which superficially resemble biological neurons, which apply the input from all the nodes to which they are connected, and transform the input into an output. Commonly, neural networks use the “multiply and sum” algorithm, to transform the inputs from multiple connected input nodes into a single output. A node may not necessarily produce an output unless the inputs to that node exceed a certain threshold. Each node has as its input the output from several other nodes, with the final output node usually being linked to a categorical variable. The number of nodes, and the topology of the nodes can be varied in almost infinite ways, providing for the ability to classify extremely noisy data that may not be possible to categorize in other ways. The most common implementation of neural networks is the multi-layer perceptron.
- Classification and regression trees (54): In these. variables are used to define a hierarchy of rules that can be followed in a stepwise manner to determine the class of a sample. The typical process creates a set of rules which lead to a specific class output, or a specific statement of the inability to discriminate. A example classification tree is an implementation of an algorithm such as:


	if gene A> x and gene Y > x and gene Z = z
	then
	class A
	else if geneA = q
	then
	class B

- Nearest neighbour methods (51, 52). Predictions or classifications are made by comparing a sample (of unknown class) to those around it (or known class), with closeness defined by a distance function. It is possible to define many different distance functions. Commonly used distance functions are the Euclidean distance (an extension of the Pythagorean distance, as in triangulation, to n-dimensions), various forms of correlation (including Pearson Correlation co-efficient). There are also transformation functions that convert data points that would not normally be interconnected by a meaningful distance metric into euclidean space, so that Euclidean distance can then be applied (e.g. Mahalanobis distance). Although the distance metric can be quite complex, the basic premise of k-nearest neighbours is quite simple, essentially being a restatement of “find the k-data vectors that are most similar to the unknown input, find out which class they correspond to, and vote as to which class the unknown input is”.
- Other methods:
  - Bayesian networks. A directed acyclic graph is used to represent a collection of variables in conjunction with their joint probability distribution, which is then used to determine the probability of class membership for a sample.
  - Independent components analysis, in which independent signals (e.g., class membership) re isolated (into components) from a collection of variables. These components can then be used to produce a classification or prediction of class membership for a sample.
- Ensemble learning methods in which a collection of prediction methods are combined to produce a joint classification or prediction of class membership for a sample

There are many variations of these methodologies that can be explored (49), and many new methodologies are constantly being defined and developed. It will be appreciated that any one of these methodologies can be applied in order to obtain an acceptable result. Particular care must be taken to avoid overfitting, by ensuring that all results are tested via a comprehensive validation scheme.

Validation

Application of any of the prediction methods described involves both training and cross-validation (43, 55) before the method can be applied to new datasets (such as data from a clinical trial). Training involves taking a subset of the dataset of interest (in this case gene expression measurements from colorectal tumours), such that it is stratified across the classes that are being tested for (in this case recurrent and non-recurrent tumours). This training set is used to generate a prediction model (defined above), which is tested on the remainder of the data (the testing set).
It is possible to alter the parameters of the prediction model so as to obtain better performance in the testing set, however, this can lead to the situation known as overfitting, where the prediction model works on the training dataset but not on any external dataset. In order to circumvent this, the process of validation is followed. There are two major types of validation typically applied, the first (hold-out validation) involves partitioning the dataset into three groups: testing, training, and validation. The validation set has no input into the training process whatsoever, so that any adjustment of parameters or other refinements must take place during application to the testing set (but not the validation set). The second major type is cross-validation, which can be applied in several different ways, described below.
There are two main sub-types of cross-validation: K-fold cross-validation, and leave-one-out cross-validation
K-fold cross-validation: The dataset is divided into K subsamples, each subsample containing approximately the same proportions of the class groups as the original. In each round of validation, one of the K subsamples is set aside, and training is accomplished using the remainder of the dataset. The effectiveness of the training for that round is gauged by how correctly the classification of the left-out group is. This procedure is repeated K-times, and the overall effectiveness ascertained by comparison of the predicted class with the known class.
Leave-one-out cross-validation: A commonly used variation of K-fold cross validation, in which K=n, where n is the number of samples.
Combinations of CCPMS, such as those described above in Tables 1 and 2, can be used to construct predictive models for prognosis.

Prognostic Signatures

Prognostic signatures, comprising one or more of these markers, can be used to determine the outcome of a patient, through application of one or more predictive models derived from the signature. In particular, a clinician or researcher can determine the differential expression (e.g., increased or decreased expression) of the one or more markers in the signature, apply a predictive model, and thereby predict the negative prognosis, e.g., likelihood of disease relapse, of a patient, or alternatively the likelihood of a positive prognosis (continued remission).
A set of prognostic signatures have been developed. In the first instance, there are two signatures developed by cross-comparison of predictive ability between two datasets: the set of microarray experiments encompassing the German colorectal cancer samples, and the set of microarray experiments encompassing the New Zealand samples (discussed in example 6). In the second instance there has been an exhaustive statistical search for effective signatures based solely on the German dataset (discussed in example 17).
As described in Example 6 below, a prognostic signature comprising 19 genes has been established from a set of colorectal samples from Germany (Table 4). Another prognostic signature, of 22 genes, has also been established from samples of colorectal tumours from patients in New Zealand (Table 3). By obtaining a patient sample (e.g., tumour sample), and matching the expression levels of one or more markers in the sample to the differential expression profile, the likelihood of the cancer recurring can be determined.

TABLE 3

New Zealand prognostic signature

WDR44	WD repeat domain 44	0.81	Hs.98510	NM_019045
RBMS1	rna binding motif, single stranded	1.27	Hs.470412	NM_016836
	interacting protein 1, isoform d
SACM1L	Ras-GTPase activating protein	0.84	Hs.156509	NM_014016
	SH3 domain-binding protein 2
SOAT1	sterol o-acyltransferase acyl-	1.21	Hs.496383	NM_003101
	coenzyme a: cholesterol
	acyltransferase 1
PBK	pdz-binding kinase	0.76	Hs.104741	NM_018492
G3BP2	ras-gtpase activating protein	0.86	Hs.303676	NM_012297
	sh3 domain-binding protein 2
ZBTB20	zinc finger and BTB domain	1.2	Hs.477166	NM_015642
	containing 20
ZNF410	zinc finger protein 410	0.84	Hs.270869	NM_021188
COMMD2	COMM domain containing 2	1.09	Hs.591315	NM_016094
PSMC1	proteasome (prosome, macropain)	0.79	Hs.356654	NM_002802
	26s subunit, atpase, 1
COX10	COX10 homolog, cytochrome c	0.9	Hs.462278	NM_001303
	oxidase assembly protein, heme A:
	farnesyltransferase (yeast)
GTF3C5	general transcription factor	0.84	Hs.495417	NM_012087
	iiic, polypeptide 5 (63 kd)
HMMR	hyaluronan-mediated motility	0.78	Hs.72550	NM_012485
	receptor (rhamm)
UBE2L3	ubiquitin-conjugating enzyme e2l 3	0.83	Hs.108104	NM_003347
GNAS	gnas complex locus	1.26	Hs.125898	NM_000516
PPP2R2A	protein phosphatase 2 (formerly 2a),	0.91	Hs.146339	NM_002717
	regulatory subunit b (pr 52),
	alpha isoform
RNASE2	ribonuclease, rnase a family, 2	0.83	Hs.728	NM_002934
	(liver, eosinophil-derived neurotoxin)
SCOC	short coiled-coil protein	0.78	Hs.480815	NM_032547
PSMD9	proteasome (prosome, macropain)	0.89	Hs.131151	NM_002813
	26s subunit, non-atpase, 9
EIF3S7	eukaryotic translation initiation	0.85	Hs.55682	NM_003753
	factor 3, subunit 7 (zeta, 66/67 kd)
ATP2B4	ATPase, Ca++ transporting,	1.11	Hs.343522	NM_001001396
	plasma membrane 4			NM_001684
ABCC9	atp-binding cassette, sub-family c,	0.9	Hs.446050	NM_020298
	member 9, isoform sur2a-delta-14

TABLE 4

German prognostic signature

		Expression
		fold difference
Gene		(relapse/	UniGene	GenBank
Symbol	Gene Description	non-relapse)	Cluster	Acc. No.

CXCL10	Chemokine (C-X-C motif)	0.87	Hs.413924	NM_001565
	ligand 10
FAS	FAS (TNF receptor	0.9	Hs.244139	NM_000043
	superfamily, member 6)			NM_152871
				NM_152872
				NM_152873
				NM_152874
				NM_152875
				NM_152876
				NM_152877
CXCL9	chemokine (C-X-C motif)	0.87	Hs.77367	NM_002416
	ligand 9
TLK1	tousled-like kinase 1	0.91	Hs.470586	NM_012290
CXCL11	chemokine (C-X-C motif)	0.75	Hs.518814	NM_005409
	ligand 11
PBK	T-LAK cell-originated	0.86	Hs.104741	NM_018492
	protein kinase
PSAT1	phosphoserine	0.91	Hs.494261	NM_021154
	aminotransferase 1
MAD2L1	MAD2 mitotic arrest	0.89	Hs.533185	NM_002358
	deficient-like 1 (yeast)
CA2	carbonic anhydrase II	0.84	Hs.155097	NM_000067
GZMB	granzyme B (granzyme 2,	0.9	Hs.1051	NM_004131
	cytotoxic T-lymphocyte-
	associated serine esterase 1)
SLC4A4	solute carrier family 4,	0.86	Hs.5462	NM_003759
	sodium bicarbonate
	cotransporter, member 4
DLG7	discs, large homolog 7	0.89	Hs.77695	NM_014750
	(Drosophila)
TNFRSF11A	tumor necrosis factor receptor	0.9	Hs.204044	NM_003839
	superfamily, member 11a,
	activator of NFKB
KITLG	KIT ligand	0.91	Hs.1048	NM_000899
INDO	indoleamine-pyrrole 2,3	0.91	Hs.840	NM_002164
	dioxygenase
GBP1	guanylate binding protein 1,	0.9	Hs.62661	NM_002053
	interferon-inducible, 67 kDa
CXCL13	chemokine (C-X-C motif)	0.86	Hs.100431	NM_006419
	ligand 13 (B-cell chemoattractant)
CLCA4	chloride channel, calcium	0.84	Hs.546343	NM_012128
	activated, family member 4
PCP4	Purkinje cell protein 4	1.14	Hs.80296	NM_006198

TABLE 5

Immune response genes

CXCL9	chemokine (C-X-C motif)	0.87	Hs.77367	NM_002416
	ligand 9
CXCL10	Chemokine (C-X-C motif)	0.87	Hs.413924	NM_001565
	ligand
10
CXCL11	chemokine (C-X-C motif)	0.75	Hs.518814	AF030514
	ligand 11
CXCL13	chemokine (C-X-C motif)	0.86	Hs.100431	NM_006419
	ligand 13 (B-cell chemoattractant)
PBK	T-LAK cell-originated	0.86	Hs.104741	NM_018492
	protein kinase
INDO	indoleamine-pyrrole 2,3	0.91	Hs.840	M34455
	dioxygenase
GBP1	guanylate binding protein 1,	0.9	Hs.62661	NM_002053
	interferon-inducible, 67 kDa
GZMB	granzyme B (granzyme 2,	0.9	Hs.1051	J03189
	cytotoxic T-lymphocyte-
	associated serine esterase 1)
KITLG	KIT ligand	0.91	Hs.1048	NM_000899
TNFRSF11A	tumor necrosis factor receptor	0.9	Hs.204044	NM_003839
	superfamily, member 11a,
	activator of NFKB
FAS	FAS (TNF receptor	0.9	Hs.244139	Z70519
	superfamily, member 6)

In certain aspects, this invention provides methods for determining the prognosis of a cancer, comprising: (a) providing a sample of the cancer; (b) detecting the expression level of a CCPM family member in said sample; and (c) determining the prognosis of the cancer. In one aspect, the cancer is colorectal cancer.
In other aspects, the invention includes a step of detecting the expression level of a CCPM mRNA. In other aspects, the invention includes a step of detecting the expression level of a CCPM polypeptide. In yet a further aspect, the invention includes a step of detecting the level of a CCPM peptide. In yet another aspect, the invention includes detecting the expression level of more than one CCPM family member in said sample. In a further aspect the CCPM is a gene associated with an immune response. In a further aspect the CCPM is selected from the markers set forth in Tables 3, 4, 8A, 8B, or 9. In a still further aspect, the CCPM is included in a signature selected from the signatures set forth in Tables 3, 4, 8A, 8B, or 9.
In a further aspect the invention comprises detecting the expression level of; WDR44, RBMS1, SACM1L, SOAT1, PBK, G3BP2, ZBTB20, ZNF410, COMMD2, PSMC1, COX10, GTF3C5, HMMR, UBE2L3, GNAS, PPP2R2A, RNASE2, SCOC PSMD9, EIF3S7, ATP2B4, and ABCC9. In a further aspect the invention comprises detecting the expression level of; CXCL10, FAS, CXCL9, TLK1, CXCL11, PBK, PSAT1, MAD2L1, CA2, GZMB, SLC4A4, DLG7, TNFRSF11A, KITLG, INDO, GBP1, CXCL13, CLCA4, and PCP4.
In still further aspects, the invention includes a method of determining a treatment regime for a cancer comprising: (a) providing a sample of the cancer; (b) detecting the expression level of a CCPM family member in said sample; (c) determining the prognosis of the cancer based on the expression level of a CCPM family member; and (d) determining the treatment regime according to the prognosis.
In still further aspects, the invention includes a device for detecting a CCPM, comprising: a substrate having a CCPM capture reagent thereon; and a detector associated with said substrate, said detector capable of detecting a CCPM associated with said capture reagent. Additional aspects include kits for detecting cancer, comprising: a substrate; a CCPM capture reagent; and instructions for use. Yet further aspects of the invention include method for detecting a CCPM using qPCR, comprising: a forward primer specific for said CCPM; a reverse primer specific for said CCPM; PCR reagents; a reaction vial; and instructions for use.
Additional aspects of this invention comprise a kit for detecting the presence of a CCPM polypeptide or peptide, comprising: a substrate having a capture agent for said CCPM polypeptide or peptide; an antibody specific for said CCPM polypeptide or peptide; a reagent capable of labeling bound antibody for said CCPM polypeptide or peptide; and instructions for use.
In yet further aspects, this invention includes a method for determining the prognosis of colorectal cancer, comprising the steps of: providing a tumour sample from a patient suspected of having colorectal cancer; measuring the presence of a CCPM polypeptide using an ELISA method. In specific aspects of this invention the CCPM of the invention is selected from the markers set forth in Tables 1, 2, 5, or 9. In still further aspects, the CCPM is included in a prognostic signature selected from the signatures set forth in Tables 3, 4, 8A, 8B, or 10.

EXAMPLES

The examples described herein are for purposes of illustrating embodiments of the invention. Other embodiments, methods, and types of analyses are within the scope of persons of ordinary skill in the molecular diagnostic arts and need not be described in detail hereon. Other embodiments within the scope of the art are considered to be part of this invention.

Example 1

Patients and Methods

Two cohorts of patients were included in this study, one set from New Zealand (NZ) and the second from Germany (DE). The NZ patients were part of a prospective cohort study that included all disease stages, whereas the DE samples were selected from a tumour bank. Clinical information is shown in Table 6, while FIG. 1 summarises the experimental design.

Example 2

Tumour Samples

Primary colorectal tumor samples from 149 NZ patients were obtained from patients undergoing surgery at Dunedin Hospital and Auckland Hospital between 1995-2000. Tumor samples were snap frozen in liquid nitrogen. All surgical specimens were reviewed by a single pathologist (H-S Y) and were estimated to contain an average of 85% tumor cells. Among the 149 CRC patients, 12 had metastatic disease at presentation, 35 developed recurrent disease, and 102 were disease-free after a minimum of 5-year follow up.
Primary colorectal tumor samples from DE patients were obtained from patients undergoing surgery at the Surgical Department of the Technical University of Munich between 1995-2001. A group of 55 colorectal carcinoma samples was selected from banked tumours which had been obtained fresh from surgery, snap frozen in liquid nitrogen. The samples were obtained from 11 patients with stage I cancer and 44 patients with stage II cancer. Twenty nine patients were recurrence-free and 26 patients had experienced disease recurrence after a minimum of 5-year follow up.
Tumor content ranged between 70 and 100% with an average of 87%.

TABLE 6

Clinical characteristics of New Zealand
and German colorectal tumours

	Relapse free	Relapse

New Zealand data

Number of patients	102	47
Age	68.5 (SD: 15.1)	69.8 (SD: 8.7)
Gender
male	48 (47%)	22 (47%)
female	54 (53%)	25 (53%)
Tumor localization
right colon	41 (40%)	18 (38%)
left colon	12 (12%)	4 (9%)
sigmoid	31 (30%)	17 (36%)
rectum	18 (18%)	8 (17%)
Tumor stage
Stage I	16	0
Stage II	61	13
Stage III	25	22
Stage IV	0	12¹
Median follow up	72 (range: 60-80)	15 (range: 0-59)
period/median
recurrence free
period (months)

German data

Number of patients	29	26
Age	64.3 (SD: 12.8)	61.8 (SD: 10.7)
Gender
male	17 (59%)	16 (62%)
female	12 (41%)	10 (38%)
Tumor localization
right colon	8 (28%)	4 (15%)
left colon	7 (24%)	5 (19%)
sigmoid	6 (21%)	7 (27%)
rectum	8 (28%)	10 (38%)
Tumor stage
Stage I	5	6
Stage II	24	20
Median follow up	83.1 (range: 64-99)	27.4 (range: 3-60)
period/median
recurrence free
period (months)

¹Persisting disease

Example 3

RNA Extraction and Target Labeling

NZ tumours: Tumours were homogenized and RNA was extracted using Tri-Reagent (Progenz, Auckland, New Zealand). The RNA was then further purified using RNeasy mini column (Qiagen, Victoria, Australia). Ten micrograms of RNA was labelled with Cy5 dUTP using the indirect amino-allyl cDNA labelling protocol.
A reference RNA from 12 different cell lines was labelled with Cy3 dUTP. The fluorescently labelled cDNA were purified using a QiaQuick PCR purification kit (Qiagen, Victoria, Australia) according to the manufacturer's protocol.
DE tumours: Tumours were homogenized and RNA was isolated using RNeasy Mini Kit (Qiagen, Hilden, Germany). cRNA preparation was performed as described previously (9), purified on RNeasy Columns (Qiagen, Hilden, Germany), and eluted in 55 μl of water. Fifteen micrograms of cRNA was fragmented for 35 minutes at 95° C. and double stranded cDNA was synthesized with a oligo-dT-T7 primer (Eurogentec, Köln, Germany) and transcribed using the Promega RiboMax T7-kit (Promega, Madison, Wis.) and Biotin-NTP labelling mix (Loxo, Dossenheim, Germany).

Example 4

Microarray Experiments

NZ tumours: Hybridisation of the labelled target cDNA was performed using MWG Human 30K Array oligonucleotides printed on epoxy coated slides. Slides were blocked with 1% BSA and the hybridisation was done in pre-hybridisation buffer at 42° C. for at least 12 hours followed by a high stringency wash. Slides were scanned with a GenePix Microarray Scanner and data was analyzed using GenePix Pro 4.1 Microarray Acquisition and Analysis Software (Axon, Calif.).
DE tumours: cRNA was mixed with B2-control oligonucleotide (Affymetrix, Santa Clara, Calif.), eukaryotic hybridization controls (Affymetrix, Santa Clara, Calif.), herring sperm (Promega, Madison, Wis.), buffer and BSA to a final volume of 300 μl and hybridized to one microarray chip (Affymetrix, Santa Clara, Calif.) for 16 hours at 45° C. Washing steps and incubation with streptavidin (Roche, Mannheim, Germany), biotinylated goat-anti streptavidin antibody (Serva, Heidelberg, Germany), goat-IgG (Sigma, Taufkirchen, Germany), and streptavidin-phycoerythrin (Molecular Probes, Leiden, Netherlands) was performed in an Affymetrix Fluidics Station according to the manufacturer's protocol. The arrays were then scanned with a HP-argon-ion laser confocal microscope and the digitized image data were processed using the Affymetrix® Microarray Suite 5.0 Software.

Example 5

Data Pre-Processing

NZ data: Data pre-processing and normalization was performed in the R computing environment (10). A log₂transformation was applied to the foreground intensities from each channel of each array. Data from each spot was used on a per array basis to perform print-tip loss normalization via the limma package (11) from the Bioconductor suite of analysis tools (12). Scale normalization (13) was then used to standardize the distribution of log intensity ratios across arrays. Post-normalization cluster analysis revealed the presence of a gene-specific print-run effect present in the data. Analysis of variance (ANOVA) normalization was used to estimate and remove print run effects from the data for each gene. Replicate array data was available for 46 of the 149 samples. Cluster analysis of the entire data set indicated that the duplicate arrays clustered well with each other suggesting internal consistency of the array platform. Genes with low intensity, large differences between replicates (mean log₂difference between duplicates higher than 0.5), and unknown proteins were removed from the data set. After the initial normalization procedure, a subset of 10,318 genes was chosen for further analysis.
DE data: All Affymetrix U133A GeneChips passed quality control to eliminate scans with abnormal characteristics, that is, abnormal low or high dynamic range, high perfect match saturation, high pixel noise, grid misalignment problems, and low mean signal to noise ratio. Background correction and normalization were performed in the R computing environment (10, 40). Background corrected and normalized expression measures from probe level data (cel-files) were obtained using the robust multi-array average function (14) implemented in the Bioconductor package affy.

Example 6

Prognostic Signatures and Cross Validation

Data analysis was performed using the BRB Array-Tools package (hypertext transfer protocol://linus.nci.nih.gov/BRB-ArrayTools.html). Gene selection was performed using a random variance model t-test. In the DE data, 318 genes were found to be differentially expressed when using a significance threshold of 0.001. As most of the differentially expressed genes exhibited relatively small changes in expression, a condition requiring the mean log₂fold change between the two classes to be higher than 1.1 was added to the gene selection process for the DE data. Gene-based prognostic signatures were produced using leave one out cross validation (LOOCV) in each of the NZ and DE data sets. To avoid the problem of over-fitting, both the gene selection and signature construction were performed during each LOOCV iteration. After LOOCV, the prediction rate was estimated by the fraction of samples correctly predicted. In order to find a gene set that could make the best prediction for unknown samples, different t-test thresholds using a random variance model were investigated in conjunction with six classification methods: compound covariate classifier (CCP), diagonal linear discriminant analysis (DLD), 3-nearest neighbours (3-NN), 1-nearest neighbours (1-NN), nearest centroid (NC), and support vector machines (SVM).
To establish the validity of the NZ and DE prognosis signatures, reciprocal validation was performed, with the NZ signature validated using the DE data set, and vice versa. To test the NZ genes, probes relating to the 22 genes from the NZ signature were identified in the DE data, and LOOCV was used to assess the performance of a signature for the DE samples, based only on these probes. Similarly, probes relating to the 19 genes in the DE signature were identified in the NZ data and LOOCV was used to assess the performance of a signature for the NZ samples. In both cases a significance threshold of 0.999 was used to ensure that all genes were used in each LOOCV iteration. Differences between the platforms (in particular, log-ratio data versus log-intensity data) meant that direct application of a prediction rule across data sets was not feasible. The consequence of this is that only the gene sets, and not the prediction rules used, can be generalized to new samples. The significance of the LOOCV prediction results was calculated by permuting the class labels of the samples and finding the proportion of times that the permuted data resulted in a higher LOOCV prediction rate than that obtained for the unpermuted data. All permutation analysis involved 2000 permutations, with small P-values indicating that prediction results were unlikely to be due to chance.

Example 7

Survival Analysis

Kaplan-Meier survival analysis for censored data was performed using the survival package within the R computing environment. Survival was defined to be “disease free survival” post surgery. For each analysis, survival curves were constructed, and the log-rank test (15) was used to assess the presence of significant differences between the curves for the two groups in question. Censoring was taken into account for both the NZ and DE data sets. For the disease-free survival data, right censoring prior to five years could only occur for non-recurrent patients as a result of either death, or the last clinical follow-up occurring at less than five years. Odds ratios and confidence intervals were produced using the epitools package for R.

Example 8

Identification of Markers Co-Expressed with Chemokine Ligands

Genes in the DE data which had a Pearson correlation coefficient greater than 0.75 with at least one of the four chemokines appearing in the predictor in the non-relapse group were selected for ontology analysis. Ontology was performed using DAVID (hypertext transfer protocol://appsl.niaid.nih.gov/david/).

Example 9

Results and Analysis

To identify robust prognostic signatures to predict disease relapse for CRC, two independent sets of samples from NZ and DE were used to generate array expression data sets from separate series of primary tumours with clinical follow-up of five or more years. After normalization, each data set was analyzed using the same statistical methods to generate a prognostic signature, which was then validated on the alternate series of patients. As such, the DE prognostic signature was validated on the NZ data set and the NZ prognostic signature was validated on the DE data set.

Example 10

Exhaustive Identification of Differentially Expressed Markers

DE Data Set: The BRB Array Tools class comparison procedure was used to detect probes exhibiting statistically significant differences in average intensity between relapse and non-relapse samples. The RVM (random variance model) was again used to produce p-values for each probe in the data set. In this second round, a total of 325 probes were found to be significantly differentially expressed between the two sample classes using an arbitrary significance threshold of 0.05. Note this selection of genes did not apply any fold-change threshold, and used a significance cut off of 0.05, rather than the threshold of 0.001 that was used in Example 6. The purpose of this less stringent threshold (p=0.05 instead of p=0.001) was to put forward a larger number of genes for construction of the second round of signatures (see example 17) These probes represent 270 unique genes (Table 1 and Table 2).
Explicitly, the test for significance (random variance model) comprises the following: generating a test statistic for each gene which was identical to that of a standard two sample t-test (45) except that the estimate of the pooled variance was obtained by representing the variance structure across all genes as an F-distribution, and then using the parameters, a and b, of this distribution (obtained via maximization of the empirical likelihood function) to form the following estimate of the pooled variance (see next page),
$s^{2} = \frac{(n - 2) s_{pooled}^{2} + 2 b^{- 1}}{(n - 2) + 2 a}$
where S²is the new estimate of the pooled variance, S² _pooledis the standard estimate of pooled variance (45), n is the number of samples, and a and b are the parameters of the F-distribution (46). Based on the t-statistic formed, a t-distribution with n−2+2a degrees of freedom was used to obtain a p-value for each gene. To adjust for multiple hypothesis testing, the False Discovery Rate controlling procedure of Benjamini and Hochberg (7) was used to produce adjusted p-values for each gene. A gene was considered to have undergone significant differential expression if its adjusted p-value was less than 0.05.

Example 11

Identification of Correlated Markers

In order to identify additional genes that can be used as prognostic predictors, correlation analysis was carried out using the R statistical computing software package. This analysis revealed 167 probes that had a Pearson correlation coefficient (40, 44, 45) of at least 0.8. Of these probes, 51 were already present in the set of 325 significantly differentially expressed probes, while the remaining 116 were reported as non-significant (using a 0.05 threshold for the FDR, or “false-discovery rate” (47) controlling procedure, the RVM, or rando variance model). These 116 probes represent 111 distinct genes (Table 2).

Example 12

Construction of Prognostic Signatures

The NZ data set was generated using oligonucleotide printed microarrays. Six different signatures were constructed, with a support vector machine (SVM) using a gene selection threshold of 0.0008 yielding the highest LOOCV prediction rate, and producing a 22-gene signature (77% prediction rate, 53% sensitivity, 88% specificity; p=0.002, Tables 7, 8A, and 8B). For Tables 8A and 8B, the gene descriptions are shown in Tables 3 and 4, respectively.

TABLE 7

Construction of prognostic signatures

Data set	Prediction rate	Sensitivity	Specificity	P value*	Odd ratio

22 gene NZ signature tested on German data

NZ data	0.77	0.53	0.88	0.002	8.4
(training; SVM)	(0.66, 0.86)^§	(0.33, 0.73)	(0.77, 0.95)		(3.5, 21.4)
NZ data minus 4 genes	0.72	0.38	0.87	0.011
not found in German data
were removed from NZ
data set (training; SVM)
German data (test; SVM)	0.71	0.62	0.79	0.002	5.9
	(0.51, 0.86)	(0.32, 0.86)	(0.52, 0.95)		(1.6, 24.5)

19 gene German signature tested on NZ data

German data	0.84	0.85	0.83	<0.0001	24.1
(training; 3-NN)	(0.65, 0.95)				(5.3, 144.7)
German data minus 5	0.67	0.65	0.66	0.046
genes not found in NZ
data were removed
from German data set
(training; 3-NN)
NZ data (test; 3-NN)	0.67	0.42	0.78	0.045	2.6
	(0.55, 0.78)	(0.22, 0.64)	(0.65, 0.89)		(1.2, 6.0)

SVM: support vector machine signature; 3-NN: 3 nearest neighbour signature.
^§95% confidence interval
*P values were calculated from 2,000 permutation of class labels

TABLE 8A

NZ prognostic signature
New Zealand 22-gene prognostic signature

	Gene	GenBank	Genes not found in German
p-value	Symbol	Acc. No.	data at time of analysis

2.30E−05	WDR44	NM_019045	*
3.30E−05	RBMS1	NM_016836
4.60E−05	SACM1L	NM_014016
6.80E−05	SOAT1	NM_003101
7.90E−05	PBK	NM_018492
0.00014	G3BP2	NM_012297
0.000163	ZBTB20	NM_015642
0.000214	ZNF410	NM_021188	*
0.00022	COMMD2	NM_016094	*
0.000293	PSMC1	NM_002802
0.000321	COX10	NM_001303
0.000334	GTF3C5	NM_012087
0.000367	HMMR	NM_012485
0.000405	UBE2L3	NM_003347
0.000417	GNAS	NM_000516
0.000467	PPP2R2A	NM_002717
0.000493	RNASE2	NM_002934
0.000532	SCOC	NM_032547	*
0.000578	PSMD9	NM_002813
0.000593	EIF3S7	NM_003753
0.000649	ATP2B4	NM_001001396
		NM_001684
0.000737	ABCC9	NM_020298

TABLE 8B

DE prognostic signature
German 19-gene prognostic signature

	Gene	GenBank	Genes not found in NZ
p-value	Symbol	Acc. No.	data at time of analysis

3.00E−06	CXCL10	NM_001565
4.00E−06	FAS	NM_000043
		NM_152871
		NM_152872
		NM_152873
		NM_152874
		NM_152875
		NM_152876
		NM_152877
8.00E−06	CXCL9	NM_002416	*
1.20E−05	TLK1	NM_012290
1.30E−05	CXCL11	NM_005409
2.10E−05	PBK	NM_018492
4.20E−05	PSAT1	NM_021154
7.60E−05	MAD2L1	NM_002358
9.80E−05	CA2	NM_000067
0.000128	GZMB	NM_004131	*
0.000177	SLC4A4	NM_003759
0.000215	DLG7	NM_014750	*
0.000376	TNFRSF11A	NM_003839
0.00038	KITLG	NM_000899
0.000579	INDO	NM_002164
0.000634	GBP1	NM_002053
0.000919	CXCL13	NM_006419	*
0.000942	CLCA4	NM_012128	*
0.001636	PCP4	NM_006198

The NZ signature had an odds ratio for disease recurrence in the NZ patients of 8.4 (95% CI 3.5-21.4).
The DE data set was generated using Affymetrix arrays resulting in a 19-gene (22-probe) and 3-nearest neighbour (3-NN) signature (selection threshold 0.002, log₂fold change>1.1, 84% classification rate, 85% sensitivity, 83% specificity, p<0.0001, Tables 3, 4, 7). The DE signature had an odds ratio for recurrence in the DE patients of 24.1 (95% CI 5.3-144.7). Using Kaplan-Meier analysis, disease-free survival in NZ and DE patients was significantly different for those predicted to recur or not recur (NZ signature, p<0.0001, FIG. 2A; DE signature, p<0.0001, FIG. 2B).

Example 13

External Validation of the NZ and DE Prognostic Signatures

To validate the NZ signature, the 22 genes were used to construct a SVM signature in the DE data set by LOOCV. A prediction rate of 71% was achieved, which was highly significant (p=0.002; Table 7). The odds ratio for recurrence in DE patients, using the NZ signature, was 5.9 (95% CI 1.6-24.5). We surmise that the reduction in prediction rate, from 77% in NZ patients to 71% in DE patients (Table 7), was due to four genes from the NZ signature not being present in the DE data. Disease-free survival for DE patients predicted to relapse, according to the NZ signature, was significantly lower than disease-free survival for patients predicted not to relapse (p=0.0049, FIG. 2C).
The DE signature was next validated by using the 19 genes to construct a 3-NN signature in the NZ data set by LOOCV. The prediction rate of 67% was again significant (p=0.046; Table 7), confirming the validity of the DE signature. The odds ratio for recurrence in NZ patients, using the DE signature, was 2.6 (95% CI 1.2-6.0). We consider that the reduction of the prediction rate was due to five genes from DE signature not being present in the NZ data set. This was confirmed when removal of these five genes from the DE data set resulted in a reduction of the LOOCV prediction rate from 84% to 67% (Table 7). Disease-free survival for NZ patients predicted to relapse, according to the DE signature, was significantly lower than disease-free survival for patients predicted not to relapse (p=0.029; FIG. 2D).

Example 14

Comparison of NZ and DE Prognostic Signatures with Current Staging System

Significant differences in disease-free survival between patients predicted to relapse or not relapse were also observed within the same clinico-pathological stage (FIG. 3). When patient predictions were stratified according to disease stage, the NZ signature was able to identify patients who were more likely to recur in both Stage II (p=0.0013, FIG. 3A), and Stage III subgroups (p=0.0295, FIG. 3A). This was mirrored to a lesser extent when the DE signature was applied to the NZ data set, where the difference was only observed for Stage III patients (p=0.0491, FIG. 3B). Again, the decreased predictive accuracy of the DE signature was likely due to the absence of five genes from the NZ data that decreased the LOOCV prediction rate.

Example 15

Genes in Signatures are Related to CRC Disease Progression

A number of genes in the NZ signature (Table 3) including G3BP2 (16), RBMS1 (17), HMMR (18), UBE2L3 (19), GNAS (20), RNASE2 (21) and ABCC9 (22) have all been reported to be involved in cancer progression, while RBMS1 (23), EIF3S7 (24) and GTF3C5 (25) are involved in transcription or translation. PBK is a protein kinase, which is involved in the process of mitosis (26), and the only gene common to the NZ and DE signatures. Eleven of 19 genes in the DE signature (Table 4) are involved in the immune response including 4 chemokine ligands (CXCL9, CXCL10, CXCL11, CXCL13; (27)), PBK (28), INDO (29), GBP1 (30), GZMB (31), KITLG (32), and two receptors of the tumor necrosis factor family (TNFRSF11A, FAS; 33)).
Eighty six genes were found to be moderately correlated (Pearson correlation coefficient >0.75) with at least one of the four chemokine ligands in the DE data. Ontology analysis found that 39 of these 65 genes were in the category of immune response (p<10⁻²⁶). This result suggests a key role for the host immune response in determining CRC recurrence.

Example 16

Discussion of NZ and DE Prognostic Signatures

It has been shown that the two different prognostic signatures can be used to improve the current prognosis of colorectal cancer.
For the DE signature, it was surprising and unexpected that the stage I/II samples could be used to predict stage III outcome. It was also surprising that many genes associated with recurrent disease are related to the immune response. The immune response has an important role in the progression of different cancers and T-lymphocyte infiltration in CRC patients is an indicator of good prognosis (36-38). All of the eleven immune response (Table 5) genes were down-regulated in recurrent patients which would be unexpected based on known biological mechanisms.
To further confirm these results, 4 chemokine genes were chosen for further analysis. Chemokine ligands not only reflect the activity of the immune system and mediate leukocyte recruitment but also are involved in chemotaxis, cell adhesion and motility, and angiogenesis (36). To investigate the role of the immune response genes, 86 genes co-expressed with the chemokine ligands were identified. Almost half of these genes had a Gene Ontology classification within the “immune response” category suggesting that the primary function of these genes in the recurrence process is the modulation of the immune response. Furthermore, CD4+ and CD8+T cell antigens (CD8A, CD3, PRF1, TRAa, TRBa) or functionally related antigens, for example, major histocompatibility molecules, interferon gamma induced proteins, and IL2RB, were found in the co-expressed gene list. The activation of tumor specific CD4+T cells and CD8+T cells has been shown to result in tumour rejection in a mouse colorectal cancer model (37). Collectively, these findings suggest that the lymphocytes form part of a tumor-specific host response involved in minimising the spread of cells from the primary tumour.

Example 17

Selection of Additional Prognostic Signatures

The performance of the two prognostic signatures described above was excellent in terms of cross-validation between the two data sets. Further studies were carried out, using a purely statistical approach, to develop a range of signatures, in addition to the aforementioned, that would also predict prognosis for other data sets. One of the additional goals of these studies was to ensure that the method used to normalize the microarray data (robust multi-array average) was not exerting undue influence on the choice of genes.
FIG. 4 shows the classification rates obtained from signatures of varying lengths. The classification rate is the proportion of correct relapse predictions (expressed as a percentage of total predictions), i.e., the proportion of samples correctly classified. The classification rates were determined using 11-fold cross validation. For this cross validation, a randomly selected stratified sample (i.e. same ratio of recurrent to non-recurrent tumours as the full data set) was removed as a validation set prior to gene selection of the genes, and model construction (using the training set of the remaining 50 samples). Cross-validation was then repeated a further ten times so that all 55 samples appeared in one validation set each. This 11-fold cross-validation process was repeated as 10 replicates, and the results plotted in FIG. 4 and FIG. 5. The classification rates shown were corrected using bootstrap bias correction (43), to give the expected classification rates for the signatures to be applied to another data set. From this analysis, it was ascertained that shorter signatures produced the best classification rate. In addition, analysis of the genes that most frequently appeared in classifiers show that the discriminatory power was mostly due to the effectiveness of two genes: FAS and ME2. This is illustrated most clearly by FIG. 5 shows the effectiveness of the signatures, once the two genes FAS and ME2 were removed from the data set. For more detail see the legend to FIG. 5.
The effect of normalization on feature selection was thoroughly investigated by generating gene lists from 1000 stratified sub-samples of the original set of tumours, each time removing 5 samples (i.e. 1/11 of the total number of samples) from the data set. (This is effectively the same as performing 11-fold cross-validation). A tally was made of the number of times each gene appeared in the “top-n” gene lists (i.e., top 10, top 20, top 100, and top 325). This value was termed the “top count”. Top counts were generated using three different normalization methods (40) (FIG. 6), and three different filtering statistics (FIG. 7). There was substantial correlation in the top count between normalization schemes and filtering statistics (41, 42) used. Thus, while normalization and feature selection methods were important, many genes appeared in the gene lists independently of the method used to pre-process the data. This indicates that the choice of normalization method had only a minimal effect on which genes were selected for use in signature construction. The top count, summed across all normalization methods and statistics, was found to be a robust measure of a gene's differential expression between recurrent and non-recurrent tumours.
Genes from the gene lists (see Table 1 and Table 2), were used to generate signatures by random sampling. The generation of samples was weighted, such that genes with higher “top count” were more likely to be selected. A range of signatures was generated, using between 2 and 55 Affymetrix probes. Signatures were selected if they exhibited >80% median classification rate, using three methods of classifiers: k-nearest neighbours, with k=1; k-nearest neighbours, with k=3; and support vector machines, with a linear kernel function, and using leave-one-out cross-validation.
On average, longer prognostic signatures were preferred over shorter signatures in terms of ability to predict prognosis for new data sets (FIG. 4 and FIG. 5). The genes FAS and ME2 were also important (discussed, above). These two facts were used, along with the fact that short signatures that do not contain either FAS or ME2 perform less effectively, to select candidate signatures as shown in Table 9, below. Signatures were selected (from the pool of randomly generated signatures) if they exhibited >80% median classification rate (using three methods of classifiers: k-nearest neighbours, with k=1; k-nearest neighbours, with k=3; and support vector machines, with a linear kernel function), using leave-one-out cross-validation.
In addition, because, on average, longer signatures (>10 genes/signature) tended to perform better, we selected signatures with 20 or more genes/signatures from a pool of signatures with 30 or more probes/signature. It is expected that these signatures (Table 10) will perform with a classification rate of around 70% when applied to other data sets, on the basis of the results shown in FIGS. 4 and 5. It was found that all of the signatures generated in this way contained both ME2, and all but one contained FAS, which may be due to the importance of these genes in providing prediction of prognosis. It was noted that the high classification rate obtained using this approach on the in-house data set did not necessarily mean that these signatures that would be expected to perform better than those set forth in Example 12, on other data sets. Rather, the purpose was to produce a range of signatures expected to apply to other data sets as least as well as the previous signatures. The markers comprising the prognostic signatures are set forth in Table 9.

TABLE 9

Additional Prognostic signatures (note SVM = support vector machine,
3NN = 3 nearest neighbours, 1NN = 1 nearest neighbour, Sens = sensitivity,
Spec = specificity, for prediction of recurrence)

Signature

SVM

3NN

1NN

Number	Signature Genes (as gene symbols)	Sens	Spec	Sens	Spec	Sens	Spec

1	WARS, STAT1, EIF4E, PRDX3, PSME2,	81%	86%	73%	90%	77%	83%
	GMFB, DLGAP4, TYMS, CTSS, MAD2L1,
	CXCL10, C1QBP, NDUFA9, SLC25A11,
	HNRPD, ME2, CXCL11, RBM25,
	CAMSAP1L1, hCAP-D3, BRRN1, ATP5A1,
	FAS, FLJ13220, PBK, BRIP1
2	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	77%	86%	85%	79%	81%	86%
	GMFB, DLGAP4, TYMS, LMAN1, CDC40,
	CXCL10, NDUFA9, SLC25A11, CA2, ME2,
	IFT20, TLK1, CXCL11, RBM25, AK2, FAS,
	FLJ13220, PBK, PSAT1, STAT1
3	WARS, SFRS2, PRDX3, GMFB, DLGAP4,	85%	86%	92%	76%	85%	79%
	TYMS, LMAN1, CDC40, CXCL10,
	NDUFA9, KPNB1, SLC25A11, CA2, ME2,
	FUT4, CXCL11, GZMB, RBM25, ATP5A1,
	CDC42BPA, FAS, RBBP4, HNRPD, BRIP1,
	STAT1
4	WARS, PRDX3, MTHFD2, PSME2, TES,	81%	79%	77%	69%	77%	79%
	DCK, CDC40, CXCL10, PLK4, NDUFA9,
	SLC25A11, WHSC1, ME2, CXCL11,
	SLC4A4, RBM25, ATP5A1, CDC42BPA,
	FAS, BAZ1A, AGPAT5, FLJ13220, HNRPD,
	KLHL24, STAT1
5	HNRPD, WARS, MTHFD2, GMFB,	88%	83%	88%	83%	88%	76%
	DLGAP4, TYMS, CXCL9, IRF8, GTSE1,
	RABIF, CXCL10, FAS, TRIM25, KITLG,
	C1QBP, SLC25A11, C17orf25, CA2, ME2,
	SLC4A4, CXCL11, RBM25, KLHL24,
	STAT1
6	HNRPD, WARS, STAT1, PRDX3,	73%	83%	81%	79%	65%	66%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, CXCL9, PLK4, KITLG, NDUFA9,
	ME2, CXCL11, SLC4A4, AK2, FAS,
	AGPAT5, FLJ13220, PBK, ETNK1
7	WARS, EIF4E, PRDX3, TK1, GMFB,	88%	90%	88%	90%	85%	86%
	DLGAP4, TYMS, LMAN1, ARF6, FAS,
	CHEK1, NDUFA9, SLC25A11, WHSC1,
	CA2, ME2, CXCL11, IFT20, SLC4A4,
	RBM25, hCAP-D3, CDC42BPA, FLJ13220,
	HNRPD, STAT1
8	WARS, EPAS1, EIF4E, PRDX3, PSME2,	77%	86%	85%	79%	77%	79%
	TK1, GMFB, DLGAP4, TYMS, DCK,
	CDC40, CXCL9, CXCL10, C1QBP,
	NDUFA9, SLC25A11, WHSC1, ME2, TLK1,
	RBM25, BRRN1, FAS, BRIP1, TRMT5,
	KLHL24, STAT1
9	HNRPD, WARS, PRDX3, MTHFD2,	69%	79%	85%	83%	77%	79%
	PSME2, GMFB, DLGAP4, TYMS, TES,
	CDC40, IRF8, CXCL10, FAS, CHEK1,
	KITLG, WHSC1, CA2, ME2, TLK1, RBM25,
	AK2, NUP210, ATP5A1, BRIP1 STAT1
10	HNRPD, EPAS1, EIF4E, PRDX3, DLGAP4,	85%	79%	85%	79%	77%	72%
	TES, CTSS, DCK, CXCL9, CXCL10, FAS,
	PLK4, HNRPA3P1, SLC25A11, C1QBP,
	C17orf25, CA2, ME2, RBM25, AK2,
	SEC10L1, FLJ13220, TRMT5, STAT1
11	HNRPD, WARS, EIF4E, PRDX3, PSME2,	85%	83%	92%	76%	85%	76%
	GBP1, GMFB, DLGAP4, TYMS, TES,
	RABIF, CXCL10, C1QBP, NDUFA9,
	SLC25A11, C17orf25, ME2, FUT4, CXCL11,
	RBM25, AK2, hCAP-D3, FAS, AGPAT5,
	SEC10L1, PBK, STAT1
12	HNRPD, MTHFD2, PSME2, GMFB,	88%	79%	92%	69%	92%	83%
	DLGAP4, TYMS, DCK, IRF8, NDUFA9,
	SLC25A11, C17orf25, CA2, ME2, CXCL11,
	GZMB, RBM25, NUP210, SOCS6, DDAH2,
	FAS, RBBP4, MARCH5, SEC10L1,
	KLHL24, STAT1
13	WARS, EPAS1, STAT1, MTHFD2, MCM6,	88%	90%	88%	76%	77%	69%
	GBP1, GMFB, DLGAP4, TYMS, ARF6,
	CXCL10, FAS, KITLG, NDUFA9, CA2,
	ME2, GZMB, CXCL11, RBM25, RBBP4,
	PBK, PSAT1, HNRPD
14	WARS, EPAS1, EIF4E, PRDX3, PSME2,	85%	83%	92%	76%	92%	79%
	GBP1, TK1, GMFB, TYMS, CXCL9, FAS,
	CHEK1, SLC25A11, NDUFA9, WHSC1,
	CA2, ME2, FUT4, CXCL11, RBM25,
	CAMSAP1L1, SFRS2, DDAH2, AGPAT5,
	HNRPD, BRIP1, ETNK1
15	SFRS2, EIF4E, PRDX3, MTHFD2, MCM6,	81%	83%	81%	83%	77%	79%
	TK1, GMFB, TYMS, TES, CTSS, ARF6,
	CXCL9, RABIF, CXCL10, FAS, KITLG,
	SLC25A11, ME2, IFT20, SLC4A4, CXCL11,
	RBM25, PSAT1, HNRPD, TRMT5, STAT1
16	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	92%	93%	81%	83%	81%	83%
	TYMS, LMAN1, CDC40, CXCL9, CXCL10,
	PLK4, CHEK1, SLC25A11, C1QBP,
	NDUFA9, ME2, IFT20, SLC4A4, CXCL11,
	RBM25, DDAH2, FAS, HNRPD, BRIP1,
	STAT1
17	WARS, EIF4E, GMFB, DLGAP4, TYMS,	92%	90%	85%	79%	81%	76%
	CTSS, MAD2L1, SLC4A4, CXCL9, IRF8,
	CXCL10, FAS, TRIM25, KPNB1,
	SLC25A11, HNRPD, ME2, CXCL11,
	RBM25, AK2, hCAP-D3, DDAH2, SEC10L1,
	ETNK1, STAT1
18	HNRPD, WARS, SFRS2, MTHFD2, PSME2,	81%	79%	85%	90%	81%	93%
	TK1, GMFB, DLGAP4, ARF6, CXCL10,
	TRIM25, NDUFA9, SLC25A11, WHSC1,
	ME2, CXCL11, TLK1, RBM25,
	CAMSAP1L1, hCAP-D3, CDC42BPA, FAS,
	AGPAT5, STAT1
19	HNRPD, WARS, SFRS2, STAT1, EIF4E,	96%	86%	73%	76%	73%	66%
	PSME2, TYMS, USP4, DCK, ARF6, CXCL9,
	RABIF, CXCL10, C1QBP, SLC25A11, ME2,
	IFT20, SLC4A4, CXCL11, RBM25, AK2,
	SOCS6, FAS, ETNK1
20	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	77%	79%	73%	83%	81%	86%
	PSME2, GMFB, TES, ARF6, CXCL10, FAS,
	KITLG, C1QBP, SLC25A11, C17orf25, ME2,
	FUT4, CXCL11, RBM25, ATP5A1,
	FLJ13220, PSAT1, HNRPD, STAT1
21	WARS, PSME2, GMFB, DLGAP4, USP4,	77%	72%	85%	83%	85%	79%
	ARF6, CDC40, CXCL9, IRF8, RABIF,
	CXCL10, PLK4, KITLG, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, ME2, TLK1,
	SLC4A4, RBM25, hCAP-D3, SOCS6, FAS,
	AGPAT5, SEC10L1, KLHL24, STAT1
22	WARS, MTHFD2, PSME2, GBP1, TK1,	77%	79%	77%	76%	81%	72%
	GMFB, DLGAP4, CXCL9, CXCL10,
	CHEK1, TRIM25, SLC25A11, C17orf25,
	HNRPD, ME2, SLC4A4, RBM25, AK2,
	BRRN1, FAS, DKFZp762E1312, SEC10L1,
	PBK, TRMT5, STAT1
23	HNRPD, WARS, STAT1, EIF4E, PRDX3,	85%	83%	92%	90%	85%	76%
	DLGAP4, TYMS, ARF6, CXCL9, CXCL10,
	FAS, HNRPA3P1, C1QBP, NDUFA9,
	SLC25A11, WHSC1, ME2, CXCL11,
	RBM25, MARCH5, SEC10L1, BRIP1
24	WARS, PRDX3, PSME2, GMFB, DLGAP4,	85%	83%	77%	69%	81%	69%
	CTSS, LMAN1, CXCL9, CXCL10,
	HNRPA3P1, SLC25A11, NDUFA9,
	C17orf25, ME2, FUT4, SLC4A4, RBM25,
	AK2, FAS, MARCH5, PBK, HNRPD,
	KLHL24, ETNK1, STAT1
25	WARS, PRDX3, MTHFD2, PSME2, GMFB,	81%	83%	77%	83%	81%	72%
	DLGAP4, TYMS, USP4, CDC40, CXCL9,
	CXCL10, TRIM25, NDUFA9, CA2, ME2,
	TLK1, CXCL11, SLC4A4, RBM25, AK2,
	ATP5A1, SOCS6, DDAH2, FAS, MARCH5,
	PBK, STAT1
26	WARS, EIF4E, MTHFD2, PSME2, GMFB,	81%	83%	92%	86%	81%	79%
	DLGAP4, TYMS, ARF6, CXCL10, PLK4,
	CHEK1, HNRPA3P1, C1QBP, NDUFA9,
	SLC25A11, WHSC1, CA2, ME2, CXCL11,
	RBM25, CAMSAP1L1, FAS, SEC10L1,
	FLJ13220, STAT1
27	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	85%	90%	85%	86%	81%	79%
	TK1, TYMS, LMAN1, CDC40, CXCL10,
	C1QBP, NDUFA9, KPNB1, CA2, ME2,
	GZMB, TLK1, SLC4A4, RBM25, ATP5A1,
	FAS, AGPAT5, SEC10L1, FLJ13220,
	HNRPD, STAT1
28	HNRPD, WARS, EPAS1, MTHFD2,	88%	86%	81%	86%	81%	76%
	PSME2, TK1, TYMS, CXCL9, CXCL10,
	FAS, TRIM25, KITLG, C1QBP, NDUFA9,
	CA2, ME2, CXCL11, RBM25, AK2, BRRN1,
	FLJ10534, SEC10L1, PBK, ETNK1, STAT1
29	EIF4E, PRDX3, PSME2, DLGAP4, CTSS,	88%	86%	88%	76%	77%	69%
	CXCL9, GTSE1, CXCL10, FAS, PLK4,
	KITLG, SLC25A11, CA2, ME2, GZMB,
	CXCL11, RBM25, AK2, AGPAT5,
	MARCH5, FLJ13220, PBK, HNRPD, STAT1
30	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	77%	79%	81%	79%	65%	69%
	PSME2, DLGAP4, TYMS, CTSS, CDC40,
	CXCL9, CXCL10, FAS, PLK4, NDUFA9,
	ME2, CXCL11, RBM25, AK2, BRRN1,
	RBBP4, HNRPD, KLHL24, ETNK1, STAT1
31	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	85%	83%	92%	76%	92%	72%
	GMFB, DLGAP4, TYMS, ARF6, CDC40,
	CXCL9, TRIM25, SLC25A11, CA2, ME2,
	IFT20, CXCL11, RBM25, BRRN1,
	CDC42BPA, FAS, AGPAT5, FLJ10534,
	HNRPD, TRMT5, STAT1
32	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	85%	79%	77%	83%	77%	72%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, CTSS, DCK, CXCL9, CXCL10, FAS,
	KITLG, NDUFA9, ME2, CXCL11, RBM25,
	ATP5A1, PBK, ETNK1, STAT1
33	WARS, SFRS2, MTHFD2, PSME2, MCM6,	73%	79%	92%	90%	88%	79%
	GMFB, DLGAP4, TYMS, LMAN1, CDC40,
	SLC4A4, CXCL10, FAS, CHEK1,
	SLC25A11, C1QBP, WHSC1, C17orf25,
	CA2, ME2, RBM25, SOCS6, AGPAT5,
	HNRPD, STAT1
34	HNRPD, WARS, MTHFD2, PSME2, GMFB,	85%	86%	92%	90%	81%	86%
	DLGAP4, RABIF, CXCL10, TRIM25,
	KITLG, C1QBP, KPNB1, SLC25A11,
	WHSC1, ME2, RBM25, CAMSAP1L1,
	BRRN1, CDC42BPA, FAS, AGPAT5,
	SEC10L1, ETNK1, STAT1
35	HNRPD, WARS, SFRS2, SFPQ, MTHFD2,	81%	83%	85%	79%	73%	79%
	DLGAP4, TYMS, USP4, LMAN1, ARF6,
	CDC40, C1QBP, C17orf25, CA2, ME2,
	CXCL11, SLC4A4, RBM25, AK2, ATP5A1,
	FAS, SEC10L1, FLJ13220, ETNK1, STAT1
36	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	85%	83%	85%	90%	88%	90%
	PSME2, GMFB, DLGAP4, LMAN1, ARF6,
	MAD2L1, GTSE1, CXCL10, FAS, KITLG,
	SLC25A11, WHSC1, ME2, FUT4, IFT20,
	RBM25, AGPAT5, HNRPD, STAT1
37	WARS, SFRS2, EIF4E, MTHFD2, TK1,	73%	79%	92%	83%	85%	86%
	GMFB, DLGAP4, TYMS, LMAN1,
	CXCL10, CHEK1, HNRPA3P1, C1QBP,
	NDUFA9, SLC25A11, ME2, CXCL11,
	RBM25, BRRN1, CDC42BPA, FAS,
	SEC10L1, PSAT1, HNRPD, KLHL24,
	STAT1
38	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	85%	86%	77%	90%	85%	90%
	GMFB, DLGAP4, TYMS, CTSS, LMAN1,
	DCK, CDC40, RABIF, CXCL10,
	HNRPA3P1, C1QBP, C17orf25, ME2,
	CXCL11, TLK1, RBM25, FAS, FLJ13220,
	HNRPD, KLHL24, STAT1
39	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	88%	83%	88%	79%	85%	72%
	GMFB, DLGAP4, TYMS, CTSS, SLC4A4,
	CXCL10, SLC25A11, C17orf25, HNRPD,
	ME2, CXCL11, RBM25, AK2, CDC42BPA,
	FAS, AGPAT5, SEC10L1, TRMT5, STAT1
40	SFRS2, EIF4E, PRDX3, PSME2, GMFB,	85%	93%	88%	83%	81%	69%
	DLGAP4, TYMS, CXCL9, IRF8, RABIF,
	CXCL10, FAS, TRIM25, SLC25A11,
	NDUFA9, ME2, CXCL11, RBM25,
	AGPAT5, FLJ13220, HNRPD, BRIP1,
	ETNK1, STAT1
41	HNRPD, WARS, EIF4E, PRDX3, TK1,	85%	83%	96%	79%	92%	72%
	DLGAP4, TYMS, CDC40, CXCL9, GTSE1,
	CXCL10, FAS, KITLG, SLC25A11,
	NDUFA9, ME2, IFT20, SLC4A4, RBM25,
	NUP210, BAZ1A, SEC10L1, TRMT5,
	KLHL24, STAT1
42	WARS, SFRS2, EIF4E, PRDX3, PSME2,	81%	79%	85%	83%	92%	69%
	DLGAP4, TYMS, CTSS, CXCL9, IRF8,
	CXCL10, FAS, C1QBP, NDUFA9, KPNB1,
	SLC25A11, ME2, SLC4A4, RBM25, SOCS6,
	MARCH5, SEC10L1, HNRPD, BRIP1,
	STAT1
43	WARS, EPAS1, PRDX3, PSME2, TK1,	77%	83%	88%	62%	92%	72%
	GMFB, DLGAP4, TYMS, CTSS, CDC40,
	CXCL9, CXCL10, SLC25A11, C1QBP,
	WHSC1, ME2, GZMB, RBM25, SFRS2,
	FAS, AGPAT5, SEC10L1, PSAT1, KLHL24,
	ETNK1, STAT1
44	WARS, PSME2, GMFB, DLGAP4, TYMS,	85%	86%	96%	79%	81%	83%
	CDC40, CXCL10, FAS, PLK4, C1QBP,
	NDUFA9, SLC25A11, CA2, ME2, CXCL11,
	IFT20, TLK1, RBM25, NUP210, BAZ1A,
	MARCH5, PSAT1, TRMT5, STAT1
45	WARS, PRDX3, MTHFD2, PSME2, TYMS,	88%	90%	85%	79%	88%	66%
	CXCL10, FAS, CHEK1, TRIM25, C1QBP,
	NDUFA9, C17orf25, CA2, ME2, CXCL11,
	IFT20, RBBP4, RBM25, AK2, CDC42BPA,
	AGPAT5, DKFZp762E1312, HNRPD,
	STAT1
46	WARS, SFRS2, EIF4E, SFPQ, PRDX3,	81%	79%	81%	79%	77%	72%
	MTHFD2, PSME2, DLGAP4, TYMS, USP4,
	CDC40, CXCL10, FAS, HNRPA3P1, KITLG,
	NDUFA9, KPNB1, SLC25A11, WHSC1,
	CA2, ME2, CXCL11, SLC4A4, RBM25,
	hCAP-D3, BRRN1, CDC42BPA, AGPAT5,
	MARCH5, SEC10L1, FLJ13220, BRIP1,
	ETNK1, STAT1
47	HNRPD, WARS, EIF4E, PRDX3, MTHFD2,	81%	83%	88%	86%	88%	69%
	PSME2, GMFB, DLGAP4, TYMS, CTSS,
	MAD2L1, CDC40, CXCL9, CXCL10,
	KITLG, NDUFA9, SLC25A11, WHSC1,
	C17orf25, CA2, ME2, SLC4A4, CXCL11,
	RBM25, AK2, ATP5A1, CDC42BPA, FAS,
	BAZ1A, AGPAT5, SEC10L1, BRIP1,
	TRMT5, STAT1
48	WARS, EIF4E, SFPQ, PRDX3, MTHFD2,	77%	83%	81%	79%	73%	69%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	ARF6, CXCL9, CXCL10, FAS, HNRPA3P1,
	C1QBP, NDUFA9, KPNB1, SLC25A11,
	ME2, CXCL11, IFT20, TLK1, RBM25,
	RBBP4, AGPAT5, MARCH5, SEC10L1,
	PBK, PSAT1, HNRPD, BRIP1, STAT1
49	HNRPD, WARS, SFRS2, EIF4E, SFPQ,	77%	83%	77%	79%	81%	83%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, TES, DCK, ARF6,
	CXCL9, CXCL10, HNRPA3P1, C1QBP,
	NDUFA9, SLC25A11, ME2, CXCL11,
	IFT20, TLK1, RBM25, AK2, hCAP-D3,
	ATP5A1, FAS, MARCH5, KLHL24, STAT1
50	WARS, STAT1, EIF4E, SFPQ, PRDX3,	81%	79%	85%	83%	77%	66%
	MTHFD2, TK1, GMFB, DLGAP4, TYMS,
	CTSS, CXCL9, IRF8, CXCL10, PLK4,
	TRIM25, C1QBP, NDUFA9, SLC25A11,
	C17orf25, ME2, SLC4A4, AK2,
	CAMSAP1L1, FAS, BAZ1A, MARCH5,
	FLJ13220, PBK, BRIP1, KLHL24, ETNK1
51	HNRPD, WARS, EIF4E, PRDX3, MTHFD2,	77%	79%	85%	79%	85%	72%
	GMFB, DLGAP4, TYMS, TES, ARF6,
	CXCL9, CXCL10, TRIM25, SLC25A11,
	NDUFA9, WHSC1, CA2, ME2, SLC4A4,
	CXCL11, RBM25, hCAP-D3, ATP5A1, FAS,
	RBBP4, SEC10L1, FLJ13220, PBK, BRIP1,
	KLHL24, ETNK1, STAT1
52	WARS, EPAS1, STAT1, EIF4E, MTHFD2,	77%	83%	81%	86%	69%	76%
	PSME2, GBP1, GMFB, DLGAP4, TYMS,
	DCK, CDC40, CXCL9, CXCL10, FAS,
	HNRPA3P1, SLC25A11, C1QBP, ME2,
	FUT4, CXCL11, SLC4A4, RBM25, AK2,
	CAMSAP1L1, SFRS2, DDAH2, RBBP4,
	AGPAT5, FLJ10534, DKFZp762E1312,
	PSAT1, HNRPD
53	HNRPD, WARS, SFRS2, SFPQ, PRDX3,	88%	83%	92%	79%	92%	72%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, LMAN1, CDC40, CXCL9, GTSE1,
	FAS, HNRPA3P1, SLC25A11, NDUFA9,
	KPNB1, CA2, ME2, CXCL11, SLC4A4,
	RBM25, BRRN1, CDC42BPA, RBBP4,
	BAZ1A, SEC10L1, BRIP1, KLHL24, STAT1
54	HNRPD, WARS, EPAS1, PAICS, EIF4E,	77%	79%	85%	83%	85%	79%
	PRDX3, MTHFD2, PSME2, MCM6, GMFB,
	DLGAP4, TYMS, USP4, LMAN1, MAD2L1,
	CDC40, SLC4A4, CXCL9, CXCL10, FAS,
	KITLG, C1QBP, SLC25A11, ME2, CXCL11,
	RBM25, AK2, CDC42BPA, SFRS2,
	SEC10L1, STAT1
55	WARS, EPAS1, STAT1, EIF4E, SFPQ,	88%	90%	88%	76%	88%	79%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, TES, CXCL9, IRF8, CXCL10, FAS,
	NDUFA9, C17orf25, CA2, HNRPD, ME2,
	CXCL11, IFT20, RBM25, CDC42BPA,
	FLJ10534, SEC10L1, PBK, BRIP1, TRMT5
56	SFRS2, PAICS, EIF4E, PRDX3, MTHFD2,	85%	79%	85%	79%	81%	86%
	PSME2, GMFB, DLGAP4, TYMS, TES,
	LMAN1, SLC4A4, CXCL9, CXCL10, FAS,
	PLK4, TRIM25, SLC25A11, NDUFA9,
	WHSC1, C17orf25, ME2, FUT4, CXCL11,
	IFT20, RBM25, ATP5A1, CDC42BPA,
	FLJ10534, SEC10L1, HNRPD, KLHL24,
	STAT1
57	SFRS2, PAICS, EIF4E, SFPQ, PRDX3,	81%	86%	85%	79%	85%	83%
	MTHFD2, PSME2, MCM6, GMFB,
	DLGAP4, TYMS, CTSS, LMAN1, SLC4A4,
	CXCL9, IRF8, CXCL10, TRIM25, NDUFA9,
	C17orf25, CA2, HNRPD, ME2, CXCL11,
	IFT20, RBM25, AK2, ATP5A1, FAS, PBK,
	BRIP1, TRMT5, ETNK1, STAT1
58	HNRPD, WARS, SFRS2, STAT1, EIF4E,	81%	76%	92%	79%	88%	72%
	MTHFD2, PSME2, DLGAP4, TYMS, DCK,
	CDC40, CXCL9, IRF8, CXCL10, PLK4,
	SLC25A11, NDUFA9, KPNB1, WHSC1,
	C17orf25, CA2, ME2, NUP210, SOCS6,
	CDC42BPA, FAS, AGPAT5, SEC10L1,
	FLJ13220, BRIP1, KLHL24, ETNK1
59	WARS, SFRS2, MTHFD2, PSME2, GMFB,	81%	79%	88%	86%	85%	83%
	DLGAP4, TYMS, CDC40, CXCL9, GTSE1,
	CXCL10, FAS, PLK4, TRIM25, SLC25A11,
	C1QBP, NDUFA9, KPNB1, WHSC1,
	C17orf25, CA2, ME2, CXCL11, TLK1,
	RBM25, BRRN1, AGPAT5, MARCH5,
	HNRPD, BRIP1, TRMT5, KLHL24, STAT1
60	HNRPD, WARS, SFRS2, EIF4E, SFPQ,	92%	79%	77%	86%	69%	76%
	MTHFD2, PSME2, MCM6, TK1, GMFB,
	DLGAP4, TYMS, LMAN1, CDC40, CXCL9,
	CXCL10, FAS, CHEK1, C1QBP, NDUFA9,
	SLC25A11, WHSC1, ME2, TLK1, CXCL11,
	RBM25, CDC42BPA, AGPAT5, FLJ10534,
	FLJ13220, PSAT1, STAT1
61	WARS, EPAS1, EIF4E, MTHFD2, PSME2,	77%	83%	85%	72%	85%	69%
	GMFB, DLGAP4, TYMS, TES, LMAN1,
	ARF6, CDC40, CXCL9, CXCL10, FAS,
	PLK4, TRIM25, C1QBP, C17orf25, CA2,
	ME2, CXCL11, SLC4A4, RBM25, AK2,
	ATP5A1, CDC42BPA, AGPAT5, FLJ10534,
	DKFZp762E1312, SEC10L1, PBK, PSAT1,
	STAT1
62	HNRPD, WARS, STAT1, EIF4E, SFPQ,	85%	76%	88%	83%	77%	69%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	TES, CXCL9, GTSE1, CXCL10, FAS,
	CHEK1, C1QBP, NDUFA9, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	SLC4A4, RBM25, CDC42BPA, DDAH2,
	AGPAT5, FLJ13220, PBK, TRMT5,
	KLHL24, ETNK1
63	WARS, EIF4E, PRDX3, PSME2, TK1,	81%	83%	65%	83%	73%	72%
	GMFB, DLGAP4, TYMS, USP4, DCK,
	MAD2L1, CXCL10, TRIM25, C1QBP,
	NDUFA9, SLC25A11, C17orf25, HNRPD,
	ME2, CXCL11, IFT20, RBBP4, TLK1,
	SLC4A4, RBM25, AK2, CAMSAP1L1,
	SOCS6, FAS, FLJ10534, FLJ13220, PBK,
	BRIP1, ETNK1, STAT1
64	WARS, SFRS2, EIF4E, SFPQ, PRDX3,	69%	79%	73%	83%	85%	83%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, LMAN1, CXCL9, IRF8, RABIF,
	CXCL10, CHEK1, NDUFA9, ME2, FUT4,
	CXCL11, SLC4A4, RBM25, AK2,
	CAMSAP1L1, FAS, RBBP4, MARCH5,
	SEC10L1, PBK, PSAT1, HNRPD, TRMT5,
	KLHL24, STAT1
65	HNRPD, WARS, SFPQ, MTHFD2, PSME2,	85%	72%	88%	79%	77%	72%
	GMFB, DLGAP4, CTSS, LMAN1, ARF6,
	CDC40, SLC4A4, CXCL9, CXCL10, FAS,
	CHEK1, KITLG, C1QBP, NDUFA9,
	SLC25A11, WHSC1, ME2, FUT4, GZMB,
	IFT20, RBM25, CAMSAP1L1, BAZ1A,
	AGPAT5, SEC10L1, PBK, KLHL24,
	ETNK1, STAT1
66	HNRPD, WARS, SFRS2, STAT1, PRDX3,	81%	76%	96%	69%	81%	66%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, LMAN1, ARF6, IRF8, RABIF,
	CXCL10, PLK4, HNRPA3P1, SLC25A11,
	C1QBP, CA2, ME2, GZMB, CXCL11,
	RBM25, NUP210, ATP5A1, DDAH2, FAS,
	PSAT1, BRIP1, TRMT5, KLHL24, ETNK1
67	WARS, EPAS1, STAT1, EIF4E, SFPQ,	77%	83%	92%	79%	77%	69%
	PSME2, GMFB, DLGAP4, TYMS, CTSS,
	DCK, SLC4A4, CXCL9, CXCL10, C1QBP,
	NDUFA9, SLC25A11, C17orf25, CA2, ME2,
	FUT4, CXCL11, RBM25, AK2, NUP210,
	CAMSAP1L1, FAS, AGPAT5, FLJ13220,
	PBK, HNRPD, ETNK1
68	HNRPD, WARS, SFRS2, EIF4E, PRDX3,	77%	76%	88%	79%	92%	79%
	MTHFD2, GMFB, TYMS, TES, CDC40,
	SLC4A4, CXCL9, CXCL10, PLK4,
	HNRPA3P1, SLC25A11, C1QBP, NDUFA9,
	C17orf25, CA2, ME2, CXCL11, RBM25,
	NUP210, hCAP-D3, SOCS6, FAS, SEC10L1,
	PBK, TRMT5, KLHL24, STAT1
69	HNRPD, WARS, EIF4E, PRDX3, MTHFD2,	81%	83%	92%	72%	77%	79%
	PSME2, GBP1, GMFB, DLGAP4, TYMS,
	TES, CTSS, CXCL9, CXCL10, FAS,
	CHEK1, C1QBP, NDUFA9, SLC25A11,
	CA2, ME2, GZMB, TLK1, CXCL11,
	RBM25, BRRN1, MARCH5, FLJ13220,
	PBK, TRMT5, KLHL24, ETNK1, STAT1
70	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	81%	79%	85%	83%	85%	79%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	USP4, TES, LMAN1, CDC40, CXCL9, IRF8,
	CXCL10, KITLG, NDUFA9, SLC25A11,
	WHSC1, CA2, ME2, CXCL11, RBM25,
	AK2, CAMSAP1L1, FAS, SEC10L1, PBK,
	BRIP1, TRMT5, STAT1
71	HNRPD, WARS, PAICS, EIF4E, MTHFD2,	85%	86%	88%	76%	81%	72%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	TES, CXCL9, CXCL10, FAS, TRIM25,
	C1QBP, SLC25A11, C17orf25, CA2, ME2,
	CXCL11, IFT20, RBBP4, RBM25, AK2,
	hCAP-D3, ATP5A1, BAZ1A, PBK, BRIP1,
	KLHL24, ETNK1, STAT1
72	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	81%	83%	85%	86%	88%	83%
	PSME2, MCM6, GMFB, TYMS, USP4,
	CXCL9, GTSE1, RABIF, CXCL10, FAS,
	PLK4, CHEK1, SLC25A11, C1QBP,
	NDUFA9, C17orf25, CA2, ME2, FUT4,
	IFT20, RBBP4, SLC4A4, CXCL11, RBM25,
	hCAP-D3, FLJ10534, MARCH5, HNRPD,
	TRMT5, STAT1
73	HNRPD WARS, EIF4E, PRDX3, PSME2,	73%	79%	81%	79%	77%	76%
	TK1, DLGAP4, TYMS, CTSS, LMAN1,
	ARF6, CXCL9, CXCL10, CHEK1, TRIM25,
	NDUFA9, KPNB1, SLC25A11, WHSC1,
	ME2, SLC4A4, RBM25, AK2, SFRS2,
	DDAH2, FAS, FLJ10534, MARCH5,
	FLJ13220, BRIP1, TRMT5, KLHL24,
	ETNK1, STAT1
74	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	92%	86%	81%	83%	88%	76%
	DLGAP4, TYMS, USP4, TES, MAD2L1,
	SLC4A4, CXCL9, CXCL10, CHEK1,
	HNRPA3P1, TRIM25, NDUFA9, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, IFT20,
	TLK1, CXCL11, RBM25, BRRN1, ATP5A1,
	FAS, AGPAT5, PBK, HNRPD, ETNK1,
	STAT1
75	HNRPD, WARS, MTHFD2, PSME2, GMFB,	85%	86%	88%	79%	85%	76%
	DLGAP4, TYMS, TES, LMAN1, CDC40,
	GTSE1, CXCL10, FAS, KITLG, C1QBP,
	NDUFA9, SLC25A11, CA2, ME2, CXCL11,
	GZMB, IFT20, TLK1, SLC4A4, RBM25,
	hCAP-D3, BRRN1, DDAH2, MARCH5,
	FLJ13220, PBK, BRIP1, KLHL24, STAT1
76	HNRPD, WARS, EIF4E, MTHFD2, PSME2,	85%	83%	88%	86%	85%	83%
	MCM6, GMFB, DLGAP4, TYMS, TES,
	CTSS, LMAN1, CDC40, SLC4A4, IRF8,
	GTSE1, CXCL10, CHEK1, HNRPA3P1,
	TRIM25, NDUFA9, WHSC1, CA2, ME2,
	CXCL11, RBM25, NUP210, ATP5A1,
	CDC42BPA, SFRS2, FAS, MARCH5,
	SEC10L1, BRIP1, STAT1
77	HNRPD, WARS, EPAS1, EIF4E, PRDX3,	96%	83%	92%	83%	88%	79%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, ARF6, SLC4A4, CXCL10, PLK4,
	CHEK1, HNRPA3P1, KPNB1, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	IFT20, RBBP4, TLK1, RBM25, CDC42BPA,
	SFRS2, FAS, AGPAT5, FLJ10534, SEC10L1,
	TRMT5, STAT1
78	WARS, SFRS2, STAT1, PAICS, EIF4E,	81%	83%	92%	76%	85%	76%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, LMAN1, MAD2L1,
	SLC4A4, CXCL9, CXCL10, SLC25A11,
	C17orf25, CA2, ME2, FUT4, GZMB,
	CXCL11, RBM25, CAMSAP1L1, BRRN1,
	CDC42BPA, FAS, FLJ10534, SEC10L1,
	PBK, TRMT5, KLHL24
79	HNRPD, WARS, SFRS2, PRDX3,	81%	72%	88%	79%	88%	69%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, USP4, TES, CXCL9, CXCL10, FAS,
	KITLG, C1QBP, NDUFA9, C17orf25, CA2,
	ME2, RBM25, SOCS6, CDC42BPA, BAZ1A,
	AGPAT5, DKFZp762E1312, SEC10L1,
	FLJ13220, PSAT1, BRIP1, TRMT5,
	KLHL24, STAT1
80	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	85%	86%	81%	69%	69%	69%
	PSME2, TK1, DLGAP4, TYMS, TES, CTSS,
	ARF6, CXCL9, CXCL10, FAS, HNRPA3P1,
	TRIM25, SLC25A11, C1QBP, NDUFA9,
	HNRPD, ME2, CXCL11, RBBP4, RBM25,
	AK2, AGPAT5, FLJ10534,
	DKFZp762E1312, SEC10L1, PBK, KLHL24,
	STAT1
81	EIF4E, SFPQ, MTHFD2, PSME2, GMFB,	81%	79%	85%	76%	81%	66%
	DLGAP4, TYMS, TES, CTSS, CXCL9,
	CXCL10, FAS, PLK4, NDUFA9, WHSC1,
	C17orf25, CA2, HNRPD, ME2, IFT20,
	RBM25, NUP210, CDC42BPA, DDAH2,
	BAZ1A, AGPAT5, FLJ10534,
	DKFZp762E1312, SEC10L1, FLJ13220,
	PBK, BRIP1, TRMT5, STAT1
82	WARS, SFRS2, STAT1, EIF4E, PRDX3,	81%	90%	85%	76%	85%	72%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, TES, LMAN1, DCK, CDC40,
	CXCL9, CXCL10, FAS, TRIM25, C1QBP,
	NDUFA9, SLC25A11, CA2, ME2, CXCL11,
	SLC4A4, RBM25, AK2, BRRN1, AGPAT5,
	DKFZp762E1312, FLJ13220, PBK
83	SFRS2, STAT1, EIF4E, PRDX3, MTHFD2,	65%	79%	77%	83%	77%	79%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	TES, CTSS, LMAN1, ARF6, CDC40, IRF8,
	CXCL10, CHEK1, C1QBP, SLC25A11,
	WHSC1, ME2, SLC4A4, CXCL11, RBM25,
	NUP210, FAS, FLJ10534, MARCH5,
	FLJ13220, PSAT1, HNRPD, BRIP1, TRMT5,
	KLHL24
84	HNRPD, WARS, SFRS2, EIF4E, PRDX3,	85%	83%	88%	76%	73%	72%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, CTSS, ARF6, MAD2L1, CXCL10,
	TRIM25, KITLG, NDUFA9, WHSC1, CA2,
	ME2, GZMB, IFT20, CXCL11, RBM25,
	FAS, AGPAT5, MARCH5, PSAT1, BRIP1,
	TRMT5, STAT1
85	HNRPD, SFRS2, STAT1, PRDX3,	88%	76%	92%	76%	81%	69%
	MTHFD2, PSME2, GMFB, DLGAP4, USP4,
	CTSS, ARF6, SLC4A4, CXCL9, RABIF,
	CXCL10, FAS, TRIM25, KITLG, C1QBP,
	SLC25A11, WHSC1, CA2, ME2, GZMB,
	RBBP4, CXCL11, RBM25, AGPAT5,
	MARCH5, SEC10L1, PBK, BRIP1, TRMT5
86	WARS, STAT1, EIF4E, MTHFD2, PSME2,	85%	76%	81%	83%	81%	76%
	DLGAP4, TYMS, USP4, LMAN1, CDC40,
	CXCL9, IRF8, CXCL10, PLK4, TRIM25,
	C1QBP, NDUFA9, SLC25A11, CA2, ME2,
	CXCL11, RBM25, ATP5A1, SFRS2, FAS,
	AGPAT5, MARCH5, FLJ13220, PBK,
	HNRPD, BRIP1, TRMT5, KLHL24, ETNK1
87	HNRPD, WARS, EPAS1, STAT1, EIF4E,	73%	79%	88%	83%	69%	72%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, SLC4A4, CXCL9, IRF8,
	GTSE1, RABIF, CXCL10, FAS, PLK4,
	HNRPA3P1, TRIM25, SLC25A11, C1QBP,
	NDUFA9, WHSC1, ME2, CXCL11, TLK1,
	RBM25, AK2, NUP210, BRRN1, ATP5A1,
	SFRS2, AGPAT5, FLJ10534, MARCH5,
	PSAT1, BRIP1, KLHL24
88	WARS, SFRS2, EPAS1, STAT1, EIF4E,	73%	83%	85%	79%	81%	72%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, LMAN1, MAD2L1,
	CDC40, CXCL9, IRF8, CXCL10, FAS,
	CHEK1, NDUFA9, KPNB1, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	IFT20, SLC4A4, RBM25, CDC42BPA,
	BAZ1A, AGPAT5, MARCH5, PBK, PSAT1,
	HNRPD, BRIP1, TRMT5, ETNK1
89	HNRPD, WARS, SFRS2, STAT1, EIF4E,	77%	76%	88%	79%	85%	66%
	PRDX3, MTHFD2, PSME2, GMFB, TYMS,
	USP4, CTSS, DCK, CDC40, SLC4A4,
	CXCL9, CXCL10, FAS, CHEK1, SLC25A11,
	C1QBP, NDUFA9, WHSC1, CA2, ME2,
	GZMB, RBBP4, RBM25, ATP5A1, SOCS6,
	AGPAT5, MARCH5, DKFZp762E1312,
	SEC10L1, PBK, BRIP1, TRMT5, KLHL24
90	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	77%	79%	88%	76%	88%	76%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	USP4, CTSS, SLC4A4, CXCL9, IRF8,
	GTSE1, CXCL10, PLK4, CHEK1,
	HNRPA3P1, KITLG, SLC25A11, C1QBP,
	NDUFA9, C17orf25, CA2, ME2, GZMB,
	CXCL11, RBM25, AK2, SOCS6, DDAH2,
	FAS, RBBP4, FLJ10534, MARCH5,
	DKFZp762E1312, PBK, HNRPD, BRIP1,
	KLHL24, STAT1
91	HNRPD, WARS, SFRS2, EPAS1, STAT1,	69%	83%	81%	79%	77%	76%
	EIF4E, SFPQ, PRDX3, MTHFD2, PSME2,
	GMFB, DLGAP4, TYMS, USP4, TES, DCK,
	ARF6, MAD2L1, CDC40, SLC4A4, CXCL9,
	RABIF, CXCL10, FAS, SLC25A11, C1QBP,
	NDUFA9, WHSC1, C17orf25, ME2, FUT4,
	CXCL11, IFT20, RBBP4, RBM25,
	CAMSAP1L1, SEC10L1, PBK, PSAT1,
	KLHL24
92	HNRPD, WARS, STAT1, EIF4E, MTHFD2,	77%	83%	92%	83%	77%	66%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	TES, CTSS, MAD2L1, SLC4A4, CXCL9,
	CXCL10, FAS, CHEK1, HNRPA3P1,
	SLC25A11, C1QBP, NDUFA9, WHSC1,
	CA2, ME2, GZMB, CXCL11, RBM25, AK2,
	CAMSAP1L1, DDAH2, BAZ1A, AGPAT5,
	SEC10L1, FLJ13220, PBK, BRIP1, TRMT5
93	HNRPD, WARS, SFRS2, EPAS1, STAT1,	73%	83%	77%	79%	77%	76%
	EIF4E, MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, TES, CTSS, DCK, MAD2L1,
	CDC40, RABIF, CXCL10, FAS, PLK4,
	KITLG, SLC25A11, NDUFA9, WHSC1,
	CA2, ME2, CXCL11, IFT20, TLK1, RBM25,
	CDC42BPA, DDAH2, RBBP4, MARCH5,
	DKFZp762E1312, PBK, PSAT1, BRIP1,
	KLHL24, ETNK1
94	HNRPD, WARS, STAT1, PAICS, EIF4E,	88%	83%	85%	76%	85%	69%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, USP4, TES, CTSS, DCK,
	ARF6, CDC40, CXCL9, IRF8, RABIF,
	CXCL10, FAS, HNRPA3P1, TRIM25,
	SLC25A11, NDUFA9, WHSC1, CA2, ME2,
	CXCL11, GZMB, IFT20, SLC4A4, SFRS2,
	AGPAT5, FLJ10534, MARCH5, PBK, BRIP1
95	WARS, SFRS2, STAT1, EIF4E, MTHFD2,	73%	79%	85%	83%	85%	79%
	PSME2, GMFB, DLGAP4, TYMS, TES,
	CTSS, LMAN1, DCK, MAD2L1, CDC40,
	SLC4A4, CXCL9, IRF8, CXCL10, FAS,
	C1QBP, NDUFA9, WHSC1, CA2, ME2,
	CXCL11, IFT20, RBM25, hCAP-D3,
	ATP5A1, DDAH2, FLJ10534, MARCH5,
	DKFZp762E1312, SEC10L1, PBK, HNRPD,
	BRIP1, TRMT5, KLHL24
96	HNRPD, WARS, SFRS2, EPAS1, STAT1,	85%	86%	92%	76%	77%	69%
	EIF4E, PRDX3, MTHFD2, PSME2, GBP1,
	TK1, GMFB, DLGAP4, TYMS, USP4,
	ARF6, CXCL9, CXCL10, FAS, PLK4,
	CHEK1, HNRPA3P1, SLC25A11, C1QBP,
	WHSC1, CA2, ME2, CXCL11, GZMB,
	IFT20, RBM25, NUP210, SOCS6, AGPAT5,
	MARCH5, SEC10L1, PBK, BRIP1, ETNK1
97	HNRPD, WARS, SFRS2, EPAS1, STAT1,	92%	90%	88%	76%	77%	66%
	EIF4E, MTHFD2, PSME2, MCM6, GMFB,
	DLGAP4, TYMS, TES, DCK, CDC40,
	SLC4A4, CXCL9, CXCL10, FAS, TRIM25,
	NDUFA9, SLC25A11, WHSC1, CA2, ME2,
	GZMB, IFT20, TLK1, CXCL11, RBM25,
	AK2, hCAP-D3, BRRN1, AGPAT5,
	MARCH5, FLJ13220, TRMT5, KLHL24
98	HNRPD, WARS, EIF4E, SFPQ, MTHFD2,	73%	76%	92%	83%	81%	83%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	DCK, CDC40, SLC4A4, CXCL9, GTSE1,
	CXCL10, FAS, PLK4, CHEK1, KITLG,
	SLC25A11, C1QBP, NDUFA9, KPNB1,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	TLK1, RBM25, NUP210, RBBP4, AGPAT5,
	MARCH5, SEC10L1, FLJ13220, PBK,
	TRMT5, KLHL24, ETNK1, STAT1
99	WARS, EPAS1, PRDX3, MTHFD2, GMFB,	85%	86%	92%	72%	77%	69%
	DLGAP4, TYMS, USP4, CTSS, CDC40,
	SLC4A4, CXCL9, IRF8, RABIF, CXCL10,
	FAS, HNRPA3P1, TRIM25, SLC25A11,
	NDUFA9, WHSC1, C17orf25, HNRPD,
	ME2, FUT4, CXCL11, GZMB, RBM25,
	AK2, ATP5A1, CDC42BPA, SFRS2,
	BAZ1A, AGPAT5, MARCH5, FLJ13220,
	BRIP1, KLHL24, ETNK1, STAT1
100	HNRPD, WARS, SFRS2, PAICS, PRDX3,	77%	79%	88%	83%	88%	76%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, LMAN1, ARF6, MAD2L1, CDC40,
	SLC4A4, CXCL9, IRF8, GTSE1, CXCL10,
	HNRPA3P1, SLC25A11, C1QBP, NDUFA9,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	RBM25, hCAP-D3, CDC42BPA, FAS,
	AGPAT5, FLJ10534, MARCH5,
	DKFZp762E1312, SEC10L1, PBK, BRIP1,
	TRMT5, ETNK1, STAT1
101	HNRPD, WARS, STAT1, PAICS, EIF4E,	73%	83%	88%	86%	85%	76%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, TES, ARF6, CXCL9,
	IRF8, CXCL10, FAS, PLK4, HNRPA3P1,
	TRIM25, C1QBP, NDUFA9, SLC25A11,
	WHSC1, C17orf25, ME2, CXCL11, IFT20,
	RBBP4, TLK1, SLC4A4, RBM25, AK2,
	NUP210, CAMSAP1L1, DDAH2, AGPAT5,
	MARCH5, SEC10L1, KLHL24, ETNK1
102	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	85%	86%	81%	83%	85%	79%
	PRDX3, MTHFD2, PSME2, DLGAP4,
	TYMS, USP4, CTSS, ARF6, CDC40,
	CXCL10, FAS, PLK4, TRIM25, KITLG,
	SLC25A11, C1QBP, NDUFA9, WHSC1,
	C17orf25, CA2, ME2, IFT20, RBBP4, TLK1,
	SLC4A4, CXCL11, RBM25, AK2, BAZ1A,
	MARCH5, SEC10L1, FLJ13220, PBK,
	BRIP1, KLHL24, STAT1
103	WARS, SFRS2, EIF4E, SFPQ, PRDX3,	81%	86%	85%	76%	77%	76%
	MTHFD2, PSME2, MCM6, TK1, GMFB,
	DLGAP4, TYMS, USP4, LMAN1, DCK,
	SLC4A4, CXCL9, CXCL10, FAS, PLK4,
	TRIM25, C1QBP, NDUFA9, SLC25A11,
	WHSC1, CA2, HNRPD, ME2, GZMB,
	IFT20, TLK1, CXCL11, RBM25, RBBP4,
	MARCH5, PBK, PSAT1, BRIP1, TRMT5,
	KLHL24, ETNK1, STAT1
104	HNRPD, WARS, SFRS2, EIF4E, MTHFD2,	85%	86%	88%	72%	77%	72%
	PSME2, MCM6, GMFB, DLGAP4, TYMS,
	USP4, LMAN1, ARF6, CDC40, CXCL9,
	GTSE1, CXCL10, FAS, CHEK1,
	HNRPA3P1, SLC25A11, C1QBP, WHSC1,
	CA2, ME2, GZMB, IFT20, SLC4A4,
	CXCL11, RBM25, BAZ1A, AUPAT5,
	SEC10L1, FLJ13220, PBK, PSAT1, BRIP1,
	TRMT5, ETNK1, STAT1
105	WARS, PAICS, EIF4E, MTHFD2, PSME2,	88%	86%	81%	83%	81%	83%
	MCM6, GMFB, DLGAP4, TYMS, CTSS,
	MAD2L1, CDC40, SLC4A4, CXCL9, IRF8,
	RABIF, CXCL10, FAS, CHEK1,
	HNRPA3P1, TRIM25, NDUFA9, SLC25A11,
	CA2, HNRPD, ME2, CXCL11, IFT20,
	RBM25, AK2, CAMSAP1L1, BRRN1,
	SFRS2, DDAH2, RBBP4, SEC10L1, PBK,
	PSAT1, BRIP1, TRMT5, KLHL24, STAT1
106	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	81%	90%	85%	83%	81%	76%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, TES, LMAN1, DCK,
	SLC4A4, CXCL9, CXCL10, PLK4,
	HNRPA3P1, C1QBP, NDUFA9, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	GZMB, IFT20, RBBP4, TLK1, RBM25,
	CAMSAP1L1, FAS, MARCH5,
	DKFZp762E1312, SEC10L1, PBK, STAT1
107	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	85%	83%	81%	86%	81%	72%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, MAD2L1, CDC40, SLC4A4, CXCL9,
	CXCL10, FAS, KITLG, C1QBP, NDUFA9,
	SLC25A11, ME2, CXCL11, IFT20, TLK1,
	RBM25, AK2, BRRN1, ATP5A1,
	CDC42BPA, RBBP4, AGPAT5, MARCH5,
	SEC10L1, PBK, HNRPD, BRIP1, TRMT5,
	ETNK1, STAT1
108	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	81%	83%	85%	69%	73%	79%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	TES, CTSS, LMAN1, CXCL9, GTSE1,
	RABIF, CXCL10, FAS, PLK4, SLC25A11,
	NDUFA9, KPNB1, HNRPD, ME2, FUT4,
	CXCL11, GZMB, IFT20, RBBP4, RBM25,
	CAMSAP1L1, hCAP-D3, SFRS2, DDAH2,
	AGPAT5, MARCH5, PBK, BRIP1, TRMT5,
	ETNK1, STAT1
109	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	77%	79%	88%	79%	77%	72%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, TES, CTSS, DCK, CDC40,
	RABIF, CXCL10, FAS, CHEK1,
	HNRPA3P1, TRIM25, KPNB1, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	TLK1, RBM25, ATP5A1, CDC42BPA,
	FLJ10534, MARCH5, DKFZp762E1312,
	SEC10L1, PBK, PSAT1, KLHL24, STAT1
110	HNRPD, WARS, SFRS2, STAT1, EIF4E,	73%	79%	85%	83%	88%	83%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, TES, ARF6, MAD2L1,
	CDC40, CXCL9, GTSE1, CXCL10, FAS,
	PLK4, CHEK1, HNRPA3P1, C1QBP,
	NDUFA9, SLC25A11, WHSC1, CA2, ME2,
	CXCL11, IFT20, TLK1, RBM25, ATP5A1,
	SOCS6, AGPAT5, SEC10L1, PBK, TRMT5,
	KLHL24
111	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	81%	90%	88%	83%	77%	76%
	PRDX3, MTHFD2, PSME2, GBP1, TK1,
	GMFB, DLGAP4, TYMS, TES, CTSS,
	MAD2L1, CXCL9, CXCL10, FAS, PLK4,
	CHEK1, SLC25A11, C1QBP, WHSC1,
	C17orf25, CA2, ME2, CXCL11, GZMB,
	TLK1, SLC4A4, RBM25, AK2, hCAP-D3,
	FLJ10534, SEC10L1, FLJ13220, PBK,
	BRIP1, KLHL24, STAT1
112	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	96%	90%	81%	76%	77%	76%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	TES, CTSS, MAD2L1, CXCL9, CXCL10,
	TRIM25, NDUFA9, KPNB1, SLC25A11,
	WHSC1, C17orf25, CA2, HNRPD, ME2,
	CXCL11, GZMB, TLK1, RBM25, AK2,
	CAMSAP1L1, BRRN1, CDC42BPA,
	DDAH2, FAS, MARCH5, SEC10L1, PBK,
	PSAT1, BRIP1, KLHL24, ETNK1, STAT1
113	HNRPD, WARS, SFRS2, STAT1, EIF4E,	65%	76%	88%	76%	85%	83%
	PRDX3, MTHFD2, PSME2, MCM6, GBP1,
	GMFB, DLGAP4, TYMS, USP4, LMAN1,
	DCK, ARF6, CDC40, CXCL9, CXCL10,
	FAS, PLK4, KITLG, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	FUT4, TLK1, CXCL11, SLC4A4, RBM25,
	AK2, ATP5A1, AGPAT5, FLJ10534,
	MARCH5, SEC10L1, PBK, PSAT1
114	HNRPD, WARS, SFRS2, STAT1, MTHFD2,	81%	76%	81%	79%	85%	62%
	PSME2, MCM6, TK1, GMFB, TYMS, USP4,
	LMAN1, ARF6, CXCL10, FAS, PLK4,
	SLC25A11, C1QBP, NDUFA9, WHSC1,
	C17orf25, CA2, ME2, GZMB, RBBP4,
	CXCL11, RBM25, AK2, BRRN1, ATP5A1,
	CDC42BPA, DDAH2, BAZ1A, AGPAT5,
	MARCH5, SEC10L1, PBK, BRIP1
115	HNRPD, WARS, EPAS1, STAT1, EIF4E,	81%	86%	81%	76%	81%	79%
	SFPQ, PRDX3, MTHFD2, PSME2, TK1,
	GMFB, DLGAP4, TYMS, TES, LMAN1,
	DCK, ARF6, CXCL9, IRF8, GTSE1,
	CXCL10, KITLG, NDUFA9, KPNB1,
	C17orf25, CA2, ME2, FUT4, CXCL11,
	GZMB, IFT20, TLK1, SLC4A4, RBM25,
	AK2, BRRN1, DDAH2, FAS, FLJ13220,
	PBK, PSAT1, BRIP1
116	WARS, SFRS2, EPAS1, PAICS, EIF4E,	81%	79%	73%	90%	73%	69%
	PRDX3, MTHFD2, PSME2, GBP1, TK1,
	GMFB, DLGAP4, TYMS, CTSS, ARF6,
	CDC40, CXCL9, CXCL10, FAS,
	HNRPA3P1, TRIM25, SLC25A11, NDUFA9,
	WHSC1, HNRPD, ME2, FUT4, CXCL11,
	SLC4A4, RBM25, CAMSAP1L1, hCAP-D3,
	DDAH2, MARCH5, FLJ13220, PBK, PSAT1,
	TRMT5, ETNK1, STAT1
117	WARS, SFRS2, EPAS1, EIF4E, SFPQ,	92%	90%	88%	79%	81%	72%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, USP4, CTSS, LMAN1,
	ARF6, MAD2L1, CDC40, SLC4A4, CXCL9,
	CXCL10, FAS, PLK4, HNRPA3P1, TRIM25,
	NDUFA9, SLC25A11, WHSC1, C17orf25,
	CA2, ME2, CXCL11, GZMB, IFT20, TLK1,
	RBM25, ATP5A1, RBBP4, AGPAT5,
	PSAT1, HNRPD, KLHL24, STAT1
118	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	77%	90%	88%	76%	73%	79%
	PSME2, GBP1, DLGAP4, TYMS, DCK,
	ARF6, MAD2L1, CDC40, CXCL9, IRF8,
	GTSE1, RABIF, CXCL10, FAS, CHEK1,
	TRIM25, C1QBP, NDUFA9, KPNB1,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	GZMB, IFT20, TLK1, CXCL11, RBM25,
	AK2, SFRS2, BAZ1A, SEC10L1, FLJ13220,
	PBK, PSAT1, HNRPD, BRIP1, KLHL24,
	STAT1
119	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	77%	76%	92%	83%	92%	76%
	SFPQ, PRDX3, MTHFD2, PSME2, GBP1,
	GMFB, DLGAP4, TYMS, DCK, CDC40,
	CXCL9, CXCL10, PLK4, CHEK1, KITLG,
	C1QBP, NDUFA9, KPNB1, SLC25A11,
	WHSC1, CA2, ME2, FUT4, CXCL11,
	RBM25, AK2, hCAP-D3, BRRN1, FAS,
	AGPAT5, FLJ10534, MARCH5, SEC10L1,
	PBK, TRMT5, KLHL24, ETNK1, STAT1
120	WARS, SFRS2, EPAS1, EIF4E, SFPQ,	81%	86%	88%	83%	85%	72%
	MTHFD2, PSME2, GMFB, TYMS, USP4,
	CTSS, LMAN1, DCK, MAD2L1, CDC40,
	SLC4A4, CXCL9, CXCL10, FAS, KITLG,
	SLC25A11, C1QBP, NDUFA9, CA2, ME2,
	IFT20, CXCL11, RBM25, AK2,
	CAMSAP1L1, hCAP-D3, ATP5A1,
	CDC42BPA, BAZ1A, AGPAT5, SEC10L1,
	PBK, HNRPD, BRIP1, KLHL24, STAT1
121	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	85%	90%	88%	90%	85%	76%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, LMAN1, MAD2L1, CDC40, CXCL9,
	CXCL10, CHEK1, TRIM25, SLC25A11,
	WHSC1, CA2, ME2, CXCL11, IFT20,
	RBBP4, SLC4A4, RBM25, AK2, NUP210,
	hCAP-D3, DDAH2, FAS, BAZ1A, FLJ10534,
	FLJ13220, PBK, BRIP1, TRMT5, ETNK1,
	STAT1
122	HNRPD, WARS, EPAS1, STAT1, EIF4E,	69%	76%	77%	86%	69%	69%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, TES, CTSS, LMAN1,
	CDC40, CXCL9, CXCL10, FAS, PLK4,
	KITLG, C1QBP, NDUFA9, SLC25A11,
	WHSC1, C17orf25, ME2, CXCL11, RBM25,
	hCAP-D3, BRRN1, ATP5A1, CDC42BPA,
	FLJ10534, MARCH5, SEC10L1, FLJ13220,
	PBK, BRIP1, TRMT5, KLHL24, ETNK1
123	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	73%	83%	85%	76%	81%	79%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, LMAN1, ARF6, CDC40,
	CXCL9, IRF8, CXCL10, FAS, PLK4,
	CHEK1, HNRPA3P1, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2,
	HNRPD, ME2, SLC4A4, CXCL11, RBM25,
	AK2, NUP210, AGPAT5, FLJ10534,
	MARCH5, DKFZp762E1312, PSAT1,
	BRIP1, TRMT5, STAT1
124	WARS, SFRS2, EPAS1, PAICS, EIF4E,	77%	76%	92%	76%	85%	72%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, CDC40, CXCL9, CXCL10, FAS,
	PLK4, HNRPA3P1, KITLG, C1QBP,
	NDUFA9, WHSC1, CA2, HNRPD, ME2,
	FUT4, CXCL11, GZMB, SLC4A4, RBM25,
	AK2, BRRN1, ATP5A1, AGPAT5,
	MARCH5, SEC10L1, FLJ13220, PBK,
	TRMT5, KLHL24, ETNK1, STAT1
125	WARS, SFRS2, EPAS1, STAT1, EIF4E,	85%	86%	92%	86%	88%	83%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, USP4, TES, CTSS,
	MAD2L1, CXCL9, IRF8, GTSE1, CXCL10,
	PLK4, CHEK1, TRIM25, NDUFA9,
	SLC25A11, C17orf25, CA2, HNRPD, ME2,
	CXCL11, IFT20, TLK1, RBM25, BRRN1,
	FAS, AGPAT5, FLJ10534, SEC10L1,
	FLJ13220, PBK, BRIP1, KLHL24
126	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	77%	83%	88%	86%	85%	72%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, USP4, TES, LMAN1,
	ARF6, MAD2L1, CXCL9, GTSE1, CXCL10,
	FAS, HNRPA3P1, NDUFA9, KPNB1,
	SLC25A11, CA2, ME2, CXCL11, TLK1,
	SLC4A4, RBM25, BRRN1, AGPAT5,
	MARCH5, DKFZp762E1312, SEC10L1,
	PBK, BRIP1, KLHL24, STAT1
127	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	73%	83%	73%	90%	73%	86%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	USP4, TES, LMAN1, CDC40, CXCL9, IRF8,
	CXCL10, PLK4, CHEK1, TRIM25, C1QBP,
	NDUFA9, SLC25A11, WHSC1, ME2, FUT4,
	CXCL11, TLK1, SLC4A4, RBM25, AK2,
	CAMSAP1L1, BRRN1, ATP5A1, SFRS2,
	FAS, SEC10L1, FLJ13220, PBK, PSAT1,
	TRMT5, KLHL24, STAT1
128	HNRPD, EIF4E, PRDX3, MTHFD2,	69%	83%	77%	83%	85%	76%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	USP4, DCK, ARF6, MAD2L1, CDC40,
	CXCL9, IRF8, CXCL10, FAS, CHEK1,
	SLC25A11, C1QBP, NDUFA9, WHSC1,
	CA2, ME2, CXCL11, TLK1, SLC4A4,
	RBM25, AK2, BRRN1 SOCS6, DDAH2,
	RBBP4, FLJ10534, MARCH5, FLJ13220,
	PBK, BRIP1, ETNK1, STAT1
129	WARS, SFRS2, EPAS1, STAT1, EIF4E,	73%	76%	92%	79%	85%	72%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, CTSS, LMAN1, DCK,
	CDC40, SLC4A4, CXCL9, IRF8, CXCL10,
	FAS, C1QBP, NDUFA9, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, RBM25,
	NUP210, CDC42BPA, AGPAT5, SEC10L1,
	FLJ13220, HNRPD, BRIP1, KLHL24,
	ETNK1
130	HNRPD, WARS, SFRS2, EPAS1, PAICS,	85%	83%	92%	72%	88%	76%
	EIF4E, SFPQ, PRDX3, MTHFD2, PSME2,
	GMFB, DLGAP4, TYMS, CTSS, CXCL9,
	IRF8, RABIF, CXCL10, FAS, PLK4,
	CHEK1, TRIM25, KITLG, SLC25A11,
	C1QBP, NDUFA9, CA2, ME2, CXCL11,
	RBBP4, SLC4A4, RBM25, AK2, AGPAT5,
	FLJ10534, FLJ13220, PBK, TRMT5,
	KLHL24, STAT1
131	WARS, SFRS2, PRDX3, MTHFD2, PSME2,	85%	83%	92%	86%	88%	79%
	MCM6, GMFB, DLGAP4, TYMS, CTSS,
	ARF6, CDC40, CXCL9, CXCL10, FAS,
	HNRPA3P1, TRIM25, KITLG, C1QBP,
	NDUFA9, KPNB1, SLC25A11, WHSC1,
	C17orf25, CA2, HNRPD, ME2, CXCL11,
	TLK1, SLC4A4, RBM25, AK2, hCAP-D3,
	BRRN1, SOCS6, DDAH2, RBBP4, AGPAT5,
	PBK, BRIP1, STAT1
132	HNRPD, WARS, SFRS2, EIF4E, MTHFD2,	77%	83%	88%	76%	85%	76%
	PSME2, MCM6, TK1, GMFB, DLGAP4,
	TYMS, USP4, CTSS, LMAN1, CDC40,
	CXCL9, CXCL10, PLK4, HNRPA3P1,
	C1QBP, NDUFA9, SLC25A11, WHSC1,
	CA2, ME2, CXCL11, GZMB, IFT20,
	SLC4A4, RBM25, AK2, ATP5A1, FAS,
	RBBP4, BAZ1A, MARCH5,
	DKFZp762E1312, SEC10L1, FLJ13220,
	PBK, TRMT5, KLHL24, STAT1
133	WARS, SFRS2, EPAS1, STAT1, EIF4E,	77%	83%	88%	76%	85%	79%
	PRDX3, MTHFD2, PSME2, MCM6, TK1,
	GMFB, DLGAP4, TYMS, TES, LMAN1,
	ARF6, CDC40, CXCL9, RABIF, CXCL10,
	FAS, PLK4, TRIM25, C1QBP, NDUFA9,
	SLC25A11, CA2, HNRPD, ME2, CXCL11,
	RBBP4, TLK1, RBM25, CDC42BPA,
	BAZ1A, AGPAT5, MARCH5, SEC10L1,
	FLJ13220, PBK, PSAT1, BRIP1
134	WARS, SFRS2, EPAS1, PAICS, EIF4E,	81%	86%	77%	93%	81%	79%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, CTSS, LMAN1, ARF6,
	MAD2L1, CDC40, IRF8, GTSE1, CXCL10,
	KITLG, C1QBP, NDUFA9, KPNB1,
	SLC25A11, WHSC1, ME2, CXCL11,
	RBBP4, TLK1, SLC4A4, RBM25, AK2,
	BRRN1, ATP5A1, CDC42BPA, DDAH2,
	FAS, MARCH5, SEC10L1, FLJ13220, PBK,
	HNRPD, BRIP1, STAT1
135	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	77%	90%	88%	72%	85%	79%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, TES, CTSS, LMAN1, DCK, CDC40,
	CXCL9, IRF8, CXCL10, FAS, PLK4,
	HNRPA3P1, C1QBP, NDUFA9, SLC25A11,
	WHSC1, CA2, ME2, FUT4, CXCL11,
	GZMB, SLC4A4, RBM25, AK2, ATP5A1,
	DDAH2, FLJ10534, PBK, HNRPD, BRIP1,
	ETNK1, STAT1
136	WARS, SFRS2, STAT1, PRDX3, MTHFD2,	81%	79%	85%	79%	81%	69%
	PSME2, MCM6, GMFB, DLGAP4, TYMS,
	TES, LMAN1, ARF6, CDC40, CXCL9,
	CXCL10, FAS, PLK4, HNRPA3P1, TRIM25,
	KITLG, SLC25A11, C1QBP, NDUFA9,
	KPNB1, C17orf25, CA2, ME2, IFT20,
	RBBP4, CXCL11, RBM25, AK2, hCAP-D3,
	ATP5A1, CDC42BPA, BAZ1A, AGPAT5,
	PBK, BRIP1, KLHL24
137	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	85%	83%	81%	83%	73%	72%
	MTHFD2, PSME2, MCM6, TK1, DLGAP4,
	TYMS, TES, LMAN1, ARF6, CDC40,
	CXCL9, CXCL10, FAS, KITLG, SLC25A11,
	C1QBP, NDUFA9, KPNB1, WHSC1, CA2,
	ME2, IFT20, RBBP4, TLK1, CXCL11,
	SLC4A4, RBM25, AK2, CDC42BPA,
	MARCH5, SEC10L1, FLJ13220, PBK,
	PSAT1, HNRPD, BRIP1, TRMT5, KLHL24,
	STAT1
138	WARS, SFRS2, EPAS1, STAT1, PAICS,	73%	76%	85%	83%	81%	76%
	EIF4E, PRDX3, MTHFD2, PSME2, MCM6,
	GMFB, DLGAP4, TYMS, USP4, CTSS,
	LMAN1, ARF6, CXCL9, IRF8, CXCL10,
	CHEK1, C1QBP, NDUFA9, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	SLC4A4, RBM25, AK2, BRRN1,
	CDC42BPA, FAS, BAZ1A, AGPAT5,
	FLJ10534, MARCH5, PBK, PSAT1, HNRPD,
	TRMT5, KLHL24
139	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	85%	76%	85%	79%	77%	69%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, LMAN1, ARF6, CXCL9,
	CXCL10, PLK4, HNRPA3P1, TRIM25,
	KITLG, C1QBP, NDUFA9, KPNB1,
	SLC25A11, WHSC1, C17orf25, HNRPD,
	ME2, FUT4, CXCL11, GZMB, RBM25,
	AK2, hCAP-D3, BRRN1, ATP5A1, FAS,
	AGPAT5, SEC10L1, FLJ13220, PSAT1,
	TRMT5, ETNK1, STAT1
140	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	81%	90%	85%	79%	81%	72%
	PRDX3, MTHFD2, PSME2, MCM6, GBP1,
	GMFB, DLGAP4, TYMS, TES, CTSS,
	LMAN1, SLC4A4, CXCL9, CXCL10, FAS,
	PLK4, CHEK1, TRIM25, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	GZMB, RBM25, hCAP-D3, ATP5A1,
	AGPAT5, FLJ10534, PBK, PSAT1, BRIP1,
	TRMT5, STAT1
141	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	85%	83%	88%	83%	73%	79%
	PSME2, MCM6, GMFB, DLGAP4, TYMS,
	USP4, MAD2L1, CDC40, CXCL9, IRF8,
	CXCL10, PLK4, HNRPA3P1, TRIM25,
	SLC25A11, NDUFA9, WHSC1, C17orf25,
	ME2, FUT4, CXCL11, IFT20, SLC4A4,
	RBM25, AK2, CAMSAP1L1, hCAP-D3,
	BRRN1, FAS, BAZ1A, AGPAT5, MARCH5,
	SEC10L1, FLJ13220, PSAT1, HNRPD,
	BRIP1, TRMT5, STAT1
142	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	77%	83%	81%	83%	85%	79%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	USP4, LMAN1, CDC40, SLC4A4, CXCL9,
	RABIF, CXCL10, PLK4, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2,
	HNRPD, ME2, CXCL11, IFT20, RBM25,
	hCAP-D3, ATP5A1, SOCS6, CDC42BPA,
	FAS, RBBP4, BAZ1A, DKFZp762E1312,
	SEC10L1, FLJ13220, PBK, PSAT1, BRIP1,
	STAT1
143	HNRPD, WARS, STAT1, EIF4E, PRDX3,	73%	72%	88%	79%	92%	76%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, USP4, TES, CTSS, CDC40, CXCL9,
	IRF8, CXCL10, PLK4, HNRPA3P1, KITLG,
	NDUFA9, KPNB1, SLC25A11, WHSC1,
	C17orf25, CA2, ME2, FUT4, CXCL11,
	SLC4A4, RBM25, hCAP-D3, DDAH2, FAS,
	RBBP4, AGPAT5, FLJ13220, PBK, BRIP1,
	TRMT5, KLHL24
144	WARS, SFRS2, MTHFD2, PSME2, GMFB,	73%	79%	85%	79%	69%	76%
	DLGAP4, TYMS, USP4, TES, CDC40,
	CXCL9, CXCL10, FAS, CHEK1, NDUFA9,
	KPNB1, WHSC1, CA2, ME2, GZMB, TLK1,
	RBM25, AK2, CAMSAP1L1, hCAP-D3,
	FLJ10534, DKFZp762E1312, FLJ13220,
	HNRPD, STAT1
145	HNRPD, WARS, SFRS2, EIF4E, MTHFD2,	77%	79%	81%	86%	81%	83%
	PSME2, GMFB, DLGAP4, TYMS, LMAN1,
	DCK, ARF6, CDC40, CXCL9, CXCL10,
	PLK4, TRIM25, C1QBP, KPNB1,
	SLC25A11, C17orf25, ME2, CXCL11,
	RBM25, hCAP-D3, DDAH2, FAS,
	MARCH5, STAT1
146	WARS, STAT1, EIF4E, MTHFD2, PSME2,	81%	79%	88%	79%	85%	69%
	DLGAP4, TYMS, ARF6, CXCL9, CXCL10,
	KITLG, C1QBP, NDUFA9, SLC25A11,
	WHSC1, C17orf25, CA2, HNRPD, ME2,
	CXCL11, SLC4A4, RBM25, hCAP-D3,
	SOCS6, CDC42BPA, FAS
147	HNRPD, WARS, EPAS1, EIF4E, MTHFD2,	88%	83%	92%	83%	85%	83%
	PSME2, GMFB, DLGAP4, TYMS, ARF6,
	CDC40, SLC4A4, CXCL9, CXCL10,
	HNRPA3P1, NDUFA9, SLC25A11, CA2,
	ME2, TLK1, CXCL11, RBM25, ATP5A1,
	SFRS2, FAS, MARCH5, SEC10L1, PBK,
	TRMT5, STAT1
148	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	73%	83%	88%	79%	85%	72%
	PSME2, GMFB, TYMS, TES, LMAN1,
	ARF6, CXCL9, CXCL10, FAS, HNRPA3P1,
	C1QBP, NDUFA9, SLC25A11, WHSC1,
	C17orf25, CA2, ME2, CXCL11, RBM25,
	SEC10L1, HNRPD, KLHL24, ETNK1,
	STAT1
149	WARS, EIF4E, MTHFD2, PSME2, GBP1,	77%	79%	85%	76%	88%	79%
	GMFB, DLGAP4, TYMS, USP4, LMAN1,
	ARF6, MAD2L1, CDC40, CXCL10,
	HNRPA3P1, NDUFA9, C17orf25, ME2,
	CXCL11, SLC4A4, RBM25, AK2,
	CDC42BPA, DDAH2, FAS, RBBP4, BAZ1A,
	AGPAT5, HNRPD, BRIP1, TRMT5, STAT1
150	WARS, SFRS2, EIF4E, PRDX3, PSME2,	85%	83%	88%	86%	85%	79%
	GMFB, DLGAP4, CXCL9, IRF8, CXCL10,
	FAS, PLK4, CHEK1, TRIM25, KITLG,
	C1QBP, NDUFA9, SLC25A11, WHSC1,
	C17orf25, CA2, ME2, CXCL11, RBM25,
	FLJ10534, SEC10L1, BRIP1, TRMT5,
	STAT1
151	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	100%	97%	85%	86%	81%	72%
	GMFB, DLGAP4, TYMS, CTSS, DCK,
	SLC4A4, CXCL9, CXCL10, FAS, TRIM25,
	SLC25A11, C1QBP, NDUFA9, WHSC1,
	CA2, ME2, CXCL11, TLK1, RBM25, AK2,
	CDC42BPA, SEC10L1, FLJ13220, KLHL24,
	STAT1
152	WARS, STAT1, MTHFD2, PSME2, GMFB,	85%	90%	81%	86%	65%	86%
	DLGAP4, TYMS, DCK, MAD2L1, CDC40,
	CXCL9, IRF8, RABIF, CXCL10, KITLG,
	SLC25A11, NDUFA9, ME2, IFT20, TLK1,
	CXCL11, RBM25, AK2, FAS, AGPAT5,
	DKFZp762E1312, SEC10L1, PSAT1,
	HNRPD, TRMT5
153	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	69%	86%	85%	86%	88%	79%
	GMFB, DLGAP4, TYMS, DCK, CDC40,
	CXCL9, CXCL10, FAS, PLK4, CHEK1,
	C1QBP, SLC25A11, CA2, ME2, FUT4,
	IFT20, SLC4A4, RBM25, SFRS2, DDAH2,
	PBK, HNRPD, KLHL24, ETNK1, STAT1
154	HNRPD, WARS, STAT1, EIF4E, PRDX3,	88%	83%	81%	83%	85%	72%
	PSME2, GMFB, DLGAP4, TYMS, TES,
	MAD2L1, CXCL9, IRF8, CXCL10,
	HNRPA3P1, C1QBP, NDUFA9, SLC25A11,
	ME2, FUT4, IFT20, hCAP-D3, SOCS6,
	DDAH2, FAS, BAZ1A, PBK, KLHL24
155	SFRS2, EPAS1, EIF4E, PRDX3, PSME2,	92%	83%	88%	83%	77%	72%
	GMFB, TYMS, TES, LMAN1, SLC4A4,
	CXCL9, GTSE1, CXCL10, C1QBP,
	NDUFA9, SLC25A11, CA2, ME2, TLK1,
	RBM25, CDC42BPA, FAS, FLJ10534,
	MARCH5, SEC10L1, PBK, HNRPD,
	TRMT5, KLHL24, ETNK1, STAT1
156	WARS, STAT1, EIF4E, PRDX3, MTHFD2,	81%	83%	88%	79%	92%	79%
	GMFB, DLGAP4, TYMS, USP4, ARF6,
	CDC40, CXCL9, IRF8, CXCL10, FAS,
	PLK4, HNRPA3P1, KITLG, C1QBP,
	SLC25A11, ME2, FUT4, RBM25, DDAH2,
	RBBP4, AGPAT5, PBK, HNRPD, TRMT5,
	KLHL24
157	HNRPD, WARS, SFPQ, MTHFD2, PSME2,	92%	86%	85%	69%	85%	69%
	GMFB, DLGAP4, TYMS, USP4, SLC4A4,
	CXCL9, CXCL10, FAS, HNRPA3P1,
	KITLG, SLC25A11, NDUFA9, CA2, ME2,
	IFT20, CXCL11, RBM25, BAZ1A, AGPAT5,
	SEC10L1, PBK, BRIP1, STAT1
158	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	69%	83%	92%	86%	88%	83%
	GMFB, DLGAP4, TYMS, ARF6, CXCL9,
	IRF8, CXCL10, PLK4, TRIM25, NDUFA9,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	RBBP4, TLK1, SLC4A4, RBM25, NUP210,
	FAS, AGPAT5, MARCH5, SEC10L1,
	HNRPD, STAT1
159	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	77%	76%	88%	79%	85%	66%
	PSME2, GBP1, GMFB, DLGAP4, TYMS,
	LMAN1, ARF6, CDC40, CXCL9, CXCL10,
	CA2, HNRPD, ME2, CXCL11, SLC4A4,
	RBM25, CDC42BPA, FAS, BAZ1A,
	AGPAT5, FLJ13220, BRIP1, KLHL24,
	STAT1
160	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	77%	76%	77%	83%	77%	79%
	PSME2, TK1, GMFB, DLGAP4, LMAN1,
	ARF6, CDC40, CXCL9, CXCL10, PLK4,
	NDUFA9, C17orf25, ME2, CXCL11,
	SLC4A4, RBM25, FAS, BAZ1A,
	DKFZp762E1312, SEC10L1, PBK, PSAT1,
	HNRPD, STAT1
161	EIF4E, PSME2, GMFB, DLGAP4, TYMS,	92%	86%	85%	79%	88%	72%
	DCK, CDC40, CXCL9, CXCL10, FAS,
	TRIM25, KITLG, NDUFA9, SLC25A11,
	WHSC1, C17orf25, HNRPD, ME2, CXCL11,
	IFT20, SLC4A4, RBM25, AK2, AGPAT5,
	MARCH5, SEC10L1, FLJ13220, KLHL24,
	STAT1
162	HNRPD, WARS, EPAS1, EIF4E, PRDX3,	81%	79%	85%	72%	85%	76%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	CTSS, CDC40, CXCL10, C1QBP,
	SLC25A11, C17orf25, ME2, CXCL11,
	SLC4A4, RBM25, CAMSAP1L1,
	CDC42BPA, FAS, MARCH5, SEC10L1,
	FLJ13220, PBK, BRIP1, KLHL24, STAT1
163	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	69%	86%	81%	83%	81%	79%
	TK1, DLGAP4, TYMS, USP4, TES, DCK,
	CDC40, CXCL10, CHEK1, HNRPA3P1,
	NDUFA9, SLC25A11, WHSC1, C17orf25,
	CA2, ME2, RBBP4, SLC4A4, RBM25, FAS,
	SEC10L1, FLJ13220, BRIP1, TRMT5,
	STAT1
164	HNRPD, WARS, MTHFD2, TK1, GMFB,	81%	83%	92%	79%	81%	83%
	DLGAP4, TYMS, LMAN1, CDC40, GTSE1,
	CXCL10, CHEK1, NDUFA9, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, FUT4,
	CXCL11, RBBP4, RBM25, AK2, BRRN1,
	FAS, AGPAT5, MARCH5, PBK, BRIP1,
	STAT1
165	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	73%	83%	88%	79%	88%	76%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	DCK, CXCL9, CXCL10, SLC25A11,
	C1QBP, NDUFA9, KPNB1, WHSC1, ME2,
	CXCL11, SLC4A4, RBM25, CDC42BPA,
	FAS, AGPAT5, SEC10L1, HNRPD, BRIP1,
	TRMT5, STAT1
166	WARS, EIF4E, MTHFD2, PSME2, GMFB,	73%	76%	81%	83%	77%	76%
	TYMS, TES, CDC40, IRF8, RABIF,
	CXCL10, PLK4, TRIM25, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, TLK1,
	CXCL11, SLC4A4, RBM25, CDC42BPA,
	FAS, RBBP4, SEC10L1, PBK, HNRPD,
	BRIP1, TRMT5, STAT1
167	WARS, SFRS2, MTHFD2, PSME2, TK1,	88%	93%	85%	76%	88%	72%
	DLGAP4, TYMS, DCK, CDC40, CXCL9,
	CXCL10, FAS, CHEK1, TRIM25, C1QBP,
	SLC25A11, WHSC1, CA2, ME2, CXCL11,
	GZMB, IFT20, SLC4A4, RBM25, hCAP-D3,
	DDAH2, SEC10L1, FLJ13220, PBK,
	KLHL24, STAT1
168	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	73%	79%	81%	86%	85%	76%
	MCM6, GMFB, DLGAP4, TYMS, LMAN1,
	DCK, CDC40, CXCL9, CXCL10, FAS,
	NDUFA9, WHSC1, HNRPD, ME2, SLC4A4,
	CXCL11, RBM25, NUP210, hCAP-D3,
	SEC10L1, PSAT1, KLHL24, STAT1
169	SFRS2, EIF4E, PRDX3, MTHFD2, GMFB,	73%	79%	85%	86%	88%	76%
	DLGAP4, TYMS, USP4, LMAN1, DCK,
	ARF6, CDC40, CXCL9, RABIF, CXCL10,
	KITLG, C1QBP, SLC25A11, C17orf25, CA2,
	ME2, CXCL11, SLC4A4, RBM25,
	CAMSAP1L1, FAS, HNRPD, BRIP1, STAT1
170	WARS, SFRS2, PAICS, EIF4E, PSME2,	85%	83%	88%	83%	77%	76%
	GMFB, DLGAP4, TYMS, ARF6, MAD2L1,
	SLC4A4, CXCL9, IRF8, CXCL10, FAS,
	NDUFA9, WHSC1, CA2, ME2, CXCL11,
	TLK1, RBM25, AK2, AGPAT5, MARCH5,
	FLJ13220, TRMT5, STAT1
171	SFRS2, EPAS1, EIF4E, MTHFD2, GBP1,	88%	86%	85%	86%	77%	79%
	GMFB, CTSS, LMAN1, CDC40, CXCL9,
	CXCL10, FAS, CHEK1, SLC25A11, C1QBP,
	C17orf25, CA2, ME2, IFT20, CXCL11,
	RBM25, BRRN1, ATP5A1, RBBP4, HNRPD,
	BRIP1, STAT1
172	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	81%	79%	96%	86%	88%	83%
	TK1, GMFB, DLGAP4, TYMS, CTSS,
	CDC40, SLC4A4, CXCL10, KITLG,
	SLC25A11, C1QBP, NDUFA9, CA2,
	HNRPD, ME2, FUT4, CXCL11, RBM25,
	ATP5A1, FAS, RBBP4, BRIP1, TRMT5,
	STAT1
173	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	77%	79%	77%	86%	73%	86%
	GMFB, TYMS, TES, LMAN1, DCK,
	CXCL9, CXCL10, KITLG, KPNB1,
	SLC25A11, ME2, CXCL11, IFT20, TLK1,
	RBM25, CDC42BPA, FAS, BAZ1A,
	FLJ10534, MARCH5, SEC10L1, HNRPD,
	BRIP1, TRMT5, STAT1
174	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	85%	79%	88%	83%	85%	86%
	MTHFD2, TK1, GMFB, DLGAP4, TYMS,
	LMAN1, CDC40, SLC4A4, CXCL9, IRF8,
	RABIF, CXCL10, SLC25A11, NDUFA9,
	CA2, ME2, CXCL11, RBBP4, RBM25,
	NUP210, FAS, SEC10L1, PBK, STAT1
175	HNRPD, WARS, EPAS1, PRDX3,	85%	90%	88%	83%	85%	72%
	MTHFD2, PSME2, DLGAP4, TYMS,
	CDC40, IRF8, CXCL10, FAS, SLC25A11,
	C1QBP, CA2, ME2, GZMB, IFT20, SLC4A4,
	AK2, NUP210, RBBP4, AGPAT5, MARCH5,
	FLJ13220, STAT1
176	HNRPD, WARS, EIF4E, MTHFD2, PSME2,	81%	79%	88%	76%	88%	79%
	GMFB, DLGAP4, TYMS, CXCL9, CXCL10,
	FAS, C1QBP, NDUFA9, SLC25A11, CA2,
	ME2, RBBP4, SLC4A4, CXCL11, RBM25,
	ATP5A1, DDAH2, BAZ1A, PBK, BRIP1,
	STAT1
177	HNRPD, WARS, SFRS2, EPAS1, STAT1,	96%	93%	92%	76%	88%	76%
	EIF4E, PRDX3, PSME2, DLGAP4, TYMS,
	TES, LMAN1, CDC40, CXCL10, FAS,
	C1QBP, NDUFA9, SLC25A11, CA2, ME2,
	GZMB, IFT20, CXCL11, SLC4A4, RBM25,
	AK2, AGPAT5, DKFZp762E1312, SEC10L1,
	BRIP1, KLHL24
178	WARS, EIF4E, PRDX3, MTHFD2, TK1,	85%	83%	88%	79%	88%	72%
	GMFB, TYMS, CDC40, CXCL9, IRF8,
	CXCL10, FAS, CHEK1, TRIM25,
	SLC25A11, NDUFA9, CA2, ME2, IFT20,
	RBM25, AK2, AGPAT5, MARCH5,
	SEC10L1, FLJ13220, PBK, HNRPD, STAT1
179	WARS, EIF4E, PRDX3, MTHFD2, GBP1,	85%	86%	88%	76%	81%	76%
	GMFB, DLGAP4, TYMS, USP4, IRF8,
	CXCL10, FAS, TRIM25, C1QBP, NDUFA9,
	SLC25A11, WHSC1, CA2, HNRPD, ME2,
	GZMB, TLK1, CXCL11, RBM25,
	DKFZp762E1312, PSAT1, BRIP1, TRMT5,
	KLHL24, STAT1
180	WARS, EPAS1, STAT1, EIF4E, MTHFD2,	92%	90%	88%	79%	73%	76%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	USP4, LMAN1, CXCL9, IRF8, CXCL10,
	C1QBP, NDUFA9, SLC25A11, WHSC1,
	HNRPD, ME2, CXCL11, IFT20, TLK1,
	SLC4A4, CDC42BPA, SFRS2, FAS, PSAT1
181	WARS, EIF4E, PSME2, TK1, GMFB,	77%	79%	81%	79%	85%	76%
	DLGAP4, TYMS, LMAN1, CDC40, CXCL9,
	FAS, PLK4, C1QBP, CA2, HNRPD, ME2,
	CXCL11, RBM25, RBBP4, SEC10L1,
	FLJ13220, PBK, BRIP1, TRMT5, KLHL24,
	ETNK1, STAT1
182	WARS, SFRS2, EIF4E, MTHFD2, GMFB,	88%	83%	85%	83%	77%	86%
	DLGAP4, TYMS, LMAN1, CDC40, CXCL9,
	IRF8, GTSE1, CXCL10, HNRPA3P1,
	SLC25A11, NDUFA9, CA2, HNRPD, ME2,
	RBBP4, SLC4A4, RBM25, BRRN1, FAS,
	BAZ1A, BRIP1, STAT1
183	HNRPD, WARS, EPAS1, EIF4E, MTHFD2,	88%	90%	81%	86%	81%	79%
	TK1, GMFB, DLGAP4, LMAN1, ARF6,
	MAD2L1, CDC40, CXCL9, CXCL10,
	HNRPA3P1, TRIM25, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, ME2,
	CXCL11, SLC4A4, RBM25, DDAH2, FAS,
	ETNK1, STAT1
184	HNRPD, WARS, PAICS, MTHFD2, PSME2,	73%	83%	77%	69%	69%	69%
	DLGAP4, TYMS, USP4, CXCL9, CXCL10,
	KITLG, C1QBP, NDUFA9, SLC25A11,
	WHSC1, ME2, CXCL11, SLC4A4, RBM25,
	NUP210, ATP5A1, CDC42BPA, FAS,
	MARCH5, DKFZp762E1312, SEC10L1,
	PBK, BRIP1, STAT1
185	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	81%	86%	81%	86%	73%	83%
	MTHFD2, PSME2, GMFB, DLGAP4, DCK,
	MAD2L1, CXCL9, CXCL10, FAS, PLK4,
	TRIM25, KITLG, SLC25A11, WHSC1, ME2,
	FUT4, CXCL11, SLC4A4, RBM25, NUP210,
	DDAH2, RBBP4, BAZ1A, AGPAT5,
	FLJ10534, MARCH5, DKFZp762E1312,
	SEC10L1, PSAT1, BRIP1, TRMT5, STAT1
186	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	85%	79%	85%	79%	73%	76%
	MTHFD2, PSME2, GBP1, GMFB, TYMS,
	LMAN1, ARF6, CDC40, CXCL9, IRF8,
	RABIF, CXCL10, FAS, PLK4, C1QBP,
	NDUFA9, SLC25A11, WHSC1, C17orf25,
	ME2, FUT4, CXCL11, IFT20, SLC4A4,
	RBM25, AK2, SOCS6, MARCH5, SEC10L1,
	FLJ13220, PBK, HNRPD, BRIP1, TRMT5,
	STAT1
187	HNRPD, WARS, SFRS2, EIF4E, MTHFD2,	77%	83%	85%	79%	81%	79%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	TES, LMAN1, ARF6, CDC40, SLC4A4,
	CXCL9, RABIF, CXCL10, FAS, PLK4,
	C1QBP, NDUFA9, SLC25A11, WHSC1,
	CA2, ME2, CXCL11, TLK1, RBM25,
	ATP5A1, CDC42BPA, RBBP4, AGPAT5,
	SEC10L1, FLJ13220, PSAT1, BRIP1, STAT1
188	HNRPD, SFRS2, EPAS1, EIF4E, PRDX3,	77%	86%	85%	83%	85%	76%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, CTSS, LMAN1, ARF6,
	MAD2L1, CDC40, CXCL9, CXCL10, FAS,
	PLK4, NDUFA9, WHSC1, C17orf25, CA2,
	ME2, CXCL11, GZMB, TLK1, SLC4A4,
	RBM25, AK2, NUP210, hCAP-D3, DDAH2,
	RBBP4, PBK, BRIP1, STAT1
189	WARS, EIF4E, PRDX3, MTHFD2, GMFB,	77%	79%	96%	79%	85%	72%
	DLGAP4, TYMS, USP4, CTSS, ARF6,
	CDC40, SLC4A4, CXCL9, CXCL10, FAS,
	SLC25A11, C1QBP, NDUFA9, WHSC1,
	C17orf25, CA2, ME2, FUT4, CXCL11,
	GZMB, TLK1, RBM25, NUP210,
	CDC42BPA, AGPAT5, MARCH5, SEC10L1,
	PBK, HNRPD, TRMT5, KLHL24, STAT1
190	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	92%	79%	85%	83%	69%	79%
	MTHFD2, PSME2, GBP1, DLGAP4, TYMS,
	TES, LMAN1, ARF6, CDC40, CXCL9, IRF8,
	CXCL10, FAS, TRIM25, SLC25A11,
	NDUFA9, WHSC1, CA2, ME2, TLK1,
	CXCL11, SLC4A4, RBM25, AK2, hCAP-D3,
	DDAH2, FLJ10534, SEC10L1, BRIP1,
	STAT1
191	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	77%	83%	85%	76%	85%	79%
	PSME2, DLGAP4, TYMS, TES, LMAN1,
	CDC40, CXCL9, IRF8, RABIF, CXCL10,
	FAS, SLC25A11, C1QBP, NDUFA9,
	WHSC1, CA2, ME2, CXCL11, SLC4A4,
	RBM25, AK2, hCAP-D3, SOCS6,
	CDC42BPA, FLJ10534, DKFZp762E1312,
	SEC10L1, FLJ13220, PBK, HNRPD,
	TRMT5, STAT1
192	WARS, SFRS2, STAT1, EIF4E, PRDX3,	73%	86%	85%	83%	85%	83%
	MTHFD2, PSME2, MCM6, TK1, GMFB,
	DLGAP4, TYMS, CTSS, CDC40, CXCL9,
	CXCL10, PLK4, KITLG, SLC25A11,
	C1QBP, NDUFA9, C17orf25, CA2, ME2,
	CXCL11, IFT20, RBM25, hCAP-D3,
	ATP5A1, FAS, FLJ10534, MARCH5,
	SEC10L1, PBK, HNRPD, BRIP1, TRMT5
193	HNRPD, WARS, EPAS1, STAT1, EIF4E,	77%	76%	85%	83%	81%	72%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, TES, MAD2L1, CXCL9,
	CXCL10, FAS, PLK4, HNRPA3P1, C1QBP,
	NDUFA9, SLC25A11, WHSC1, C17orf25,
	CA2, ME2, SLC4A4, RBM25, hCAP-D3,
	SOCS6, BAZ1A, FLJ10534, SEC10L1,
	FLJ13220, PBK, BRIP1
194	SFRS2, PAICS, EIF4E, PRDX3, MTHFD2,	77%	83%	85%	83%	81%	76%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	TES, CTSS, LMAN1, CDC40, CXCL9,
	CXCL10, FAS, TRIM25, C1QBP, NDUFA9,
	SLC25A11, WHSC1, CA2, ME2, CXCL11,
	IFT20, RBBP4, SLC4A4, RBM25, AK2,
	hCAP-D3, BRRN1, CDC42BPA, MARCH5,
	FLJ13220, HNRPD, STAT1
195	WARS, SFRS2, EPAS1, EIF4E, SFPQ,	81%	86%	88%	76%	85%	79%
	MTHFD2, PSME2, MCM6, GMFB,
	DLGAP4, TYMS, USP4, DCK, ARF6,
	CDC40, CXCL10, FAS, CHEK1,
	HNRPA3P1, SLC25A11, NDUFA9, CA2,
	HNRPD, ME2, GZMB, RBBP4, TLK1,
	SLC4A4, CXCL11, RBM25, ATP5A1,
	AGPAT5, FLJ10534, FLJ13220, ETNK1,
	STAT1
196	WARS, SFRS2, STAT1, EIF4E, PRDX3,	88%	83%	88%	79%	88%	72%
	MTHFD2, PSME2, MCM6, GMFB,
	DLGAP4, TYMS, ARF6, CDC40, SLC4A4,
	CXCL9, GTSE1, RABIF, CXCL10, FAS,
	HNRPA3P1, KITLG, NDUFA9, SLC25A11,
	WHSC1, C17orf25, CA2, HNRPD, ME2,
	CXCL11, RBBP4, RBM25, AK2,
	CDC42BPA, MARCH5, TRMT5, KLHL24
197	WARS, SFRS2, EPAS1, STAT1, EIF4E,	77%	79%	85%	79%	88%	79%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, DCK, CDC40, CXCL9,
	RABIF, CXCL10, FAS, PLK4, KITLG,
	C1QBP, NDUFA9, SLC25A11, WHSC1,
	CA2, HNRPD, ME2, FUT4, CXCL11,
	RBM25, CDC42BPA, MARCH5,
	DKFZp762E1312, SEC10L1, PBK
198	WARS, SFRS2, EPAS1, EIF4E, SFPQ,	85%	90%	77%	83%	77%	66%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, USP4, CDC40, RABIF, CXCL10,
	PLK4, KITLG, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, ME2,
	CXCL11, IFT20, RBM25, CAMSAP1L1,
	BRRN1, FAS, AGPAT5, PSAT1, HNRPD,
	TRMT5, KLHL24, ETNK1, STAT1
199	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	92%	90%	96%	76%	85%	76%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, TES, LMAN1, ARF6,
	CDC40, CXCL9, CXCL10, FAS, KITLG,
	C1QBP, NDUFA9, KPNB1, SLC25A11,
	CA2, ME2, GZMB, RBBP4, TLK1, CXCL11,
	RBM25, AK2, SOCS6, AGPAT5, SEC10L1,
	PBK, STAT1
200	SFRS2, PAICS, EIF4E, PRDX3, PSME2,	81%	86%	88%	79%	73%	72%
	GMFB, DLGAP4, TYMS, DCK, ARF6,
	MAD2L1, CDC40, CXCL9, GTSE1, RABIF,
	CXCL10, FAS, C1QBP, NDUFA9,
	SLC25A11, C17orf25, CA2, ME2, GZMB,
	IFT20, CXCL11, RBM25, AK2, hCAP-D3,
	BRRN1, AGPAT5, DKFZp762E1312, PBK,
	PSAT1, HNRPD, TRMT5, ETNK1, STAT1
201	HNRPD, WARS, SFRS2, STAT1, EIF4E,	88%	93%	88%	76%	85%	66%
	MTHFD2, PSME2, DLGAP4, TYMS,
	CXCL9, GTSE1, CXCL10, FAS, CHEK1,
	HNRPA3P1, TRIM25, KITLG, NDUFA9,
	SLC25A11, WHSC1, CA2, ME2, GZMB,
	IFT20, SLC4A4, CXCL11, RBM25,
	CAMSAP1L1, hCAP-D3, BRRN1, AGPAT5,
	MARCH5, DKFZp762E1312, SEC10L1,
	PBK, BRIP1
202	WARS, SFRS2, STAT1, MTHFD2, PSME2,	85%	86%	92%	76%	73%	72%
	MCM6, GMFB, DLGAP4, TYMS, USP4,
	CTSS, ARF6, CDC40, CXCL9, CXCL10,
	FAS, HNRPA3P1, SLC25A11, CA2,
	HNRPD, ME2, FUT4, RBBP4, TLK1,
	CXCL11, SLC4A4, RBM25, AK2,
	CDC42BPA, AGPAT5, DKFZp762E1312,
	SEC10L1, FLJ13220, PBK, KLHL24,
	ETNK1
203	WARS, SFRS2, STAT1, MTHFD2, PSME2,	92%	86%	85%	76%	69%	69%
	GMFB, DLGAP4, SLC4A4, CXCL9,
	CXCL10, FAS, CHEK1, TRIM25, KITLG,
	SLC25A11, C1QBP, NDUFA9, KPNB1,
	WHSC1, ME2, CXCL11, IFT20, RBM25,
	NUP210, CAMSAP1L1, BRRN1,
	CDC42BPA, DDAH2, AGPAT5,
	DKFZp762E1312, SEC10L1, FLJ13220,
	PBK, HNRPD, TRMT5, KLHL24
204	WARS, SFRS2, EPAS1, EIF4E, PSME2,	85%	83%	85%	76%	81%	72%
	MCM6, GMFB, DLGAP4, TYMS, DCK,
	ARF6, SLC4A4, CXCL9, IRF8, CXCL10,
	FAS, KITLG, NDUFA9, SLC25A11,
	WHSC1, CA2, HNRPD, ME2, FUT4, GZMB,
	IFT20, RBBP4, CXCL11, RBM25, AK2,
	AGPAT5, MARCH5, SEC10L1, FLJ13220,
	PBK, BRIP1, ETNK1, STAT1
205	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	96%	86%	81%	79%	85%	72%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	CTSS, LMAN1, MAD2L1, CDC40, SLC4A4,
	CXCL9, GTSE1, RABIF, CXCL10, FAS,
	PLK4, TRIM25, C1QBP, NDUFA9,
	SLC25A11, CA2, HNRPD, ME2, CXCL11,
	IFT20, RBM25, BRRN1, CDC42BPA,
	DDAH2, PSAT1, KLHL24, STAT1
206	WARS, PAICS, EIF4E, MTHFD2, PSME2,	81%	83%	88%	90%	77%	79%
	TK1, GMFB, DLGAP4, TYMS, ARF6,
	SLC4A4, CXCL9, CXCL10, FAS, PLK4,
	TRIM25, SLC25A11, C1QBP, NDUFA9,
	KPNB1, WHSC1, C17orf25, HNRPD, ME2,
	CXCL11, IFT20, TLK1, RBM25, AK2,
	AGPAT5, SEC10L1, FLJ13220, BRIP1,
	TRMT5, KLHL24, STAT1
207	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	85%	90%	96%	79%	85%	79%
	PSME2, GMFB, DLGAP4, TYMS, LMAN1,
	ARF6, CDC40, CXCL9, CXCL10, FAS,
	HNRPA3P1, KITLG, SLC25A11, C1QBP,
	NDUFA9, KPNB1, WHSC1, C17orf25, CA2,
	HNRPD, ME2, FUT4, CXCL11, GZMB,
	IFT20, SLC4A4, RBM25, AK2, SEC10L1,
	PBK, BRIP1, STAT1
208	HNRPD, WARS, EPAS1, STAT1, EIF4E,	77%	79%	81%	83%	73%	72%
	PRDX3, MTHFD2, PSME2, GBP1, TK1,
	GMFB, DLGAP4, TYMS, TES, CDC40,
	CXCL9, IRF8, GTSE1, CXCL10, FAS,
	C1QBP, NDUFA9, C17orf25, ME2, SLC4A4,
	CXCL11, RBM25, NUP210, FLJ10534,
	MARCH5, DKFZp762E1312, FLJ13220,
	PBK, BRIP1, TRMT5, ETNK1
209	WARS, EIF4E, PRDX3, MTHFD2, PSME2,	85%	86%	88%	79%	85%	76%
	DLGAP4, TYMS, USP4, LMAN1, MAD2L1,
	CDC40, SLC4A4, CXCL9, IRF8, GTSE1,
	RABIF, CXCL10, FAS, TRIM25, C1QBP,
	NDUFA9, SLC25A11, C17orf25, CA2, ME2,
	CXCL11, GZMB, IFT20, TLK1, RBM25,
	AK2, SOCS6, RBBP4, AGPAT5, MARCH5,
	SEC10L1, PBK, HNRPD, STAT1
210	HNRPD, WARS, SFRS2, STAT1, EIF4E,	77%	79%	85%	86%	81%	79%
	SFPQ, PRDX3, MTHFD2, PSME2, MCM6,
	DLGAP4, TYMS, ARF6, MAD2L1, CDC40,
	CXCL9, RABIF, CXCL10, PLK4, CHEK1,
	TRIM25, C1QBP, NDUFA9, WHSC1,
	C17orf25, CA2, ME2, CXCL11, TLK1,
	BRRN1, SOCS6, FAS, AGPAT5, MARCH5,
	FLJ13220, PBK, TRMT5, KLHL24
211	WARS, PAICS, EIF4E, PRDX3, MTHFD2,	77%	79%	85%	76%	81%	72%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	USP4, DCK, MAD2L1, CDC40, RABIF,
	CXCL10, FAS, HNRPA3P1, SLC25A11,
	NDUFA9, C17orf25, ME2, CXCL11,
	SLC4A4, RBM25, AK2, hCAP-D3, SOCS6,
	DDAH2, RBBP4, AGPAT5,
	DKFZp762E1312, SEC10L1, PBK, PSAT1,
	HNRPD, BRIP1, ETNK1, STAT1
212	HNRPD, WARS, EPAS1, STAT1, EIF4E,	81%	83%	85%	76%	77%	79%
	MTHFD2, GBP1, TK1, GMFB, DLGAP4,
	TYMS, LMAN1, DCK, CDC40, CXCL9,
	IRF8, CXCL10, FAS, PLK4, HNRPA3P1,
	SLC25A11, NDUFA9, KPNB1, WHSC1,
	CA2, ME2, CXCL11, GZMB, RBBP4,
	SLC4A4, RBM25, NUP210, DDAH2, PBK,
	KLHL24, ETNK1
213	HNRPD, WARS, SFRS2, STAT1, EIF4E,	100%	90%	92%	72%	85%	79%
	PRDX3, MTHFD2, GMFB, DLGAP4,
	TYMS, DCK, ARF6, CDC40, CXCL9, IRF8,
	CXCL10, FAS, TRIM25, SLC25A11,
	C1QBP, C17orf25, CA2, ME2, CXCL11,
	GZMB, IFT20, TLK1, RBM25, AK2,
	CDC42BPA, SEC10L1, FLJ13220, PBK,
	BRIP1, KLHL24, ETNK1
214	WARS, EIF4E, MTHFD2, PSME2, TK1,	81%	79%	85%	79%	85%	72%
	GMFB, DLGAP4, TYMS, USP4, CDC40,
	CXCL9, IRF8, GTSE1, CXCL10, FAS,
	PLK4, TRIM25, C1QBP, SLC25A11,
	C17orf25, CA2, HNRPD, ME2, CXCL11,
	IFT20, AK2, BRRN1, SOCS6, CDC42BPA,
	SFRS2, RBBP4, MARCH5, SEC10L1,
	FLJ13220, PSAT1, BRIP1, TRMT5,
	KLHL24, STAT1
215	HNRPD, WARS, SFRS2, EIF4E, PRDX3,	85%	86%	88%	72%	81%	72%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, MAD2L1, CDC40, CXCL9, IRF8,
	GTSE1, CXCL10, SLC25A11, NDUFA9,
	WHSC1, CA2, ME2, CXCL11, IFT20,
	RBM25, AK2, BRRN1, CDC42BPA, FAS,
	RBBP4, BAZ1A, AGPAT5, SEC10L1,
	FLJ13220, PBK, BRIP1, KLHL24, ETNK1,
	STAT1
216	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	73%	83%	88%	79%	85%	72%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, TES, CTSS, LMAN1,
	CDC40, CXCL9, IRF8, CXCL10, FAS,
	PLK4, HNRPA3P1, KITLG, C1QBP,
	NDUFA9, SLC25A11, WHSC1, C17orf25,
	CA2, ME2, CXCL11, RBM25, AK2, hCAP-
	D3, BAZ1A, AGPAT5, DKFZp762E1312,
	PBK, BRIP1
217	WARS, EIF4E, MTHFD2, PSME2, MCM6,	85%	86%	81%	79%	77%	76%
	DLGAP4, TYMS, USP4, TES, DCK, ARF6,
	MAD2L1, CDC40, CXCL9, IRF8, CXCL10,
	PLK4, HNRPA3P1, TRIM25, SLC25A11,
	C1QBP, WHSC1, CA2, ME2, CXCL11,
	GZMB, IFT20, TLK1, SLC4A4, RBM25,
	SOCS6, DDAH2, FAS, FLJ13220, PBK,
	KLHL24, ETNK1, STAT1
218	WARS, SFRS2, EPAS1, STAT1, PAICS,	81%	83%	85%	83%	88%	76%
	PRDX3, MTHFD2, PSME2, MCM6, GMFB,
	DLGAP4, TYMS, USP4, TES, LMAN1,
	SLC4A4, CXCL9, IRF8, CXCL10, FAS,
	PLK4, CHEK1, HNRPA3P1, TRIM25,
	C1QBP, NDUFA9, CA2, ME2, FUT4,
	CXCL11, RBM25, AK2, ATP5A1, AGPAT5,
	SEC10L1, FLJ13220, HNRPD, KLHL24
219	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	81%	79%	85%	79%	88%	76%
	PSME2, GBP1, GMFB, DLGAP4, TYMS,
	USP4, CDC40, CXCL9, CXCL10, FAS,
	PLK4, HNRPA3P1, SLC25A11, NDUFA9,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	IFT20, RBM25, hCAP-D3, ATP5A1, RBBP4,
	AGPAT5, FLJ10534, MARCH5, SEC10L1,
	HNRPD, BRIP1, KLHL24, STAT1
220	HNRPD, WARS, SFRS2, EPAS1, SFPQ,	73%	79%	85%	79%	85%	83%
	PRDX3, MTHFD2, PSME2, GMFB, TYMS,
	USP4, TES, LMAN1, CDC40, CXCL9,
	CXCL10, FAS, C1QBP, SLC25A11,
	WHSC1, CA2, ME2, FUT4, TLK1, CXCL11,
	SLC4A4, RBM25, hCAP-D3, DDAH2,
	BAZ1A, FLJ10534, MARCH5, FLJ13220,
	PBK, PSAT1, BRIP1,TRMT5, STAT1
221	HNRPD, EPAS1, STAT1, PRDX3,	81%	83%	88%	83%	85%	86%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, CTSS, DCK, CXCL9,
	CXCL10, FAS, CHEK1, HNRPA3P1,
	C1QBP, NDUFA9, KPNB1, SLC25A11,
	WHSC1, CA2, ME2, CXCL11, TLK1,
	RBM25, ATP5A1, DDAH2, RBBP4,
	SEC10L1, PBK, BRIP1, ETNK1
222	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	88%	86%	92%	72%	81%	72%
	DLGAP4, TYMS, ARF6, CXCL9, IRF8,
	GTSE1, RABIF, CXCL10, FAS, PLK4,
	KITLG, SLC25A11, C1QBP, NDUFA9,
	ME2, CXCL11, GZMB, IFT20, RBBP4,
	SLC4A4, RBM25, AK2, BAZ1A, AGPAT5,
	MARCH5, FLJ13220, HNRPD, BRIP1,
	KLHL24, ETNK1, STAT1
223	HNRPD, WARS, SFRS2, STAT1, EIF4E,	85%	83%	88%	76%	81%	83%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, LMAN1, ARF6, CXCL9, GTSE1,
	CXCL10, FAS, PLK4, HNRPA3P1, TRIM25,
	KITLG, C1QBP, SLC25A11, WHSC1,
	C17orf25, CA2, ME2, CXCL11, TLK1,
	RBM25, ATP5A1, AGPAT5, FLJ10534,
	MARCH5, FLJ13220, PBK, BRIP1, TRMT5
224	HNRPD, WARS, SFRS2, EIF4E, PRDX3,	85%	79%	92%	76%	85%	72%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, USP4, TES, CDC40, SLC4A4,
	CXCL9, CXCL10, FAS, TRIM25, KITLG,
	C1QBP, NDUFA9, C17orf25, CA2, ME2,
	GZMB, TLK1, CXCL11, RBM25,
	CAMSAP1L1, CDC42BPA, DDAH2,
	BAZ1A, AGPAT5, SEC10L1, PBK,
	KLHL24, ETNK1, STAT1
225	WARS, EIF4E, PRDX3, MTHFD2, PSME2,	81%	79%	88%	76%	88%	79%
	GMFB, DLGAP4, TYMS, USP4, CTSS,
	ARF6, CDC40, CXCL9, IRF8, CXCL10,
	FAS, PLK4, CHEK1, TRIM25, C1QBP,
	NDUFA9, SLC25A11, WHSC1, CA2,
	HNRPD, ME2, CXCL11, GZMB, IFT20,
	RBBP4, SLC4A4, RBM25, ATP5A1, PBK,
	BRIP1, TRMT5, STAT1
226	HNRPD, WARS, SFRS2, EIF4E, MTHFD2,	77%	79%	77%	86%	73%	69%
	PSME2, GMFB, DLGAP4, TYMS, LMAN1,
	DCK, CXCL9, CXCL10, FAS, HNRPA3P1,
	TRIM25, C1QBP, NDUFA9, SLC25A11,
	WHSC1, ME2, SLC4A4, CXCL11, RBM25,
	BRRN1, BAZ1A, AGPAT5, FLJ10534,
	MARCH5, SEC10L1, FLJ13220, PBK,
	PSAT1, BRIP1, TRMT5, ETNK1, STAT1
227	HNRPD, WARS, SFRS2, EPAS1, PRDX3,	81%	90%	92%	76%	88%	69%
	PSME2, GBP1, TK1, DLGAP4, TYMS,
	DCK, ARF6, CDC40, CXCL9, GTSE1,
	RABIF, CXCL10, FAS, TRIM25, C1QBP,
	NDUFA9, SLC25A11, C17orf25, CA2, ME2,
	CXCL11, GZMB, IFT20, RBBP4, RBM25,
	AGPAT5, MARCH5, SEC10L1, FLJ13220,
	PBK, BRIP1, STAT1
228	WARS, SFRS2, EPAS1, STAT1, EIF4E,	77%	83%	88%	76%	88%	76%
	MTHFD2, GMFB, DLGAP4, TYMS, TES,
	CTSS, CXCL9, CXCL10, FAS, PLK4,
	CHEK1, TRIM25, SLC25A11, NDUFA9,
	WHSC1, C17orf25, CA2, ME2, FUT4,
	CXCL11, SLC4A4, RBM25, AK2, BRRN1,
	CDC42BPA, DDAH2, AGPAT5, MARCH5,
	PBK, HNRPD, KLHL24
229	HNRPD, WARS, SFRS2, EPAS1, PAICS,	85%	86%	85%	72%	85%	76%
	EIF4E, PRDX3, MTHFD2, PSME2,
	DLGAP4, TYMS, CXCL9, IRF8, RABIF,
	FAS, PLK4, TRIM25, SLC25A11, C1QBP,
	WHSC1, C17orf25, CA2, ME2, FUT4,
	CXCL11, GZMB, IFT20, RBM25, SOCS6,
	DDAH2, MARCH5, PBK, PSAT1, BRIP1,
	TRMT5, STAT1
230	WARS, SFRS2, STAT1, MTHFD2, PSME2,	73%	83%	81%	76%	69%	66%
	GMFB, DLGAP4, TYMS, USP4, TES, ARF6,
	CDC40, CXCL9, CXCL10, FAS,
	HNRPA3P1, C1QBP, SLC25A11, WHSC1,
	ME2, CXCL11, RBBP4, SLC4A4, RBM25,
	AK2, hCAP-D3, CDC42BPA, FLJ10534,
	SEC10L1, FLJ13220, PBK, PSAT1, HNRPD,
	BRIP1, TRMT5, KLHL24
231	SFRS2, EPAS1, EIF4E, MTHFD2, PSME2,	73%	76%	92%	72%	77%	76%
	MCM6, TK1, GMFB, DLGAP4, TYMS,
	CTSS, LMAN1, CXCL9, IRF8, CXCL10,
	CHEK1, HNRPA3P1, KITLG, SLC25A11,
	C1QBP, NDUFA9, WHSC1, C17orf25, ME2,
	FUT4, CXCL11, GZMB, RBM25,
	CDC42BPA, FAS, RBBP4, AGPAT5,
	FLJ10534, SEC10L1, FLJ13220, PBK,
	HNRPD, TRMT5, STAT1
232	HNRPD, WARS, SFRS2, PAICS, EIF4E,	73%	79%	88%	86%	81%	83%
	MTHFD2, PSME2, MCM6, GBP1, TK1,
	GMFB, DLGAP4, TYMS, USP4, TES,
	CDC40, CXCL9, IRF8, RABIF, CXCL10,
	CHEK1, C1QBP, NDUFA9, SLC25A11,
	WHSC1, CA2, ME2, FUT4, CXCL11, IFT20,
	TLK1, SLC4A4, RBM25, NUP210,
	CAMSAP1L1, BRRN1, FAS, RBBP4,
	BAZ1A, FLJ10534, MARCH5, SEC10L1,
	FLJ13220, PBK, PSAT1, KLHL24, STAT1
233	WARS, EIF4E, PRDX3, MTHFD2, PSME2,	77%	79%	92%	76%	88%	76%
	GMFB, DLGAP4, TYMS, USP4, TES,
	LMAN1, DCK, ARF6, MAD2L1, CDC40,
	SLC4A4, CXCL9, GTSE1, CXCL10, FAS,
	KITLG, NDUFA9, SLC25A11, WHSC1,
	C17orf25, CA2, HNRPD, ME2, FUT4,
	CXCL11, GZMB, IFT20, TLK1, RBM25,
	AK2, CAMSAP1L1, DDAH2, RBBP4,
	BAZ1A, AGPAT5, SEC10L1, PBK, BRIP1,
	KLHL24, ETNK1, STAT1
234	WARS, SFRS2, EPAS1, STAT1, PAICS,	85%	90%	92%	79%	77%	83%
	EIF4E, PRDX3, MTHFD2, PSME2, GBP1,
	GMFB, DLGAP4, TYMS, ARF6, CDC40,
	CXCL9, IRF8, RABIF, CXCL10, FAS,
	SLC25A11, NDUFA9, C17orf25, CA2, ME2,
	CXCL11, GZMB, IFT20, RBBP4, TLK1,
	SLC4A4, RBM25, NUP210, BRRN1,
	ATP5A1, AGPAT5, MARCH5, SEC10L1,
	PBK, PSAT1, HNRPD, BRIP1, TRMT5
235	WARS, SFRS2, EPAS1, STAT1, EIF4E,	81%	90%	92%	76%	85%	69%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, USP4, CTSS, DCK, ARF6,
	MAD2L1, CDC40, CXCL9, CXCL10, PLK4,
	CHEK1, TRIM25, KITLG, SLC25A11,
	C1QBP, KPNB1, WHSC1, C17orf25, CA2,
	HNRPD, ME2, GZMB, CXCL11, RBM25,
	BRRN1, ATP5A1, CDC42BPA, DDAH2,
	FAS, BAZ1A, AGPAT5, FLJ10534,
	MARCH5, SEC10L1, PBK, TRMT5,
	KLHL24, ETNK1
236	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	81%	83%	88%	72%	81%	76%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, TES, CTSS, DCK, ARF6,
	MAD2L1, CDC40, CXCL9, RABIF,
	CXCL10, CHEK1, HNRPA3P1, TRIM25,
	KITLG, C1QBP, NDUFA9, KPNB1,
	SLC25A11, WHSC1, CA2, ME2, GZMB,
	SLC4A4, CXCL11, RBM25, AK2, ATP5A1,
	DDAH2, FAS, BAZ1A, DKFZp762E1312,
	SEC10L1, FLJ13220, BRIP1, TRMT5,
	ETNK1, STAT1
237	WARS, SFRS2, PAICS, EIF4E, PRDX3,	77%	83%	92%	83%	81%	76%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, DCK, ARF6, MAD2L1,
	SLC4A4, CXCL9, GTSE1, CXCL10, FAS,
	HNRPA3P1, KITLG, SLC25A11, C1QBP,
	NDUFA9, KPNB1, C17orf25, CA2, HNRPD,
	ME2, CXCL11, GZMB, IFT20, RBBP4,
	RBM25, AK2, ATP5A1, BAZ1A, AGPAT5,
	SEC10L1, FLJ13220, PBK, BRIP1, ETNK1,
	STAT1
238	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	85%	86%	88%	86%	85%	79%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, TES, CTSS, LMAN1,
	SLC4A4, CXCL9, IRF8, GTSE1, CXCL10,
	CHEK1, TRIM25, KITLG, SLC25A11,
	C1QBP, NDUFA9, KPNB1, WHSC1,
	C17orf25, CA2, ME2, FUT4, TLK1,
	CXCL11, RBM25, BRRN1, DDAH2, FAS,
	RBBP4, AGPAT5, FLJ10534, MARCH5,
	SEC10L1, FLJ13220, PBK, TRMT5, STAT1
239	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	69%	79%	88%	83%	81%	76%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, DCK, CDC40, CXCL9,
	IRF8, GTSE1, RABIF, CXCL10, FAS,
	CHEK1, SLC25A11, C1QBP, NDUFA9,
	WHSC1, C17orf25, CA2, ME2, IFT20,
	CXCL11, SLC4A4, RBM25, AK2, hCAP-D3,
	ATP5A1, SOCS6, DDAH2, FLJ10534,
	MARCH5, SEC10L1, PBK, PSAT1, BRIP1,
	STAT1
240	WARS, SFRS2, EPAS1, STAT1, EIF4E,	81%	83%	96%	69%	81%	76%
	PRDX3, MTHFD2, TK1, GMFB, DLGAP4,
	TYMS, CTSS, LMAN1, ARF6, MAD2L1,
	CXCL9, IRF8, RABIF, CXCL10, FAS,
	HNRPA3P1, TRIM25, KITLG, C1QBP,
	NDUFA9, SLC25A11, WHSC1, C17orf25,
	HNRPD, ME2, GZMB, SLC4A4, CXCL11,
	RBM25, AK2, CAMSAP1L1, hCAP-D3,
	BRRN1, CDC42BPA, RBBP4, BAZ1A,
	FLJ10534, SEC10L1, BRIP1, KLHL24,
	ETNK1
241	HNRPD, WARS, SFRS2, EIF4E, PRDX3,	73%	79%	88%	83%	92%	79%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, LMAN1, MAD2L1, CDC40, CXCL9,
	RABIF, CXCL10, FAS, PLK4, TRIM25,
	SLC25A11, NDUFA9, KPNB1, WHSC1,
	CA2, ME2, CXCL11, TLK1, SLC4A4,
	RBM25, hCAP-D3, BRRN1, SOCS6,
	CDC42BPA, DDAH2, RBBP4, BAZ1A,
	AGPAT5, DKFZp762E1312, SEC10L1, PBK,
	BRIP1, KLHL24, ETNK1, STAT1
242	WARS, STAT1, EIF4E, MTHFD2, PSME2,	81%	83%	85%	79%	81%	69%
	TK1, GMFB, DLGAP4, TYMS, USP4, CTSS,
	LMAN1, DCK, ARF6, MAD2L1, CDC40,
	CXCL9, RABIF, CXCL10, FAS, PLK4,
	TRIM25, KITLG, SLC25A11, C1QBP,
	NDUFA9, KPNB1, C17orf25, CA2, ME2,
	CXCL11, GZMB, SLC4A4, RBM25, AK2,
	hCAP-D3, DDAH2, RBBP4, BAZ1A,
	PSAT1, HNRPD, BRIP1, TRMT5, KLHL24,
	ETNK1
243	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	85%	83%	92%	79%	77%	72%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	CTSS, LMAN1, CDC40, SLC4A4, CXCL9,
	CXCL10, FAS, PLK4, CHEK1, KITLG,
	C1QBP, NDUFA9, WHSC1, CA2, HNRPD,
	ME2, CXCL11, GZMB, TLK1, RBM25,
	AK2, hCAP-D3, BRRN1, CDC42BPA,
	RBBP4, BAZ1A, AGPAT5, SEC10L1,
	FLJ13220, PBK, BRIP1, KLHL24, ETNK1,
	STAT1
244	WARS, SFRS2, EPAS1, STAT1, EIF4E,	81%	83%	88%	79%	81%	69%
	PRDX3, MTHFD2, PSME2, GBP1, TK1,
	GMFB, DLGAP4, TYMS, USP4, ARF6,
	CDC40, SLC4A4, CXCL9, RABIF, CXCL10,
	FAS, PLK4, CHEK1, KITLG, SLC25A11,
	C1QBP, NDUFA9, WHSC1, CA2, HNRPD,
	ME2, CXCL11, GZMB, IFT20, RBM25,
	CAMSAP1L1, BRRN1, CDC42BPA,
	BAZ1A, AGPAT5, FLJ10534,
	DKFZp762E1312, PBK, ETNK1
245	HNRPD, WARS, SFRS2, EPAS1, PAICS,	77%	86%	88%	76%	77%	76%
	EIF4E, PRDX3, MTHFD2, PSME2, MCM6,
	GMFB, DLGAP4, TYMS, TES, DCK,
	CDC40, SLC4A4, CXCL9, CXCL10, PLK4,
	CHEK1, HNRPA3P1, KITLG, C1QBP,
	NDUFA9, SLC25A11, WHSC1, CA2, ME2,
	GZMB, RBBP4, CXCL11, RBM25, AK2,
	NUP210, CAMSAP1L1, hCAP-D3,
	CDC42BPA, FAS, MARCH5, SEC10L1,
	PBK, ETNK1, STAT1
246	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	77%	83%	92%	79%	81%	79%
	MTHFD2, PSME2, GBP1, GMFB, DLGAP4,
	TYMS, TES, LMAN1, CDC40, SLC4A4,
	CXCL9, RABIF, CXCL10, FAS, PLK4,
	HNRPA3P1, SLC25A11, C1QBP, NDUFA9,
	KPNB1, WHSC1, C17orf25, CA2, ME2,
	FUT4, GZMB, TLK1, CXCL11, RBM25,
	CAMSAP1L1, DDAH2, AGPAT5,
	MARCH5, SEC10L1, FLJ13220, PBK,
	HNRPD, BRIP1, ETNK1, STAT1
247	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	77%	83%	85%	79%	85%	72%
	MTHFD2, PSME2, GBP1, GMFB, DLGAP4,
	TYMS, USP4, TES, MAD2L1, CDC40,
	SLC4A4, CXCL9, IRF8, GTSE1, CXCL10,
	PLK4, KITLG, C1QBP, NDUFA9, KPNB1,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	IFT20, RBBP4, CXCL11, RBM25, AK2,
	CAMSAP1L1, CDC42BPA, FAS, AGPAT5,
	FLJ10534, MARCH5, SEC10L1, PBK,
	HNRPD, BRIP1, KLHL24, ETNK1, STAT1
248	HNRPD, WARS, SFRS2, EIF4E, PRDX3,	77%	86%	88%	76%	81%	69%
	MTHFD2, PSME2, MCM6, GBP1, TK1,
	GMFB, DLGAP4, TYMS, USP4, DCK,
	CDC40, CXCL9, GTSE1, RABIF, CXCL10,
	FAS, PLK4, TRIM25, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	FUT4, GZMB, IFT20, RBBP4, CXCL11,
	SLC4A4, RBM25, BRRN1, AGPAT5,
	FLJ10534, MARCH5, FLJ13220, PSAT1,
	TRMT5, KLHL24, ETNK1, STAT1
249	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	92%	97%	88%	76%	85%	79%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, USP4, MAD2L1, SLC4A4, CXCL9,
	GTSE1, CXCL10, FAS, PLK4, TRIM25,
	KITLG, NDUFA9, KPNB1, WHSC1,
	C17orf25, CA2, ME2, FUT4, CXCL11,
	GZMB, IFT20, TLK1, RBM25,
	CAMSAP1L1, BRRN1, SOCS6, CDC42BPA,
	BAZ1A, AGPAT5, MARCH5, SEC10L1,
	FLJ13220, KLHL24, ETNK1, STAT1
250	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	92%	90%	92%	76%	85%	79%
	SFPQ, PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, USP4, ARF6, CDC40,
	CXCL9, CXCL10, FAS, CHEK1, TRIM25,
	NDUFA9, KPNB1, SLC25A11, C17orf25,
	CA2, ME2, CXCL11, IFT20, TLK1,
	SLC4A4, RBM25, AK2, BRRN1, ATP5A1,
	DDAH2, BAZ1A, AGPAT5, MARCH5,
	SEC10L1, FLJ13220, PBK, PSAT1, BRIP1,
	STAT1
251	WARS, EPAS1, STAT1, EIF4E, SFPQ,	77%	90%	92%	76%	85%	72%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, LMAN1, ARF6, SLC4A4,
	CXCL9, IRF8, GTSE1, CXCL10, FAS,
	PLK4, HNRPA3P1, SLC25A11, C1QBP,
	NDUFA9, CA2, HNRPD, ME2, FUT4,
	CXCL11, GZMB, IFT20, TLK1, RBM25,
	AK2, ATP5A1, SOCS6, DDAH2, RBBP4,
	AGPAT5, MARCH5, SEC10L1, FLJ13220,
	BRIP1, TRMT5
252	WARS, SFRS2, EPAS1, PAICS, EIF4E,	65%	83%	77%	90%	73%	76%
	PRDX3, MTHFD2, PSME2, GBP1, GMFB,
	DLGAP4, TYMS, USP4, CTSS, DCK,
	CDC40, SLC4A4, GTSE1, RABIF, CXCL10,
	FAS, PLK4, HNRPA3P1, C1QBP,
	SLC25A11, WHSC1, HNRPD, ME2, FUT4,
	CXCL11, IFT20, TLK1, RBM25, AK2,
	NUP210, BRRN1, ATP5A1, AGPAT5,
	FLJ10534, DKFZp762E1312, SEC10L1,
	FLJ13220, PBK, TRMT5, KLHL24, ETNK1,
	STAT1
253	HNRPD, WARS, EPAS1, STAT1, EIF4E,	73%	83%	85%	79%	81%	76%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, USP4, TES, LMAN1,
	DCK, SLC4A4, CXCL9, CXCL10, FAS,
	PLK4, C1QBP, NDUFA9, KPNB1,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	FUT4, CXCL11, RBBP4, TLK1, RBM25,
	CAMSAP1L1, ATP5A1, MARCH5,
	SEC10L1, PBK, PSAT1, BRIP1, TRMT5,
	KLHL24, ETNK1
254	HNRPD, WARS, EPAS1, EIF4E, MTHFD2,	77%	76%	92%	86%	88%	79%
	PSME2, MCM6, GBP1, GMFB, DLGAP4,
	TYMS, USP4, CTSS, DCK, ARF6, SLC4A4,
	CXCL9, IRF8, CXCL10, FAS, PLK4,
	CHEK1, HNRPA3P1, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	FUT4, IFT20, RBBP4, CXCL11, RBM25,
	NUP210, hCAP-D3, SFRS2, DDAH2,
	BAZ1A, AGPAT5, FLJ10534,
	DKFZp762E1312, SEC10L1, FLJ13220,
	KLHL24, STAT1
255	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	81%	79%	85%	79%	85%	76%
	PRDX3, MTHFD2, PSME2, GBP1, TK1,
	GMFB, DLGAP4, TYMS, LMAN1, CDC40,
	CXCL9, CXCL10, PLK4, CHEK1, TRIM25,
	KITLG, C1QBP, NDUFA9, WHSC1,
	C17orf25, CA2, ME2, CXCL11, SLC4A4,
	RBM25, AK2, NUP210, DDAH2, FAS,
	BAZ1A, AGPAT5, FLJ10534, MARCH5,
	DKFZp762E1312, SEC10L1, PBK, PSAT1,
	BRIP1, KLHL24, STAT1
256	WARS, SFRS2, EPAS1, STAT1, EIF4E,	77%	83%	85%	79%	81%	83%
	SFPQ, PRDX3, MTHFD2, TK1, GMFB,
	DLGAP4, TYMS, USP4, LMAN1, ARF6,
	CDC40, SLC4A4, CXCL9, RABIF, CXCL10,
	FAS, PLK4, CHEK1, TRIM25, KITLG,
	SLC25A11, C1QBP, NDUFA9, C17orf25,
	CA2, ME2, TLK1, RBM25, NUP210,
	AGPAT5, FLJ10534, SEC10L1, FLJ13220,
	PBK, PSAT1, HNRPD, BRIP1, TRMT5,
	KLHL24
257	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	73%	86%	88%	83%	77%	72%
	GBP1, TK1, GMFB, DLGAP4, TYMS,
	LMAN1, MAD2L1, CDC40, CXCL9,
	CXCL10, FAS, CHEK1, HNRPA3P1,
	KITLG, SLC25A11, C1QBP, NDUFA9,
	KPNB1, WHSC1, CA2, HNRPD, ME2,
	GZMB, TLK1, SLC4A4, CXCL11, RBM25,
	AK2, CAMSAP1L1, DDAH2, AGPAT5,
	FLJ10534, MARCH5, DKFZp762E1312,
	PBK, PSAT1, BRIP1, TRMT5, KLHL24,
	ETNK1, STAT1
258	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	77%	83%	73%	86%	73%	76%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	LMAN1, ARF6, CDC40, CXCL9, CXCL10,
	FAS, PLK4, CHEK1, HNRPA3P1,
	SLC25A11, C1QBP, NDUFA9, WHSC1,
	C17orf25, HNRPD, ME2, CXCL11, IFT20,
	RBBP4, SLC4A4, RBM25, AK2, ATP5A1,
	SOCS6, FLJ10534, MARCH5,
	DKFZp762E1312, SEC10L1, FLJ13220,
	PBK, PSAT1, BRIP1, TRMT5, ETNK1,
	STAT1
259	HNRPD, WARS, EPAS1, PAICS, MTHFD2,	85%	93%	92%	72%	77%	72%
	PSME2, MCM6, GMFB, DLGAP4, TYMS,
	CDC40, CXCL9, RABIF, CXCL10, FAS,
	PLK4, HNRPA3P1, TRIM25, SLC25A11,
	C1QBP, NDUFA9, WHSC1, CA2, ME2,
	CXCL11, GZMB, IFT20, RBBP4, TLK1,
	RBM25, AK2, CAMSAP1L1, ATP5A1,
	CDC42BPA, DDAH2, BAZ1A, AGPAT5,
	FLJ10534, MARCH5, SEC10L1, FLJ13220,
	PBK, PSAT1, BRIP1, ETNK1, STAT1
260	HNRPD, WARS, SFRS2, PAICS, EIF4E,	77%	79%	85%	76%	85%	69%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, ARF6, MAD2L1, CDC40,
	CXCL9, GTSE1, RABIF, CXCL10, PLK4,
	CHEK1, HNRPA3P1, TRIM25, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	FUT4, CXCL11, IFT20, SLC4A4, RBM25,
	AK2, NUP210, ATP5A1, SOCS6, FAS,
	AGPAT5, FLJ10534, MARCH5, SEC10L1,
	PBK, PSAT1, BRIP1, ETNK1, STAT1
261	HNRPD, WARS, SFRS2, STAT1, MTHFD2,	85%	83%	88%	72%	77%	76%
	TK1, GMFB, DLGAP4, TYMS, USP4, CTSS,
	ARF6, SLC4A4, CXCL9, GTSE1, CXCL10,
	FAS, HNRPA3P1, TRIM25, SLC25A11,
	C1QBP, NDUFA9, KPNB1, WHSC1,
	C17orf25, CA2, ME2, CXCL11, GZMB,
	IFT20, RBM25, hCAP-D3, ATP5A1, SOCS6,
	DDAH2, BAZ1A, MARCH5, SEC10L1,
	FLJ13220, PBK, PSAT1, BRIP1, ETNK1
262	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	77%	79%	85%	79%	85%	76%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, LMAN1, DCK, CDC40,
	CXCL9, CXCL10, FAS, PLK4, CHEK1,
	HNRPA3P1, KITLG, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	CXCL11, IFT20, SLC4A4, RBM25, AK2,
	ATP5A1, SOCS6, BAZ1A, AGPAT5,
	FLJ10534, SEC10L1, PBK, PSAT1, BRIP1,
	KLHL24, ETNK1, STAT1
263	HNRPD, WARS, SFRS2, EPAS1, STAT1,	81%	83%	88%	79%	81%	79%
	EIF4E, PRDX3, PSME2, MCM6, GBP1,
	GMFB, DLGAP4, USP4, CTSS, ARF6,
	CDC40, SLC4A4, CXCL9, GTSE1, RABIF,
	CXCL10, FAS, CHEK1, HNRPA3P1,
	KITLG, C1QBP, NDUFA9, KPNB1,
	WHSC1, CA2, ME2, CXCL11, RBM25,
	CDC42BPA, RBBP4, AGPAT5, MARCH5,
	SEC10L1, FLJ13220, PBK, PSAT1, TRMT5,
	KLHL24
264	WARS, SFRS2, EPAS1, EIF4E, SFPQ,	88%	86%	88%	83%	85%	79%
	PRDX3, MTHFD2, PSME2, GBP1, TK1,
	GMFB, DLGAP4, TYMS, CTSS, LMAN1,
	CDC40, SLC4A4, CXCL9, IRF8, CXCL10,
	FAS, PLK4, TRIM25, SLC25A11, C1QBP,
	NDUFA9, WHSC1, CA2, HNRPD, ME2,
	CXCL11, GZMB, TLK1, RBM25, AK2,
	hCAP-D3, ATP5A1, CDC42BPA, BAZ1A,
	AGPAT5, MARCH5, SEC10L1, PBK,
	TRMT5, KLHL24, STAT1
265	HNRPD, WARS, EPAS1, PAICS, EIF4E,	92%	90%	85%	76%	69%	76%
	SFPQ, PRDX3, MTHFD2, PSME2, TK1,
	GMFB, DLGAP4, TYMS, USP4, CTSS,
	LMAN1, ARF6, CDC40, SLC4A4, CXCL9,
	IRF8, CXCL10, FAS, PLK4, CHEK1,
	TRIM25, KITLG, C1QBP, NDUFA9,
	KPNB1, SLC25A11, WHSC1, ME2, GZMB,
	TLK1, CXCL11, RBM25, AK2,
	CAMSAP1L1, AGPAT5, FLJ10534,
	SEC10L1, PBK, BRIP1, KLHL24, STAT1
266	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	77%	86%	88%	76%	85%	79%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, USP4, TES, CTSS, MAD2L1,
	SLC4A4, CXCL9, IRF8, CXCL10, FAS,
	PLK4, TRIM25, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	CXCL11, GZMB, RBM25, AK2, ATP5A1,
	RBBP4, AGPAT5, MARCH5, SEC10L1,
	PBK, HNRPD, BRIP1, TRMT5, KLHL24,
	ETNK1, STAT1
267	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	85%	83%	85%	79%	81%	76%
	PSME2, GMFB, DLGAP4, TYMS, TES,
	LMAN1, DCK, ARF6, CDC40, SLC4A4,
	CXCL9, IRF8, GTSE1, CXCL10, FAS,
	CHEK1, SLC25A11, C1QBP, NDUFA9,
	WHSC1, C17orf25, CA2, ME2, CXCL11,
	IFT20, RBM25, AK2, NUP210, SOCS6,
	CDC42BPA, SFRS2, RBBP4, BAZ1A,
	FLJ10534, MARCH5, FLJ13220, PBK,
	PSAT1, HNRPD, KLHL24, STAT1
268	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	88%	93%	92%	76%	81%	72%
	PRDX3, MTHFD2, PSME2, MCM6, GBP1,
	GMFB, DLGAP4, TYMS, USP4, ARF6,
	CDC40, SLC4A4, IRF8, GTSE1, CXCL10,
	FAS, HNRPA3P1, TRIM25, KITLG,
	NDUFA9, SLC25A11, CA2, ME2, CXCL11,
	GZMB, TLK1, RBM25, AK2, hCAP-D3,
	CDC42BPA, AGPAT5, FLJ10534,
	MARCH5, SEC10L1, FLJ13220, PBK,
	PSAT1, BRIP1, TRMT5, STAT1
269	HNRPD, WARS, SFRS2, EIF4E, PRDX3,	81%	79%	92%	76%	81%	69%
	MTHFD2, PSME2, MCM6, TK1, GMFB,
	DLGAP4, TYMS, USP4, ARF6, CDC40,
	SLC4A4, CXCL9, GTSE1, CXCL10,
	HNRPA3P1, KITLG, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	FUT4, CXCL11, GZMB, RBM25, AK2,
	CDC42BPA, FAS, RBBP4, BAZ1A,
	SEC10L1, FLJ13220, PBK, PSAT1,
	KLHL24, ETNK1, STAT1
270	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	88%	86%	88%	79%	85%	72%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, CTSS, ARF6, MAD2L1,
	CDC40, CXCL9, IRF8, GTSE1, CXCL10,
	FAS, CHEK1, HNRPA3P1, TRIM25, KITLG,
	SLC25A11, NDUFA9, KPNB1, WHSC1,
	CA2, ME2, FUT4, CXCL11, GZMB,
	RBM25, AK2, CDC42BPA, BAZ1A,
	AGPAT5, DKFZp762E1312, SEC10L1, PBK,
	TRMT5, KLHL24, ETNK1, STAT1
271	WARS, SFRS2, EPAS1, STAT1, EIF4E,	77%	69%	92%	79%	81%	69%
	MTHFD2, PSME2, MCM6, TK1, GMFB,
	DLGAP4, TYMS, USP4, LMAN1, ARF6,
	MAD2L1, CDC40, SLC4A4, CXCL9, IRF8,
	GTSE1, CXCL10, PLK4, C1QBP, NDUFA9,
	SLC25A11, WHSC1, CA2, HNRPD, ME2,
	FUT4, GZMB, RBM25, AK2, ATP5A1,
	CDC42BPA, FAS, AGPAT5, FLJ10534,
	SEC10L1, FLJ13220, PBK, BRIP1, TRMT5,
	KLHL24, ETNK1
272	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	73%	83%	92%	83%	85%	76%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, USP4, CTSS, LMAN1,
	DCK, SLC4A4, CXCL9, IRF8, CXCL10,
	FAS, HNRPA3P1, KITLG, C1QBP,
	NDUFA9, SLC25A11, CA2, ME2, FUT4,
	IFT20, RBBP4, TLK1, CXCL11, RBM25,
	BRRN1, CDC42BPA, AGPAT5, FLJ10534,
	MARCH5, SEC10L1, PBK, BRIP1, TRMT5,
	KLHL24, ETNK1, STAT1
273	WARS, SFRS2, EPAS1, STAT1, EIF4E,	88%	83%	85%	83%	77%	79%
	MTHFD2, PSME2, GBP1, TK1, GMFB,
	DLGAP4, TYMS, USP4, ARF6, CXCL9,
	IRF8, RABIF, CXCL10, FAS, PLK4,
	CHEK1, KITLG, SLC25A11, C1QBP,
	NDUFA9, WHSC1, CA2, ME2, CXCL11,
	IFT20, RBBP4, TLK1, RBM25, ATP5A1,
	CDC42BPA, FLJ13220, PBK, HNRPD,
	BRIP1, TRMT5, KLHL24, ETNK1
274	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	81%	86%	88%	83%	85%	76%
	PRDX3, MTHFD2, PSME2, GBP1, GMFB,
	DLGAP4, TYMS, TES, DCK, MAD2L1,
	CXCL9, CXCL10, FAS, PLK4, HNRPA3P1,
	KITLG, SLC25A11, NDUFA9, WHSC1,
	C17orf25, CA2, ME2, IFT20, RBBP4,
	CXCL11, SLC4A4, RBM25, NUP210,
	CAMSAP1L1, BRRN1, CDC42BPA,
	DDAH2, AGPAT5, FLJ10534, MARCH5,
	SEC10L1, FLJ13220, PBK, TRMT5,
	KLHL24, ETNK1, STAT1
275	WARS, SFRS2, PAICS, EIF4E, MTHFD2,	73%	86%	77%	83%	69%	79%
	PSME2, MCM6, GBP1, TK1, GMFB,
	DLGAP4, TYMS, USP4, TES, LMAN1,
	CDC40, CXCL9, CXCL10, PLK4, TRIM25,
	KITLG, SLC25A11, C1QBP, NDUFA9,
	C17orf25, HNRPD, ME2, CXCL11, IFT20,
	TLK1, SLC4A4, RBM25, hCAP-D3,
	ATP5A1, DDAH2, FAS, AGPAT5,
	FLJ10534, MARCH5, SEC10L1, FLJ13220,
	PBK, PSAT1, BRIP1, KLHL24, STAT1
276	HNRPD, WARS, SFRS2, STAT1, EIF4E,	85%	79%	88%	79%	81%	79%
	PRDX3, MTHFD2, PSME2, MCM6, TK1,
	GMFB, DLGAP4, TYMS, USP4, DCK,
	ARF6, CDC40, CXCL9, IRF8, CXCL10,
	FAS, PLK4, TRIM25, KITLG, C1QBP,
	NDUFA9, SLC25A11, WHSC1, CA2, ME2,
	CXCL11, GZMB, RBBP4, TLK1, RBM25,
	AK2, NUP210, ATP5A1, AGPAT5,
	MARCH5, SEC10L1, PBK, BRIP1, TRMT5
277	HNRPD, WARS, SFRS2, EPAS1, STAT1,	81%	83%	88%	76%	77%	69%
	EIF4E, PRDX3, MTHFD2, PSME2, MCM6,
	GBP1, GMFB, DLGAP4, TYMS, TES,
	CTSS, LMAN1, DCK, SLC4A4, CXCL9,
	GTSE1, CXCL10, PLK4, CHEK1, TRIM25,
	C1QBP, NDUFA9, KPNB1, WHSC1,
	C17orf25, ME2, CXCL11, RBM25, BRRN1,
	ATP5A1, CDC42BPA, DDAH2, FAS,
	AGPAT5, MARCH5, PBK, BRIP1, TRMT5,
	KLHL24, ETNK1
278	WARS, STAT1, EIF4E, SFPQ, PRDX3,	77%	72%	88%	83%	77%	79%
	MTHFD2, MCM6, TK1, GMFB, DLGAP4,
	TYMS, TES, CTSS, MAD2L1, CDC40,
	SLC4A4, CXCL9, RABIF, CXCL10, FAS,
	KITLG, SLC25A11, C1QBP, NDUFA9,
	C17orf25, CA2, HNRPD, ME2, GZMB,
	TLK1, CXCL11, RBM25, BRRN1,
	CDC42BPA, SFRS2, DDAH2, AGPAT5,
	SEC10L1, PBK, PSAT1, BRIP1, TRMT5,
	KLHL24
279	HNRPD, WARS, EPAS1, STAT1, EIF4E,	77%	86%	92%	76%	77%	76%
	SFPQ, PRDX3, MTHFD2, PSME2, MCM6,
	TK1, GMFB, DLGAP4, TYMS, USP4, TES,
	DCK, ARF6, CDC40, SLC4A4, CXCL9,
	RABIF, CXCL10, FAS, TRIM25, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	GZMB, TLK1, CXCL11, RBM25, AK2,
	hCAP-D3, CDC42BPA, DDAH2, RBBP4,
	FLJ10534, SEC10L1, FLJ13220, PBK,
	PSAT1, BRIP1, KLHL24
280	WARS, SFRS2, STAT1, EIF4E, MTHFD2,	81%	79%	92%	79%	85%	72%
	PSME2, MCM6, GBP1, TK1, GMFB,
	DLGAP4, TYMS, USP4, TES, CTSS,
	LMAN1, ARF6, CDC40, SLC4A4, CXCL9,
	CXCL10, FAS, PLK4, KITLG, C1QBP,
	KPNB1, WHSC1, CA2, ME2, FUT4, GZMB,
	CXCL11, RBM25, AK2, CDC42BPA,
	RBBP4, BAZ1A, AGPAT5, MARCH5,
	SEC10L1, PBK, HNRPD, BRIP1, KLHL24,
	ETNK1
281	HNRPD, WARS, SFRS2, EPAS1, STAT1,	85%	79%	77%	86%	73%	76%
	EIF4E, PRDX3, MTHFD2, PSME2, TK1,
	GMFB, DLGAP4, TYMS, CTSS, LMAN1,
	DCK, CDC40, SLC4A4, CXCL9, IRF8,
	CXCL10, TRIM25, SLC25A11, C1QBP,
	NDUFA9, KPNB1, WHSC1, ME2, CXCL11,
	TLK1, RBM25, hCAP-D3, CDC42BPA, FAS,
	BAZ1A, AGPAT5, SEC10L1, FLJ13220,
	PBK, TRMT5, ETNK1
282	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	77%	83%	88%	83%	88%	86%
	PRDX3, MTHFD2, PSME2, GBP1, GMFB,
	DLGAP4, TYMS, TES, CTSS, LMAN1,
	MAD2L1, SLC4A4, CXCL9, CXCL10, FAS,
	CHEK1, SLC25A11, C1QBP, NDUFA9,
	KPNB1, WHSC1, C17orf25, CA2, ME2,
	FUT4, CXCL11, TLK1, RBM25, hCAP-D3,
	ATP5A1, CDC42BPA, DDAH2, AGPAT5,
	FLJ10534, DKFZp762E1312, SEC10L1,
	FLJ13220, PBK, TRMT5, STAT1
283	WARS, SFRS2, PAICS, EIF4E, PRDX3,	81%	83%	85%	76%	85%	72%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, TES, ARF6, CDC40, CXCL9,
	CXCL10, FAS, PLK4, TRIM25, SLC25A11,
	C1QBP, NDUFA9, WHSC1, C17orf25, CA2,
	ME2, FUT4, IFT20, SLC4A4, CXCL11,
	RBM25, AK2, BRRN1, ATP5A1,
	CDC42BPA, AGPAT5, MARCH5, SEC10L1,
	FLJ13220, PBK, HNRPD, BRIP1, TRMT5,
	KLHL24, ETNK1, STAT1
284	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	81%	76%	88%	79%	85%	72%
	PRDX3, MTHFD2, PSME2, GBP1, TK1,
	GMFB, DLGAP4, TYMS, USP4, LMAN1,
	ARF6, SLC4A4, CXCL9, IRF8, CXCL10,
	FAS, KITLG, C1QBP, NDUFA9, SLC25A11,
	WHSC1, C17orf25, CA2, ME2, GZMB,
	CXCL11, RBM25, AK2, hCAP-D3,
	CDC42BPA, DDAH2, RBBP4, AGPAT5,
	MARCH5, DKFZp762E1312, SEC10L1,
	FLJ13220, PBK, BRIP1, TRMT5, KLHL24,
	STAT1
285	WARS, SFRS2, EPAS1, STAT1, EIF4E,	85%	86%	92%	76%	81%	72%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, USP4, CTSS, DCK, ARF6,
	CDC40, SLC4A4, CXCL9, CXCL10, FAS,
	CHEK1, TRIM25, SLC25A11, C1QBP,
	C17orf25, CA2, ME2, GZMB, IFT20,
	RBBP4, CXCL11, RBM25, AK2, NUP210,
	SOCS6, DDAH2, AGPAT5, FLJ10534,
	MARCH5, DKFZp762E1312, SEC10L1,
	PBK, HNRPD, TRMT5
286	WARS, EPAS1, STAT1, PAICS, EIF4E,	73%	76%	81%	79%	73%	66%
	PRDX3, MTHFD2, PSME2, TK1, DLGAP4,
	TYMS, MAD2L1, CDC40, CXCL9, IRF8,
	CXCL10, FAS, TRIM25, KITLG, C1QBP,
	NDUFA9, SLC25A11, WHSC1, C17orf25,
	HNRPD, ME2, CXCL11, IFT20, RBBP4,
	SLC4A4, RBM25, AK2, NUP210, SOCS6,
	CDC42BPA, BAZ1A, AGPAT5, SEC10L1,
	FLJ13220, PBK, PSAT1, BRIP1, TRMT5
287	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	88%	90%	88%	79%	77%	79%
	PSME2, GMFB, DLGAP4, TYMS, CTSS,
	ARF6, MAD2L1, CDC40, CXCL9, CXCL10,
	FAS, TRIM25, SLC25A11, C1QBP,
	NDUFA9, KPNB1, WHSC1, C17orf25, CA2,
	HNRPD, ME2, CXCL11, GZMB, IFT20,
	TLK1, SLC4A4, RBM25, CAMSAP1L1,
	hCAP-D3, RBBP4, BAZ1A, AGPAT5,
	MARCH5, FLJ13220, PBK, TRMT5,
	ETNK1, STAT1
288	HNRPD, WARS, SFRS2, EPAS1, STAT1,	81%	90%	85%	76%	85%	69%
	EIF4E, SFPQ, PRDX3, MTHFD2, PSME2,
	TK1, GMFB, DLGAP4, TYMS, ARF6,
	CDC40, CXCL9, CXCL10, FAS, SLC25A11,
	NDUFA9, WHSC1, C17orf25, CA2, ME2,
	CXCL11, IFT20, SLC4A4, RBM25, AK2,
	SOCS6, DDAH2, RBBP4, BAZ1A,
	DKFZp762E1312, FLJ13220, PBK, PSAT1,
	BRIP1, ETNK1
289	WARS, SFRS2, EPAS1, STAT1, PAICS,	77%	86%	88%	83%	73%	69%
	EIF4E, PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, USP4, CTSS, LMAN1,
	CDC40, CXCL9, IRF8, RABIF, CXCL10,
	FAS, TRIM25, SLC25A11, C1QBP, WHSC1,
	C17orf25, CA2, HNRPD, ME2, CXCL11,
	GZMB, TLK1, RBM25, CAMSAP1L1,
	hCAP-D3, CDC42BPA, BAZ1A, AGPAT5,
	MARCH5, DKFZp762E1312, FLJ13220,
	PBK, PSAT1, BRIP1, KLHL24
290	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	85%	83%	85%	83%	81%	72%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	USP4, ARF6, MAD2L1, SLC4A4, CXCL9,
	IRF8, CXCL10, FAS, TRIM25, SLC25A11,
	NDUFA9, KPNB1, WHSC1, C17orf25, CA2,
	ME2, GZMB, IFT20, RBBP4, CXCL11,
	RBM25, AK2, BRRN1, CDC42BPA,
	AGPAT5, FLJ10534, MARCH5, SEC10L1,
	FLJ13220, PBK, HNRPD, BRIP1, KLHL24,
	ETNK1, STAT1
291	HNRPD, WARS, SFRS2, EPAS1, STAT1,	85%	86%	92%	79%	85%	86%
	EIF4E, SFPQ, PRDX3, MTHFD2, GMFB,
	DLGAP4, TYMS, USP4, TES, CTSS, ARF6,
	MAD2L1, CDC40, CXCL9, CXCL10, FAS,
	PLK4, CHEK1, KITLG, SLC25A11,
	NDUFA9, KPNB1, CA2, ME2, FUT4,
	CXCL11, GZMB, TLK1, SLC4A4, RBM25,
	ATP5A1, DDAH2, MARCH5,
	DKFZp762E1312, PBK, BRIP1, KLHL24
292	WARS, SFRS2, EPAS1, STAT1, EIF4E,	81%	83%	85%	72%	69%	76%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, USP4, CTSS, CXCL9,
	IRF8, RABIF, CXCL10, FAS, PLK4,
	TRIM25, C1QBP, NDUFA9, SLC25A11,
	C17orf25, CA2, HNRPD, ME2, CXCL11,
	GZMB, SLC4A4, RBM25, ATP5A1,
	CDC42BPA, DDAH2, MARCH5,
	DKFZp762E1312, SEC10L1, FLJ13220,
	PBK, PSAT1, BRIP1, KLHL24, ETNK1,
	UBD, GTSE1, MYO1B, TMED5, RBBP8
293	HNRPD, WARS, EIF4E, PRDX3, MTHFD2,	81%	79%	77%	79%	69%	72%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	MAD2L1, CXCL9, IRF8, CXCL10, FAS,
	SLC25A11, NDUFA9, WHSC1, ME2,
	CXCL11, IFT20, RBBP4, SLC4A4, RBM25,
	AK2, NUP210, CAMSAP1L1, ATP5A1,
	DDAH2, AGPAT5, MARCH5, SEC10L1,
	FLJ13220, PBK, PSAT1, BRIP1, STAT1,
	FLJ22471, LAPTM5, DEPDC1, INDO,
	YDD19
294	WARS, SFRS2, PSME2, GMFB, DLGAP4,	73%	79%	88%	79%	85%	76%
	TYMS, TES, CDC40, CXCL9, CXCL10,
	HNRPA3P1, C1QBP, SLC25A11, WHSC1,
	C17orf25, CA2, ME2, TLK1, SLC4A4,
	CXCL11, AK2, hCAP-D3, DDAH2, FAS,
	AGPAT5, FLJ10534, PSAT1, HNRPD,
	BRIP1, KLHL24, STAT1, IVD
295	WARS, SFRS2, EPAS1, EIF4E, SFPQ,	85%	86%	85%	76%	73%	76%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, LMAN1, CDC40, SLC4A4,
	CXCL9, IRF8, RABIF, CXCL10, FAS,
	PLK4, CHEK1, HNRPA3P1, TRIM25,
	SLC25A11, NDUFA9, KPNB1, WHSC1,
	CA2, HNRPD, ME2, GZMB, IFT20,
	CXCL11, RBM25, hCAP-D3, BAZ1A,
	AGPAT5, MARCH5, PBK, BRIP1, KLHL24,
	ETNK1, STAT1, TACC3, IL2RB, AK2
296	HNRPD, WARS, SFRS2, PAICS, EIF4E,	81%	86%	92%	86%	85%	76%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, CDC40, SLC4A4, CXCL9,
	CXCL10, HNRPA3P1, KITLG, C1QBP,
	NDUFA9, SLC25A11, WHSC1, CA2, ME2,
	FUT4, CXCL11, IFT20, RBBP4, RBM25,
	AK2, DDAH2, FAS, FLJ10534, SEC10L1,
	FLJ13220, PBK, BRIP1, TRMT5, KLHL24,
	STAT1, FEM1C, ITGB5
297	WARS, EIF4E, PSME2, GMFB, DLGAP4,	77%	79%	73%	86%	81%	86%
	TYMS, USP4, CDC40, SLC4A4, CXCL10,
	TRIM25, C1QBP, NDUFA9, SLC25A11,
	CA2, ME2, CXCL11, RBM25, CAMSAP1L1,
	ATP5A1, SOCS6, FLJ10534,
	DKFZp762E1312, SEC10L1, HNRPD,
	STAT1, LMAN1, LOC92249, NFS1
298	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	81%	76%	81%	72%	77%	76%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	USP4, TES, CTSS, DCK, MAD2L1, CXCL9,
	GTSE1, CXCL10, FAS, HNRPA3P1, KITLG,
	C1QBP, NDUFA9, SLC25A11, WHSC1,
	CA2, HNRPD, ME2, FUT4, CXCL11,
	SLC4A4, RBM25, CDC42BPA, DDAH2,
	RBBP4, FLJ10534, MARCH5, SEC10L1,
	FLJ13220, PBK, BRIP1, ETNK1, STAT1,
	ZWINT, ZG16, TPRT, PURA
299	HNRPD, WARS, STAT1, EIF4E, SFPQ,	85%	79%	81%	69%	77%	72%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, MAD2L1, SLC4A4,
	CXCL9, CXCL10, FAS, NDUFA9, WHSC1,
	ME2, GZMB, TLK1, CXCL11, RBM25,
	AGPAT5, FLJ13220, KLHL24, SLAMF8,
	PBX1, CAP350
300	HNRPD, WARS, STAT1, EIF4E, PRDX3,	77%	79%	85%	76%	85%	79%
	MTHFD2, PSME2, GBP1, TK1, GMFB,
	DLGAP4, TYMS, USP4, LMAN1, DCK,
	ARF6, CXCL9, CXCL10, FAS, TRIM25,
	KITLG, C1QBP, NDUFA9, KPNB1,
	SLC25A11, WHSC1, CA2, ME2, FUT4,
	CXCL11, GZMB, IFT20, SLC4A4, RBM25,
	BRRN1, ATP5A1, SFRS2, DDAH2, RBBP4,
	SEC10L1, FLJ13220, PBK, PSAT1,
	KLHL24, ETNK1, FLJ20273, VAPB,
	LARP4, CD74, BTN2A2
301	WARS, SFRS2, EPAS1, EIF4E, SFPQ,	81%	76%	88%	69%	77%	69%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, USP4, CTSS, CDC40,
	SLC4A4, CXCL9, IRF8, CXCL10, FAS,
	PLK4, CHEK1, TRIM25, KITLG,
	SLC25A11, C1QBP, NDUFA9, WHSC1,
	HNRPD, ME2, CXCL11, GZMB, RBBP4,
	RBM25, CAMSAP1L1, BRRN1,
	CDC42BPA, AGPAT5, FLJ10534, SEC10L1,
	PBK, BRIP1, KLHL24, ETNK1, STAT1,
	H2AFZ, PGGT1B
302	WARS, EIF4E, MTHFD2, PSME2, GBP1,	85%	86%	88%	83%	81%	79%
	GMFB, DLGAP4, TYMS, CDC40, SLC4A4,
	CXCL10, FAS, CHEK1, HNRPA3P1,
	KITLG, SLC25A11, CA2, ME2, FUT4,
	CXCL11, IFT20, TLK1, RBM25, AK2,
	SFRS2, TRMT5, KLHL24, STAT1, FKBP9
303	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	77%	79%	88%	79%	81%	76%
	PRDX3, MTHFD2, PSME2, MCM6, TK1,
	DLGAP4, TYMS, TES, MAD2L1, CDC40,
	CXCL9, CXCL10, FAS, PLK4, CHEK1,
	TRIM25, C1QBP, NDUFA9, WHSC1, CA2,
	ME2, CXCL11, GZMB, RBBP4, SLC4A4,
	RBM25, CAMSAP1L1, DDAH2, AGPAT5,
	MARCH5, SEC10L1, PBK, BRIP1, TRMT5,
	ETNK1, STAT1, CHAF1A, ITGB5,
	HNRPDL
304	HNRPD, WARS, SFRS2, MTHFD2, PSME2,	81%	79%	81%	83%	81%	72%
	TK1, GMFB, DLGAP4, TYMS, LMAN1,
	DCK, MAD2L1, CXCL9, CXCL10, FAS,
	KITLG, KPNB1, SLC25A11, WHSC1, ME2,
	CXCL11, IFT20, SLC4A4, RBM25, BRRN1,
	ATP5A1, CDC42BPA, BAZ1A, MARCH5,
	SEC10L1, PBK, PSAT1, BRIP1, KLHL24,
	STAT1, RBM28
305	HNRPD, WARS, SFRS2, EIF4E, MTHFD2,	77%	83%	77%	83%	88%	79%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	CDC40, CXCL9, CXCL10, PLK4,
	HNRPA3P1, TRIM25, SLC25A11, KPNB1,
	ME2, SLC4A4, RBM25, hCAP-D3, FAS,
	RBBP4, BAZ1A, DKFZp762E1312,
	SEC10L1, KLHL24, STAT1, PSME1, BUB3,
	SOCS6
306	WARS, EPAS1, STAT1, EIF4E, MTHFD2,	73%	79%	85%	79%	81%	76%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	TES, CTSS, ARF6, SLC4A4, CXCL9,
	RABIF, CXCL10, FAS, PLK4, KITLG,
	SLC25A11, C1QBP, NDUFA9, KPNB1,
	WHSC1, CA2, HNRPD, ME2, FUT4,
	CXCL11, IFT20, RBM25, CAMSAP1L1,
	SOCS6, DDAH2, AGPAT5, FLJ10534,
	MARCH5, SEC10L1, FLJ13220, PBK,
	BRIP1, KLHL24, ETNK1, RPS2, CHAF1A,
	LGALS3BP
307	WARS, SFRS2, MTHFD2, PSME2, GMFB,	85%	93%	85%	83%	81%	83%
	DLGAP4, TYMS, CXCL9, GTSE1, RABIF,
	CXCL10, HNRPA3P1, TRIM25, KITLG,
	C1QBP, NDUFA9, WHSC1, CA2, ME2,
	FUT4, RBM25, hCAP-D3, ATP5A1,
	DDAH2, FAS, STAT1, CDCA8, HMGB3
308	WARS, MTHFD2, PSME2, GBP1,	81%	76%	81%	83%	77%	69%
	MAD2L1, CXCL9, IRF8, CXCL10, CHEK1,
	KITLG, ME2, CXCL11, IFT20, RBM25,
	AK2, ATP5A1, FAS, AGPAT5, SEC10L1,
	FLJ13220, HNRPD, KLHL24, ETNK1,
	STAT1, ECGF1
309	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	81%	83%	88%	76%	73%	76%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, TES, CDC40, SLC4A4, CXCL9,
	GTSE1, CXCL10, FAS, PLK4, CHEK1,
	KITLG, C1QBP, NDUFA9, SLC25A11,
	WHSC1, C17orf25, ME2, FUT4, CXCL11,
	IFT20, RBBP4, RBM25, AK2, NUP210,
	BRRN1, CDC42BPA, AGPAT5, FLJ10534,
	MARCH5, SEC10L1, FLJ13220, PBK,
	TRMT5, ETNK1, STAT1, SELL, GART
310	WARS, SFRS2, EPAS1, STAT1, EIF4E,	73%	72%	85%	83%	69%	72%
	SFPQ, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, USP4, CTSS, ARF6,
	CDC40, CXCL9, GTSE1, CXCL10, FAS,
	PLK4, CHEK1, TRIM25, SLC25A11,
	C1QBP, NDUFA9, WHSC1, ME2, FUT4,
	CXCL11, IFT20, RBBP4, SLC4A4, RBM25,
	hCAP-D3, DDAH2, AGPAT5, FLJ10534,
	MARCH5, SEC10L1, FLJ13220, PSAT1,
	HNRPD, BRIP1, KLHL24, ETNK1, WFDC1,
	YTHDF3, K-ALPHA-1, PAWR
311	HNRPD, WARS, SFRS2, STAT1, EIF4E,	81%	83%	88%	83%	73%	79%
	PRDX3, MTHFD2, PSME2, TK1, GMFB,
	DLGAP4, TYMS, TES, LMAN1, MAD2L1,
	CDC40, CXCL9, IRF8, CXCL10, PLK4,
	HNRPA3P1, KITLG, C1QBP, NDUFA9,
	SLC25A11, WHSC1, ME2, FUT4, CXCL11,
	IFT20, RBM25, BRRN1, CDC42BPA, FAS,
	AGPAT5, DKFZp762E1312, SEC10L1,
	FLJ13220, PBK, BRIP1, KLHL24, SMC2L1,
	IRF1
312	WARS, EPAS1, STAT1, MTHFD2, PSME2,	73%	79%	81%	79%	77%	76%
	MCM6, GMFB, DLGAP4, TYMS, USP4,
	CTSS, LMAN1, CXCL9, IRF8, CXCL10,
	KITLG, C1QBP, NDUFA9, SLC25A11,
	ME2, SLC4A4, RBM25, hCAP-D3, SOCS6,
	FAS, RBBP4, BAZ1A, AGPAT5, PSAT1,
	BRIP1, ETNK1, LPP, PPM1D, LAP3,
	TXNDC
313	WARS, EIF4E, PRDX3, PSME2, TK1,	77%	76%	85%	79%	77%	83%
	GMFB, DLGAP4, TYMS, LMAN1,
	CXCL10, SLC25A11, C1QBP, NDUFA9,
	KPNB1, C17orf25, CA2, ME2, RBBP4,
	SLC4A4, RBM25, FAS, SEC10L1, PBK,
	HNRPD, ETNK1, STAT1, KIAA0828,
	SPCS3, NARS
314	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	81%	76%	85%	79%	81%	79%
	SFPQ, PRDX3, MTHFD2, PSME2, MCM6,
	TK1, GMFB, DLGAP4, TYMS, USP4,
	LMAN1, ARF6, CDC40, SLC4A4, CXCL9,
	IRF8, CXCL10, FAS, PLK4, KITLG,
	C1QBP, NDUFA9, SLC25A11, WHSC1,
	CA2, ME2, GZMB, CXCL11, RBM25,
	CAMSAP1L1, CDC42BPA, FLJ10534,
	MARCH5, FLJ13220, PBK, PSAT1, BRIP1,
	KLHL24, STAT1, NUP160, HLA-E
315	WARS, EIF4E, SFPQ, PRDX3, MTHFD2,	73%	79%	85%	83%	77%	72%
	MCM6, GMFB, DLGAP4, TYMS, CDC40,
	CXCL9, CXCL10, CHEK1, HNRPA3P1,
	C1QBP, SLC25A11, WHSC1, CA2, ME2,
	CXCL11, SLC4A4, RBM25, AK2, SFRS2,
	FAS, MARCH5, FLJ13220, KLHL24,
	ETNK1, STAT1, SOCS1
316	WARS, EIF4E, MTHFD2, PSME2, GMFB,	81%	83%	81%	79%	85%	76%
	DLGAP4, USP4, DCK, CDC40, CXCL9,
	CXCL10, FAS, SLC25A11, C1QBP, KPNB1,
	WHSC1, CA2, ME2, FUT4, CXCL11,
	RBM25, DDAH2, SEC10L1, PBK, HNRPD,
	TRMT5, KLHL24, STAT1, PPA2, GTSE1,
	TNFRSF11A, RYK
317	WARS, SFRS2, EPAS1, PSME2, TK1,	77%	90%	85%	79%	85%	83%
	GMFB, DLGAP4, TYMS, CTSS, LMAN1,
	CDC40, SLC4A4, CXCL9, IRF8, CXCL10,
	PLK4, CHEK1, SLC25A11, C1QBP, KPNB1,
	WHSC1, CA2, ME2, GZMB, TLK1,
	CXCL11, RBM25, hCAP-D3, FAS, RBBP4,
	FLJ10534, MARCH5, HNRPD, STAT1,
	KIF2C, HAT1
318	WARS, EIF4E, PRDX3, PSME2, GBP1,	69%	83%	77%	86%	81%	83%
	TYMS, LMAN1, CXCL9, CXCL10, FAS,
	CHEK1, SLC25A11, NDUFA9, CA2, ME2,
	RBBP4, TLK1, CXCL11, SLC4A4, BRRN1,
	PBK, HNRPD, STAT1, TGFB2
319	WARS, SFRS2, EPAS1, EIF4E, SFPQ,	92%	90%	88%	79%	73%	79%
	PRDX3, MTHFD2, PSME2, TK1, DLGAP4,
	TYMS, LMAN1, SLC4A4, CXCL9,
	CXCL10, PLK4, SLC25A11, WHSC1,
	C17orf25, CA2, ME2, CXCL11, GZMB,
	IFT20, RBM25, NUP210, CAMSAP1L1,
	ATP5A1, FAS, RBBP4, AGPAT5, FLJ10534,
	PBK, PSAT1, HNRPD, STAT1, HLA-DMB
320	SFRS2, EIF4E, PRDX3, MTHFD2, PSME2,	73%	86%	73%	76%	81%	79%
	DLGAP4, TYMS, CXCL10, FAS, PLK4,
	CHEK1, HNRPA3P1, TRIM25, SLC25A11,
	C1QBP, NDUFA9, CA2, ME2, CXCL11,
	SLC4A4, RBM25, ATP5A1, FLJ13220,
	PSAT1, BRIP1, STAT1, RIF1, SCC-112,
	U2AF2
321	HNRPD, WARS, STAT1, EIF4E, SFPQ,	77%	83%	81%	79%	81%	76%
	PRDX3, MTHFD2, PSME2, MCM6, TK1,
	GMFB, DLGAP4, TYMS, CTSS, LMAN1,
	DCK, CDC40, SLC4A4, CXCL9, CXCL10,
	FAS, PLK4, TRIM25, SLC25A11, NUUFA9,
	WHSC1, C17orf25, CA2, ME2, FUT4,
	CXCL11, IFT20, RBM25, AK2, BRRN1,
	SFRS2, DDAH2, MARCH5, SEC10L1,
	FLJ13220, PBK, PSAT1, BRIP1, KLHL24,
	CD8A, GTF2H2, C14orf156, BIRC5
322	HNRPD, WARS, SFRS2, EPAS1, STAT1,	77%	79%	81%	83%	88%	76%
	EIF4E, SFPQ, PRDX3, MTHFD2, PSME2,
	MCM6, TK1, GMFB, DLGAP4, TYMS,
	USP4, CTSS, DCK, CXCL9, RABIF,
	CXCL10, FAS, TRIM25, NDUFA9, KPNB1,
	WHSC1, CA2, ME2, RBBP4, SLC4A4,
	RBM25, NUP210, hCAP-D3, SOCS6,
	BAZ1A, PBK, PSAT1, BRIP1, KLHL24,
	MAX, HADHSC
323	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	88%	83%	88%	76%	85%	79%
	TK1, GMFB, DLGAP4, TYMS, TES, CTSS,
	ARF6, MAD2L1, CDC40, CXCL9, IRF8,
	CXCL10, TRIM25, SLC25A11, C1QBP,
	NDUFA9, CA2, ME2, CXCL11, GZMB,
	SLC4A4, RBM25, AK2, NUP210, BRRN1,
	ATP5A1, DDAH2, FAS, MARCH5,
	SEC10L1, PBK, HNRPD, ETNK1, STAT1,
	AP1G1
324	WARS, STAT1, PRDX3, MTHFD2, PSME2,	73%	76%	81%	83%	85%	86%
	TK1, GMFB, DLGAP4, TYMS, CTSS,
	LMAN1, ARF6, MAD2L1, CDC40, CXCL9,
	CXCL10, FAS, PLK4, TRIM25, KITLG,
	C1QBP, NDUFA9, KPNB1, SLC25A11,
	WHSC1, CA2, HNRPD, ME2, FUT4,
	CXCL11, RBM25, CAMSAP1L1, hCAP-D3,
	BRRN1, ATP5A1, SOCS6, RBBP4,
	SEC10L1, PBK, BRIP1, KLHL24, ETNK1,
	MIS12, RBMS3, RUNX1, TTC19
325	HNRPD, WARS, SFRS2, EIF4E, MTHFD2,	85%	76%	92%	76%	85%	76%
	PSME2, GMFB, DLGAP4, TYMS, MAD2L1,
	CXCL10, FAS, HNRPA3P1, NDUFA9,
	SLC25A11, CA2, ME2, GZMB, CXCL11,
	hCAP-D3, RBBP4, BAZ1A, AGPAT5,
	FLJ10534, ETNK1, STAT1, JAK2, RNGTT
326	WARS, PAICS, EIF4E, SFPQ, MTHFD2,	73%	76%	81%	79%	77%	66%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	TES, ARF6, CDC40, CXCL9, RABIF,
	CXCL10, FAS, TRIM25, KITLG, C1QBP,
	NDUFA9, SLC25A11, WHSC1, ME2, FUT4,
	CXCL11, SLC4A4, RBM25, CAMSAP1L1,
	hCAP-D3, CDC42BPA, AGPAT5, PBK,
	PSAT1, HNRPD, BRIP1, STAT1, CDC2,
	ATP13A3, ZC3HAV1, FANCA
327	WARS, EIF4E, MTHFD2, PSME2, TK1,	77%	79%	85%	79%	69%	79%
	GMFB, TYMS, CXCL9, CXCL10, FAS,
	SLC25A11, WHSC1, C17orf25, CA2, ME2,
	RBM25, NUP210, BAZ1A, FLJ10534,
	MARCH5, SEC10L1, HNRPD, BRIP1,
	KLHL24, ETNK1, STAT1, SGPP1, CLCA4,
	FOXM1
328	HNRPD, WARS, SFRS2, EPAS1, STAT1,	88%	83%	85%	79%	81%	76%
	EIF4E, MTHFD2, PSME2, GBP1, TK1,
	GMFB, DLGAP4, TYMS, TES, LMAN1,
	DCK, ARF6, CDC40, CXCL9, CXCL10,
	FAS, PLK4, TRIM25, KITLG, SLC25A11,
	C1QBP, NDUFA9, KPNB1, WHSC1,
	C17orf25, CA2, ME2, TLK1, CXCL11,
	SLC4A4, RBM25, AK2, hCAP-D3, BAZ1A,
	AGPAT5, SEC10L1, FLJ13220, PBK,
	KLHL24, ETNK1, MCAM, BUB3, YTHDC2,
	APOL6, NUP210
329	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	88%	86%	85%	76%	77%	72%
	PSME2, MCM6, TK1, GMFB, DLGAP4,
	TYMS, USP4, TES, LMAN1, ARF6, CDC40,
	CXCL9, IRF8, GTSE1, RABIF, CXCL10,
	FAS, HNRPA3P1, C1QBP, NDUFA9,
	KPNB1, SLC25A11, WHSC1, C17orf25,
	CA2, HNRPD, ME2, CXCL11, GZMB,
	SLC4A4, RBM25, AK2, SOCS6,
	CDC42BPA, RBBP4, AGPAT5, MARCH5,
	SEC10L1, PSAT1, BRIP1, KLHL24, ETNK1,
	STAT1, CACNB3, BUB1B, ESPL1, H2AFZ
330	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	77%	79%	73%	79%	65%	69%
	PSME2, TK1, GMFB, DLGAP4, USP4,
	CXCL9, CXCL10, NDUFA9, KPNB1,
	SLC25A11, C17orf25, ME2, CXCL11,
	RBBP4, hCAP-D3, ATP5A1, FAS, AGPAT5,
	FLJ10534, PBK, PSAT1, HNRPD, BRIP1,
	ETNK1, STAT1, LHCGR
331	WARS, EIF4E, MTHFD2, PSME2, GBP1,	69%	72%	73%	86%	81%	76%
	DLGAP4, TYMS, CTSS, CDC40, SLC4A4,
	IRF8, CXCL10, FAS, TRIM25, SLC25A11,
	C1QBP, NDUFA9, ME2, FUT4, RBBP4,
	TLK1, RBM25, AK2, FLJ10534, MARCH5,
	FLJ13220, ETNK1, STAT1, C18orf9,
	C10orf3, AURKB, IFI16, PTPRC
332	HNRPD, WARS, PAICS, EIF4E, PRDX3,	77%	83%	88%	76%	77%	72%
	MTHFD2, TK1, GMFB, TYMS, CTSS,
	CXCL9, FAS, KITLG, NDUFA9, SLC25A11,
	C17orf25, ME2, FUT4, CXCL11, IFT20,
	SLC4A4, RBM25, CDC42BPA, SFRS2,
	AGPAT5, MARCH5, SEC10L1, FLJ13220,
	PBK, PSAT1, BRIP1, KLHL24, STAT1, AK2
333	WARS, EIF4E, PRDX3, MTHFD2, PSME2,	88%	86%	85%	66%	65%	79%
	MCM6, GMFB, DLGAP4, TYMS, USP4,
	CTSS, LMAN1, CXCL9, CXCL10, FAS,
	PLK4, HNRPA3P1, TRIM25, SLC25A11,
	WHSC1, ME2, CXCL11, IFT20, SLC4A4,
	RBM25, BAZ1A, AGPAT5,
	DKFZp762E1312, SEC10L1, PBK, HNRPD,
	BRIP1, ETNK1, STAT1, TOP2A, NUSAP1,
	USP14, PRF1, SCYL2
334	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	88%	93%	88%	86%	73%	83%
	PSME2, GMFB, DLGAP4, TYMS, USP4,
	CXCL10, FAS, WHSC1, C17orf25, ME2,
	IFT20, TLK1, CXCL11, SLC4A4, RBM25,
	AK2, CDC42BPA, HNRPD, ETNK1, STAT1,
	HLA-DRA, POLE2, PAICS, NUP210
335	HNRPD, WARS, EIF4E, PRDX3, MTHFD2,	81%	83%	92%	79%	88%	83%
	PSME2, GBP1, TK1, GMFB, DLGAP4,
	TYMS, USP4, LMAN1, CDC40, CXCL9,
	PLK4, SLC25A11, WHSC1, C17orf25, CA2,
	ME2, IFT20, CXCL11, RBM25, hCAP-D3,
	FAS, FLJ10534, DKFZp762E1312,
	SEC10L1, ETNK1, STAT1, WDHD1
336	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	77%	86%	85%	76%	81%	76%
	MTHFD2, PSME2, MCM6, GBP1, GMFB,
	DLGAP4, TYMS, USP4, CTSS, MAD2L1,
	CXCL9, IRF8, GTSE1, CXCL10, FAS,
	CHEK1, KITLG, SLC25A11, C1QBP,
	NDUFA9, WHSC1, C17orf25, CA2, ME2,
	CXCL11, GZMB, IFT20, TLK1, SLC4A4,
	RBM25, hCAP-D3, BAZ1A, MARCH5,
	DKFZp762E1312, SEC10L1, FLJ13220,
	PSAT1, HNRPD, BRIP1, KLHL24, ETNK1,
	STAT1, CUTL1, FAM64A
337	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	77%	79%	92%	69%	92%	79%
	PSME2, GMFB, DLGAP4, TYMS, CTSS,
	LMAN1, CDC40, CXCL9, IRF8, SLC25A11,
	C1QBP, NDUFA9, CA2, ME2, FUT4,
	CXCL11, RBM25, AK2, CDC42BPA, FAS,
	RBBP4, AGPAT5, MARCH5, SEC10L1,
	PBK, HNRPD, BRIP1, TRMT5, STAT1,
	TMEPAI, ZNF304, KLF7
338	WARS, SFRS2, EPAS1, STAT1, EIF4E,	81%	93%	92%	79%	81%	72%
	SFPQ, PRDX3, MTHFD2, PSME2, GBP1,
	GMFB, DLGAP4, TYMS, CDC40, SLC4A4,
	CXCL9, RABIF, CXCL10, FAS, CHEK1,
	TRIM25, SLC25A11, C1QBP, NDUFA9,
	WHSC1, CA2, HNRPD, ME2, GZMB,
	RBBP4, CXCL11, RBM25, AK2, NUP210,
	BRRN1, ATP5A1, CDC42BPA, AGPAT5,
	FLJ10534, MARCH5, SEC10L1, FLJ13220,
	PBK, PSAT1, BRIP1, MCM10, HLA-DMA,
	RABEP1, YARS, P15RS
339	WARS, STAT1, EIF4E, MTHFD2, PSME2,	73%	79%	77%	79%	69%	83%
	GMFB, DLGAP4, MAD2L1, FAS, PLK4,
	TRIM25, KITLG, SLC25A11, KPNB1,
	WHSC1, ME2, CXCL11, SLC4A4, RBM25,
	AK2, AGPAT5, KLHL24, CDKN1C, RFC5,
	FEN1, TFRC
340	WARS, EIF4E, MTHFD2, PSME2, TK1,	73%	79%	85%	83%	81%	72%
	GMFB, DLGAP4, TYMS, TES, LMAN1,
	DCK, CDC40, CXCL9, IRF8, GTSE1,
	CXCL10, FAS, PLK4, TRIM25, SLC25A11,
	C1QBP, NDUFA9, C17orf25, CA2, ME2,
	FUT4, CXCL11, SLC4A4, RBM25, AK2,
	CDC42BPA, RBBP4, BAZ1A, AGPAT5,
	FLJ10534, SEC10L1, FLJ13220, PBK,
	PSAT1, HNRPD, KLHL24, ETNK1, STAT1,
	SPFH1, SP3, CDC20, RAP1GDS1, M11S1
341	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	96%	90%	81%	72%	73%	72%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	USP4, LMAN1, ARF6, SLC4A4, CXCL9,
	CXCL10, FAS, TRIM25, KITLG, C1QBP,
	NDUFA9, SLC25A11, WHSC1, C17orf25,
	HNRPD, ME2, GZMB, TLK1, CXCL11,
	RBM25, AK2, BRRN1, DDAH2, AGPAT5,
	FLJ10534, SEC10L1, FLJ13220, PBK,
	PSAT1, TRMT5, KLHL24, ETNK1, STAT1,
	AVEN, HLA-DPA1, CD59
342	WARS, SFRS2, EPAS1, PRDX3, MTHFD2,	81%	83%	92%	79%	85%	79%
	TK1, GMFB, DLGAP4, TYMS, TES,
	LMAN1, SLC4A4, GTSE1, CXCL10, FAS,
	TRIM25, C1QBP, NDUFA9, SLC25A11,
	WHSC1, C17orf25, CA2, HNRPD, ME2,
	FUT4, CXCL11, R8M25, CDC42BPA,
	RBBP4, BAZ1A, AGPAT5, MARCH5,
	SEC10L1, BRIP1, TRMT5, KLHL24,
	STAT1, MPP5, EIF4A1, TRIP13, APOL3
343	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	69%	79%	85%	83%	88%	76%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	LMAN1, CDC40, CXCL9, CXCL10, FAS,
	CHEK1, HNRPA3P1, SLC25A11, C1QBP,
	WHSC1, CA2, HNRPD, ME2, CXCL11,
	TLK1, SLC4A4, RBM25, AK2, ATP5A1,
	SOCS6, BAZ1A, AGPAT5, MARCH5,
	DKFZp762E1312, SEC10L1, PBK, BRIP1,
	KLHL24, STAT1, GPR161, SGCD
344	WARS, SFRS2, EIF4E, PRDX3, PSME2,	77%	86%	92%	79%	88%	86%
	GMFB, DLGAP4, TYMS, USP4, MAD2L1,
	CDC40, SLC4A4, CXCL10, FAS, CHEK1,
	KITLG, NDUFA9, KPNB1, SLC25A11,
	CA2, HNRPD, ME2, FUT4, GZMB,
	CXCL11, RBM25, BRRN1, CDC42BPA,
	MARCH5, KLHL24, ETNK1, STAT1,
	ADH1C, WHSC1, HIP2
345	WARS, SFRS2, EPAS1, PAICS, EIF4E,	81%	86%	88%	83%	88%	72%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, USP4, DCK, ARF6, SLC4A4,
	CXCL9, RABIF, CXCL10, FAS, TRIM25,
	SLC25A11, C1QBP, NDUFA9, WHSC1,
	C17orf25, CA2, HNRPD, ME2, FUT4,
	GZMB, IFT20, CXCL11, RBM25, AK2,
	CAMSAP1L1, BRRN1, DDAH2, RBBP4,
	AGPAT5, PBK, PSAT1, BRIP1, KLHL24,
	STAT1, XPO7, TRAFD1, YTHDC2, RNF138
346	WARS, SFRS2, EPAS1, PRDX3, MTHFD2,	81%	83%	85%	76%	81%	72%
	PSME2, MCM6, DLGAP4, TYMS, USP4,
	CDC40, SLC4A4, CXCL9, RABIF, CXCL10,
	FAS, SLC25A11, C1QBP, NDUFA9,
	WHSC1, CA2, ME2, CXCL11, RBM25,
	NUP210, BRRN1, DDAH2, RBBP4, BAZ1A,
	DKFZp762E1312, SEC10L1, PSAT1,
	HNRPD, KLHL24, ETNK1, STAT1,
	ACADSB, AMIGO2, CCL5, KIAA0286
347	SFRS2, EPAS1, EIF4E, SFPQ, PRDX3,	81%	83%	92%	79%	85%	79%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, LMAN1, DCK, ARF6, CDC40,
	CXCL9, GTSE1, CXCL10, FAS, SLC25A11,
	KPNB1, WHSC1, CA2, HNRPD, ME2,
	CXCL11, SLC4A4, RBM25, AK2, ATP5A1,
	CDC42BPA, BAZ1A, FLJ10534, FLJ13220,
	PBK, BRIP1, KLHL24, STAT1, PSMB9,
	HBP1, CPD, AIM2
348	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	73%	86%	73%	86%	73%	79%
	MCM6, GMFB, DLGAP4, CDC40, CXCL10,
	CHEK1, KPNB1, CA2, ME2, RBBP4,
	CXCL11, SLC4A4, RBM25, CDC42BPA,
	FAS, FLJ10534, SEC10L1, FLJ13220,
	HNRPD, STAT1, TTK, YBX2, BCL7C, SI
349	WARS, SFRS2, STAT1, EIF4E, PRDX3,	88%	79%	96%	69%	88%	76%
	MTHFD2, TK1, GMFB, DLGAP4, TYMS,
	USP4, TES, CTSS, CXCL9, CXCL10, FAS,
	SLC25A11, KPNB1, C17orf25, ME2, GZMB,
	SLC4A4, NUP210, hCAP-D3, HNRPD,
	TRMT5, KLHL24, PRO2730
350	EPAS1, EIF4E, PRDX3, PSME2, GMFB,	73%	83%	92%	79%	81%	76%
	DLGAP4, TYMS, USP4, CTSS, SLC4A4,
	CXCL10, HNRPA3P1, KITLG, SLC25A11,
	WHSC1, CA2, HNRPD, ME2, FUT4,
	RBM25, CAMSAP1L1, FAS, AGPAT5,
	FLJ10534, MARCH5, SEC10L1, PSAT1,
	BRIP1, KLHL24, STAT1, MCM2, GGA2,
	SPAG5, VRK1, EBNA1BP2
351	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	85%	76%	88%	83%	88%	76%
	TK1, GMFB, DLGAP4, TYMS, LMAN1,
	MAD2L1, SLC4A4, CXCL9, RABIF,
	CXCL10, FAS, CHEK1, KITLG, SLC25A11,
	NDUFA9, C17orf25, CA2, ME2, IFT20,
	CXCL11, RBM25, hCAP-D3, CDC42BPA,
	AGPAT5, MARCH5, HNRPD, KLHL24,
	STAT1, MYCBP, GBP1, ITGA4, PBXIP1,
	CENPA
352	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	77%	79%	92%	76%	77%	76%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, TES, CTSS, ARF6,
	CDC40, SLC4A4, CXCL9, CXCL10, FAS,
	TRIM25, KITLG, NDUFA9, SLC25A11,
	C17orf25, CA2, ME2, FUT4, GZMB,
	CXCL11, BRRN1, SOCS6, CDC42BPA,
	BAZ1A, DKFZp762E1312, SEC10L1, PBK,
	PSAT1, BRIP1, TRMT5, ETNK1, STAT1,
	PPIG, NUP98, FUSIP1, SH3GLB1
353	WARS, SFRS2, EPAS1, EIF4E, PRDX3,	85%	83%	88%	79%	73%	72%
	MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, DCK, CDC40, CXCL9, GTSE1,
	RABIF, CXCL10, KITLG, C1QBP,
	NDUFA9, SLC25A11, C17orf25, CA2, ME2,
	GZMB, IFT20, SLC4A4, RBM25, DDAH2,
	FAS, AGPAT5, FLJ10534, MARCH5,
	FLJ13220, PBK, HNRPD, KLHL24, ETNK1,
	STAT1, C5orf4, KIF23, SSPN
354	HNRPD, WARS, SFRS2, STAT1, EIF4E,	85%	83%	92%	83%	81%	76%
	SFPQ, PSME2, GBP1, GMFB, DLGAP4,
	TYMS, CTSS, ARF6, CDC40, SLC4A4,
	CXCL10, FAS, C1QBP, NDUFA9,
	SLC25A11, WHSC1, CA2, ME2, IFT20,
	RBBP4, CXCL11, RBM25, NUP210,
	BAZ1A, AGPAT5, MARCH5, PBK,
	KLHL24, MAP2K4, UBE2L6
355	HNRPD, WARS, EIF4E, MTHFD2, MCM6,	88%	90%	73%	79%	73%	76%
	DLGAP4, TYMS, CDC40, CXCL9, CXCL10,
	FAS, TRIM25, C1QBP, ME2, CXCL11,
	RBM25, AK2, CDC42BPA, SEC10L1, PBK,
	KLHL24, ETNK1, STAT1, DNA2L, TAP2,
	SYNPO
356	HNRPD, WARS, EIF4E, MTHFD2, GBP1,	69%	83%	85%	83%	81%	79%
	GMFB, DLGAP4, TYMS, USP4, DCK,
	CDC40, CXCL9, IRF8, GTSE1, CXCL10,
	HNRPA3P1, TRIM25, C1QBP, NDUFA9,
	SLC25A11, WHSC1, CA2, ME2, FUT4,
	CXCL11, RBBP4, TLK1, SLC4A4, RBM25,
	AK2, NUP210, ATP5A1, SFRS2, FAS,
	AGPAT5, FLJ10534, MARCH5, SEC10L1,
	PBK, KLHL24, ETNK1, STAT1, EXOSC9,
	KIF15, FBXL14, ABCE1
357	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	85%	86%	88%	79%	81%	72%
	PSME2, MCM6, TK1, GMFB, DLGAP4,
	TYMS, TES, CTSS, LMAN1, CDC40,
	SLC4A4, CXCL9, IRF8, CXCL10, FAS,
	PLK4, HNRPA3P1, C1QBP, NDUFA9,
	SLC25A11, WHSC1, C17orf25, CA2,
	HNRPD, ME2, CXCL11, RBM25, AK2,
	CDC42BPA, RBBP4, AGPAT5, FLJ10534,
	SEC10L1, FLJ13220, PBK, BRIP1, STAT1,
	CCL5, FLJ20516, BUB1, MRPL42
358	HNRPD, WARS, EIF4E, MTHFD2, PSME2,	77%	83%	85%	79%	81%	69%
	GBP1, GMFB, DLGAP4, TYMS, USP4,
	ARF6, MAD2L1, CDC40, SLC4A4, CXCL9,
	CXCL10, FAS, PLK4, C1QBP, SLC25A11,
	WHSC1, CA2, ME2, CXCL11, RBBP4,
	RBM25, AK2, CDC42BPA, BAZ1A,
	AGPAT5, SEC10L1, PBK, PSAT1, BRIP1,
	ETNK1, STAT1, GZMA, EIF4A1, PSMA3,
	CD2, CCNB1
359	WARS, PSME2, GMFB, DLGAP4, TYMS,	77%	79%	81%	76%	77%	66%
	CDC40, CXCL9, GTSE1, CXCL10, FAS,
	TRIM25, SLC25A11, C1QBP, NDUFA9,
	WHSC1, C17orf25, ME2, CXCL11, RBM25,
	CAMSAP1L1, AGPAT5, FLJ13220, PSAT1,
	TRMT5, KLHL24, ETNK1, STAT1, RRM1,
	CXCL13, NKG7, MGAT2, LCP2
360	HNRPD, SFRS2, EPAS1, STAT1, EIF4E,	88%	90%	85%	79%	73%	76%
	MTHFD2, PSME2, TK1, GMFB, DLGAP4,
	TYMS, CXCL9, CXCL10, FAS, CHEK1,
	HNRPA3P1, KPNB1, SLC25A11, WHSC1,
	C17orf25, ME2, CXCL11, IFT20, TLK1,
	SLC4A4, RBM25, CDC42BPA, BAZ1A,
	AGPAT5, MARCH5, SEC10L1, PBK,
	PSAT1, KLHL24, C1orf112, TCF7L2,
	RARRES3, SERBP1, TBX2
361	HNRPD, WARS, EIF4E, SFPQ, MTHFD2,	81%	83%	88%	76%	77%	69%
	PSME2, GMFB, DLGAP4, TYMS, TES,
	CTSS, ARF6, CXCL9, IRF8, RABIF,
	CXCL10, FAS, PLK4, HNRPA3P1, KITLG,
	SLC25A11, C1QBP, NDUFA9, WHSC1,
	C17orf25, ME2, CXCL11, IFT20, TLK1,
	RBM25, AK2, NUP210, hCAP-D3,
	CDC42BPA, DDAH2, AGPAT5, FLJ10534,
	SEC10L1, PBK, KLHL24, STAT1, PTGER3,
	HCAP-G
362	HNRPD, WARS, SFRS2, EPAS1, STAT1,	81%	90%	85%	79%	77%	83%
	EIF4E, SFPQ, PRDX3, MTHFD2, PSME2,
	TK1, GMFB, DLGAP4, TYMS, CTSS,
	LMAN1, MAD2L1, CDC40, CXCL9, IRF8,
	CXCL10, KITLG, C1QBP, NDUFA9,
	SLC25A11, WHSC1, ME2, CXCL11, GZMB,
	IFT20, RBBP4, SLC4A4, RBM25, hCAP-D3,
	BRRN1, FAS, FLJ10534, SEC10L1, PSAT1,
	KLHL24, NUP50, MCCC2, RABGEF1
363	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	92%	90%	77%	83%	69%	72%
	GMFB, DLGAP4, TYMS, USP4, CDC40,
	CXCL9, CXCL10, FAS, HNRPA3P1,
	TRIM25, C1QBP, SLC25A11, ME2,
	CXCL11, IFT20, RBM25, AK2, hCAP-D3,
	CDC42BPA, RBBP4, BAZ1A,
	DKFZp762E1312, SEC10L1, PBK, HNRPD,
	ETNK1, STAT1, PSMA6, ZNF345, UBAP1
364	WARS, EPAS1, PAICS, EIF4E, MTHFD2,	77%	86%	88%	76%	85%	76%
	PSME2, GMFB, TYMS, TES, LMAN1,
	SLC4A4, CXCL9, RABIF, FAS, CHEK1,
	HNRPA3P1, TRIM25, SLC25A11, C1QBP,
	WHSC1, ME2, CDC42BPA, FLJ10534,
	SEC10L1, PBK, STAT1, ZBTB20, NAT2
365	WARS, SFRS2, EIF4E, MTHFD2, PSME2,	85%	86%	85%	76%	81%	69%
	GMFB, DLGAP4, TYMS, USP4, MAD2L1,
	CXCL9, CXCL10, FAS, C1QBP, NDUFA9,
	KPNB1, SLC25A11, WHSC1, CA2, ME2,
	IFT20, SLC4A4, RBM25, AK2, CDC42BPA,
	DDAH2, PSAT1, HNRPD, BRIP1, KLHL24,
	ETNK1, STAT1, HMMR, CTSL
366	WARS, EIF4E, PRDX3, MTHFD2, PSME2,	88%	83%	85%	72%	69%	76%
	GMFB, DLGAP4, TYMS, USP4, CTSS,
	DCK, CXCL9, CXCL10, FAS, TRIM25,
	WHSC1, C17orf25, CA2, ME2, FUT4, IFT20,
	CXCL11, SLC4A4, RBM25, CDC42BPA,
	RBBP4, AGPAT5, MARCH5, FLJ13220,
	PBK, HNRPD, TRMT5, KLHL24, ETNK1,
	STAT1, PBX1, ZDHHC3, CLEC2D
367	HNRPD, WARS, SFRS2, EIF4E, MTHFD2,	73%	83%	85%	83%	73%	66%
	PSME2, TK1, GMFB, DLGAP4, TYMS,
	TES, LMAN1, ARF6, CDC40, CXCL9, IRF8,
	GTSE1, RABIF, CXCL10, FAS, KITLG,
	C1QBP, NDUFA9, SLC25A11, WHSC1,
	ME2, TLK1, SLC4A4, CXCL11, RBM25,
	hCAP-D3, DDAH2, RBBP4, BAZ1A,
	AGPAT5, SEC10L1, PBK, TRMT5,
	KLHL24, ETNK1, STAT1, NEK2,
	KIAA0841, RNMT, C4orf16
368	WARS, SFRS2, EPAS1, STAT1, MTHFD2,	73%	83%	81%	79%	81%	72%
	PSME2, GMFB, DLGAP4, TYMS, TES,
	CDC40, SLC4A4, CXCL9, RABIF, CXCL10,
	FAS, PLK4, CHEK1, HNRPA3P1, TRIM25,
	C1QBP, KPNB1, SLC25A11, WHSC1, CA2,
	HNRPD, ME2, FUT4, RBBP4, CXCL11,
	RBM25, NUP210, SOCS6, CDC42BPA,
	FLJ10534, MARCH5, FLJ13220, PBK,
	PSAT1, BRIP1, KLHL24, APOL1, PDGFA,
	FBXO5, CACYBP, ABCE1
369	WARS, SFRS2, EPAS1, STAT1, PAICS,	88%	86%	81%	83%	81%	79%
	EIF4E, MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, USP4, DCK, CDC40, SLC4A4,
	CXCL9, GTSE1, CXCL10, PLK4,
	SLC25A11, NDUFA9, KPNB1, WHSC1,
	C17orf25, CA2, ME2, FUT4, IFT20, TLK1,
	CXCL11, RBM25, AK2, CDC42BPA,
	DDAH2, FAS, BAZ1A, AGPAT5, SEC10L1,
	FLJ13220, PBK, PSAT1, HNRPD, BRIP1,
	BMP5, ETNK1, PTGER3, VAMP4, CCNB2
370	WARS, EPAS1, PRDX3, MTHFD2, PSME2,	81%	79%	81%	79%	81%	76%
	TK1, GMFB, DLGAP4, TYMS, TES, CTSS,
	MAD2L1, CDC40, SLC4A4, CXCL9,
	GTSE1, RABIF, CXCL10, FAS, PLK4,
	TRIM25, KITLG, SLC25A11, C1QBP, CA2,
	ME2, CXCL11, RBBP4, TLK1, RBM25,
	AK2, BRRN1, SFRS2, BAZ1A, AGPAT5,
	FLJ13220, PSAT1, HNRPD, BRIP1,
	KLHL24, STAT1, TAP1, LCP2, ITGAL,
	CCNT2, FYB
371	HNRPD, WARS, PRDX3, MTHFD2,	88%	79%	85%	79%	73%	72%
	PSME2, MCM6, TK1, GMFB, DLGAP4,
	TYMS, DCK, ARF6, CXCL9, CXCL10,
	C1QBP, NDUFA9, SLC25A11, ME2, IFT20,
	CXCL11, RBM25, AK2, BRRN1, ATP5A1,
	CDC42BPA, SFRS2, FAS, BAZ1A,
	AGPAT5, FLJ13220, PBK, PSAT1, BRIP1,
	KLHL24, STAT1, NEIL3, PCDHGC3,
	NUSAP1
372	SFRS2, EPAS1, EIF4E, PRDX3, MTHFD2,	77%	79%	81%	83%	85%	79%
	PSME2, MCM6, TK1, GMFB, DLGAP4,
	TYMS, TES, DCK, MAD2L1, CXCL9, IRF8,
	CXCL10, FAS, TRIM25, KITLG, C1QBP,
	NDUFA9, SLC25A11, WHSC1, CA2,
	HNRPD, ME2, CXCL11, IFT20, RBBP4,
	SLC4A4, RBM25, AK2, CDC42BPA,
	DDAH2, BAZ1A, AGPAT5, FLJ10534,
	MARCH5, SEC10L1, FLJ13220, PBK,
	KLHL24, ETNK1, STAT1, TNFAIP2
373	WARS, STAT1, EIF4E, SFPQ, MTHFD2,	85%	86%	92%	79%	81%	72%
	PSME2, GMFB, DLGAP4, TYMS, ARF6,
	CDC40, SLC4A4, CXCL9, RABIF, CXCL10,
	FAS, SLC25A11, C1QBP, NDUFA9,
	KPNB1, WHSC1, C17orf25, CA2, ME2,
	FUT4, CXCL11, GZMB, TLK1, RBM25,
	AK2, FLJ10534, FLJ13220, HNRPD, BRIP1,
	GEMIN4, PTPRC
374	WARS, SFRS2, EPAS1, PAICS, EIF4E,	77%	90%	81%	76%	85%	76%
	MTHFD2, PSME2, MCM6, GBP1, GMFB,
	DLGAP4, TYMS, TES, CTSS, DCK,
	MAD2L1, CDC40, SLC4A4, CXCL9, IRF8,
	GTSE1, CXCL10, FAS, PLK4, TRIM25,
	KITLG, C1QBP, NDUFA9, KPNB1,
	SLC25A11, WHSC1, CA2, ME2, CXCL11,
	RBM25, AK2, hCAP-D3, CDC42BPA,
	DDAH2, AGPAT5, MARCH5, SEC10L1,
	FLJ13220, PBK, HNRPD, BRIP1, KLHL24,
	STAT1, APOBEC3G, KIF11, GBP2, RAB6A,
	ITGB5
375	WARS, EIF4E, MTHFD2, PSME2, MCM6,	73%	72%	85%	90%	81%	83%
	GMFB, DLGAP4, TYMS, MAD2L1, CDC40,
	CXCL9, CXCL10, FAS, SLC25A11, C1QBP,
	NDUFA9, ME2, FUT4, CXCL11, RBM25,
	hCAP-D3, BRRN1, MARCH5, SEC10L1,
	FLJ13220, HNRPD, STAT1, AP2B1, KIF2,
	K-ALPHA-1, GPHN
376	HNRPD, WARS, SFRS2, EPAS1, PAICS,	77%	83%	77%	86%	73%	86%
	EIF4E, PRDX3, MTHFD2, PSME2, GBP1,
	TK1, GMFB, DLGAP4, TYMS, USP4, CTSS,
	LMAN1, CXCL9, IRF8, RABIF, CXCL10,
	FAS, HNRPA3P1, KITLG, SLC25A11,
	C1QBP, NDUFA9, WHSC1, ME2, CXCL11,
	TLK1, SLC4A4, RBM25, ATP5A1, RBBP4,
	FLJ10534, MARCH5, FLJ13220, PSAT1,
	BRIP1, KLHL24, STAT1, KIF18A, KIF2C,
	NF2, DLG7, PSMA5
377	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	81%	90%	85%	90%	88%	72%
	PSME2, GMFB, DLGAP4, TYMS, CDC40,
	CXCL9, CXCL10, FAS, PLK4, TRIM25,
	KITLG, C1QBP, NDUFA9, SLC25A11,
	HNRPD, ME2, CXCL11, IFT20, RBM25,
	ATP5A1, DDAH2, AGPAT5, FLJ13220,
	PSAT1, BRIP1, KLHL24, STAT1, SLC4A4,
	CD7, DNM1L, RPL39, CDKN3
378	HNRPD, WARS, SFRS2, EPAS1, STAT1,	85%	90%	85%	72%	73%	79%
	EIF4E, PRDX3, MTHFD2, PSME2, TK1,
	DLGAP4, TYMS, USP4, LMAN1, DCK,
	MAD2L1, CDC40, SLC4A4, CXCL9,
	GTSE1, RABIF, CXCL10, FAS, PLK4,
	CHEK1, HNRPA3P1, TRIM25, C1QBP,
	NDUFA9, SLC25A11, WHSC1, ME2,
	CXCL11, GZMB, IFT20, RBBP4, TLK1,
	RBM25, AK2, ATP5A1, AGPAT5, KLHL24,
	ETNK1, CD3Z, DHX15, MTHFD1
379	WARS, STAT1, EIF4E, MTHFD2, PSME2,	81%	83%	77%	83%	77%	79%
	GMFB, DLGAP4, TYMS, LMAN1, DCK,
	SLC4A4, CXCL9, IRF8, RABIF, CXCL10,
	FAS, TRIM25, NDUFA9, SLC25A11,
	WHSC1, HNRPD, ME2, CXCL11, TLK1,
	RBM25, CAMSAP1L1, CDC42BPA, RBBP4,
	MARCH5, SEC10L1, FLJ13220, PSAT1,
	BRIP1, KLHL24, ETNK1, ATF6, RRM2,
	KPNA2
380	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	73%	83%	81%	86%	69%	72%
	MTHFD2, PSME2, GBP1, TK1, DLGAP4,
	TYMS, LMAN1, MAD2L1, CXCL9, IRF8,
	CXCL10, FAS, HNRPA3P1, KITLG,
	NDUFA9, KPNB1, SLC25A11, ME2,
	CXCL11, TLK1, SLC4A4, RBM25, AK2,
	AGPAT5, FLJ10534, MARCH5, SEC10L1,
	PBK, PSAT1, BRIP1, KLHL24, STAT1,
	BTN3A3
381	WARS, EIF4E, PRDX3, MTHFD2, PSME2,	85%	83%	92%	86%	85%	76%
	TK1, GMFB, DLGAP4, TYMS, USP4, TES,
	CDC40, CXCL9, CXCL10, FAS, KITLG,
	NDUFA9, SLC25A11, WHSC1, CA2, ME2,
	RBM25, AK2, ATP5A1, SEC10L1, PBK,
	HNRPD, BRIP1, KLHL24, STAT1, CHEK1,
	C20orf45, CKS2
382	WARS, SFRS2, EPAS1, EIF4E, MTHFD2,	92%	90%	81%	79%	73%	76%
	PSME2, GBP1, GMFB, DLGAP4, TYMS,
	USP4, ARF6, MAD2L1, CXCL9, RABIF,
	CXCL10, FAS, PLK4, CHEK1, HNRPA3P1,
	KITLG, SLC25A11, WHSC1, C17orf25,
	ME2, FUT4, CXCL11, IFT20, SLC4A4,
	RBM25, ATP5A1, CDC42BPA, RBBP4,
	MARCH5, SEC10L1, FLJ13220, PBK,
	PSAT1, ETNK1, STAT1, HMGN2, SFRS10
383	WARS, EPAS1, EIF4E, PRDX3, MTHFD2,	85%	83%	88%	76%	81%	72%
	PSME2, GBP1, GMFB, DLGAP4, TYMS,
	USP4, DCK, CDC40, CXCL9, IRF8, RABIF,
	CXCL10, FAS, PLK4, HNRPA3P1, TRIM25,
	KITLG, C1QBP, NDUFA9, SLC25A11,
	C17orf25, CA2, HNRPD, ME2, CXCL11,
	RBM25, SFRS2, DDAH2, RBBP4, AGPAT5,
	FLJ13220, PBK, ETNK1, STAT1, TMEM48
384	WARS, SFRS2, EPAS1, EIF4E, SFPQ,	88%	90%	88%	83%	81%	76%
	GMFB, DLGAP4, TYMS, USP4, SLC4A4,
	CXCL9, RABIF, CXCL10, FAS, KPNB1,
	CA2, ME2, FUT4, CXCL11, RBM25,
	CAMSAP1L1, KLHL24, STAT1, TRAF3IP3,
	SOS1
385	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	85%	86%	88%	79%	73%	79%
	PSME2, DLGAP4, TYMS, USP4, MAD2L1,
	SLC4A4, CXCL9, GTSE1, RABIF, CXCL10,
	FAS, HNRPA3P1, TRIM25, SLC25A11,
	NDUFA9, WHSC1, CA2, ME2, GZMB,
	TLK1, CXCL11, RBM25, AK2, BRRN1,
	ATP5A1, DDAH2, AGPAT5, MARCH5,
	SEC10L1, PBK, PSAT1, HNRPD, BRIP1,
	KLHL24, STAT1, C16orf30
386	WARS, SFRS2, PA1CS, EIF4E, PRDX3,	69%	76%	69%	86%	81%	86%
	MTHFD2, PSME2, MCM6, TK1, GMFB,
	DLGAP4, TYMS, LMAN1, CXCL9, IRF8,
	GTSE1, CXCL10, FAS, TRIM25, KITLG,
	SLC25A11, C1QBP, NDUFA9, KPNB1,
	WHSC1, HNRPD, ME2, CXCL11, IFT20,
	RBBP4, TLK1, SLC4A4, RBM25,
	CAMSAP1L1, ATP5A1, DDAH2, FLJ10534,
	MARCH5, DKFZp762E1312, SEC10L1,
	PBK, TRMT5, STAT1, PGD, ZNF148
387	HNRPD, WARS, EPAS1, PRDX3,	73%	86%	88%	83%	81%	83%
	MTHFD2, PSME2, TK1, DLGAP4, TYMS,
	USP4, TES, LMAN1, CXCL9, CXCL10,
	FAS, PLK4, TRIM25, C1QBP, SLC25A11,
	WHSC1, ME2, RBBP4, TLK1, SLC4A4,
	NUP210, SFRS2, SEC10L1, ETNK1, STAT1,
	SNRPC, RAC2
388	WARS, SFRS2, PAICS, EIF4E, MTHFD2,	73%	79%	73%	86%	77%	83%
	PSME2, GMFB, DLGAP4, TYMS, TES,
	LMAN1, CDC40, CXCL10, NDUFA9,
	KPNB1, SLC25A11, ME2, CXCL11,
	SLC4A4, RBM25, NUP210, hCAP-D3, FAS,
	RBBP4, ETNK1, STAT1, DHX40,
	KIAA0090
389	HNRPD, WARS, SFRS2, EPAS1, STAT1,	85%	86%	88%	76%	81%	83%
	EIF4E, MTHFD2, PSME2, GMFB, DLGAP4,
	TYMS, LMAN1, ARF6, CXCL10, FAS,
	PLK4, TRIM25, SLC25A11, C1QBP,
	NDUFA9, ME2, CXCL11, GZMB, TLK1,
	SLC4A4, RBM25, hCAP-D3, ATP5A1,
	CDC42BPA, DDAH2, AGPAT5, FLJ10534,
	MARCH5, FLJ13220, SLA
390	WARS, EPAS1, EIF4E, PRDX3, TK1,	88%	86%	81%	83%	81%	86%
	GMFB, DLGAP4, USP4, CXCL9, CXCL10,
	FAS, CHEK1, KITLG, C1QBP, NDUFA9,
	SLC25A11, WHSC1, ME2, IFT20, RBM25,
	HNRPD, BRIP1, ETNK1, STAT1, MASA,
	SYDE1, C9orf16, ZNF518
391	WARS, SFRS2, MTHFD2, PSME2, GMFB,	85%	79%	92%	79%	88%	76%
	DLGAP4, TYMS, CXCL9, RABIF, CXCL10,
	HNRPA3P1, TRIM25, KITLG, SLC25A11,
	ME2, RBBP4, CXCL11, RBM25, SOCS6,
	FAS, AGPAT5, MARCH5, SEC10L1,
	HNRPD, BRIP1, STAT1, KIAA0265,
	CCNA2, LRP8, CNAP1
392	HNRPD, WARS, SFRS2, EIF4E, PRDX3,	85%	90%	88%	79%	85%	69%
	MTHFD2, PSME2, GBP1, TK1, GMFB,
	DLGAP4, USP4, CTSS, ARF6, CXCL9,
	IRF8, GTSE1, CXCL10, TRIM25, C1QBP,
	SLC25A11, WHSC1, CA2, ME2, FUT4,
	CXCL11, GZMB, SLC4A4, RBM25, AK2,
	CAMSAP1L1, ATP5A1, SOCS6,
	CDC42BPA, FAS, RBBP4, BAZ1A,
	AGPAT5, MARCH5, SEC10L1, PBK,
	BRIP1, KLHL24, STAT1, GTPBP3,
	MOBK1B, MDS032, WDR45L
393	HNRPD, WARS, SFRS2, STAT1, EIF4E,	81%	79%	77%	86%	69%	66%
	MTHFD2, PSME2, MCM6, GMFB,
	DLGAP4, TYMS, USP4, TES, DCK, CDC40,
	CXCL9, IRF8, CXCL10, FAS, PLK4,
	SLC25A11, C1QBP, NDUFA9, KPNB1,
	C17orf25, ME2, IFT20, RBBP4, TLK1,
	SLC4A4, CXCL11, RBM25, AK2, NUP210,
	ATP5A1, CDC42BPA, SEC10L1, FLJ13220,
	PBK, PSAT1, BRIP1, KLHL24, ETNK1,
	FLJ20641, PIK3CD
394	WARS, SFRS2, EIF4E, PRDX3, MTHFD2,	81%	90%	85%	79%	85%	72%
	PSME2, GBP1, TK1, GMFB, DLGAP4,
	TYMS, USP4, MAD2L1, CDC40, CXCL9,
	IRF8, CXCL10, WHSC1, C17orf25, CA2,
	HNRPD, ME2, CXCL11, GZMB, SLC4A4,
	RBM25, AK2, FAS, SEC10L1, KLHL24,
	STAT1, KIAA0907
395	WARS, SFRS2, EPAS1, PAICS, EIF4E,	85%	86%	85%	72%	69%	76%
	PRDX3, MTHFD2, PSME2, DLGAP4,
	TYMS, TES, DCK, CDC40, SLC4A4, IRF8,
	CXCL10, PLK4, C1QBP, NDUFA9,
	SLC25A11, WHSC1, CA2, ME2, FUT4,
	GZMB, TLK1, CXCL11, RBM25, hCAP-D3,
	FAS, AGPAT5, MARCH5, SEC10L1,
	PSAT1, HNRPD, BRIP1, STAT1, NUMB,
	HMGB2
396	WARS, EIF4E, MTHFD2, GMFB, DLGAP4,	81%	83%	81%	90%	73%	79%
	CTSS, CDC40, CXCL10, FAS, HNRPA3P1,
	C1QBP, NDUFA9, SLC25A11, HNRPD,
	ME2, FUT4, CXCL11, RBM25, ATP5A1,
	FLJ10534, SEC10L1, FLJ13220, PBK,
	BRIP1, STAT1, KPNA2, IBRDC3, RIG, NP
397	WARS, EPAS1, EIF4E, MTHFD2, PSME2,	81%	83%	92%	76%	73%	76%
	TK1, GMFB, DLGAP4, TYMS, USP4,
	LMAN1, DCK, CDC40, CXCL9, IRF8,
	GTSE1, CXCL10, FAS, TRIM25, KITLG,
	SLC25A11, C1QBP, NDUFA9, KPNB1,
	WHSC1, C17orf25, CA2, HNRPD, ME2,
	CXCL11, GZMB, RBM25, AK2, NUP210,
	ATP5A1, DDAH2, FLJ10534, MARCH5,
	FLJ13220, PBK, PSAT1, BRIP1, TRMT5,
	KLHL24, ETNK1, STAT1, SFRS7,
	SMURF2, SCC-112
398	WARS, SFRS2, PRDX3, PSME2, TK1,	92%	97%	88%	76%	81%	79%
	GMFB, DLGAP4, TYMS, TES, MAD2L1,
	CXCL9, GTSE1, CXCL10, PLK4, TRIM25,
	C1QBP, NDUFA9, KPNB1, WHSC1,
	C17orf25, CA2, ME2, CXCL11, GZMB,
	IFT20, SLC4A4, RBM25, AK2, hCAP-D3,
	ATP5A1, FAS, MARCH5, PBK, HNRPD,
	ETNK1, STAT1, HEM1, DKK1, PRDX1,
	ELOVL6, CD86
399	HNRPD, WARS, SFRS2, EPAS1, EIF4E,	85%	79%	88%	79%	88%	76%
	PRDX3, MTHFD2, PSME2, MCM6, GMFB,
	DLGAP4, TYMS, USP4, LMAN1, CDC40,
	SLC4A4, CXCL9, GTSE1, CXCL10, FAS,
	PLK4, SLC25A11, C1QBP, NDUFA9,
	KPNB1, WHSC1, C17orf25, CA2, ME2,
	CXCL11, IFT20, RBM25, BRRN1,
	CDC42BPA, RBBP4, AGPAT5, MARCH5,
	SEC10L1, PBK, TRMT5, KLHL24, STAT1,
	PEG3, ASPM, NR5A2
400	WARS, SFRS2, PAICS, EIF4E, SFPQ,	65%	79%	92%	86%	85%	76%
	PRDX3, MTHFD2, PSME2, GMFB,
	DLGAP4, TYMS, USP4, CTSS, LMAN1,
	DCK, MAD2L1, CXCL9, IRF8, CXCL10,
	PLK4, KITLG, C1QBP, NDUFA9, KPNB1,
	SLC25A11, WHSC1, C17orf25, CA2,
	HNRPD, ME2, CXCL11, TLK1, SLC4A4,
	RBM25, AK2, ATP5A1, FAS, RBBP4,
	BAZ1A, FLJ10534, SEC10L1, FLJ13220,
	PBK, PSAT1, BRIP1, KLHL24, STAT1,
	AMD1
401	HNRPD, WARS, EIF4E, MTHFD2, PSME2,	85%	79%	85%	86%	81%	76%
	GBP1, TK1, GMFB, DLGAP4, TYMS,
	USP4, TES, MAD2L1, CXCL9, CXCL10,
	FAS, TRIM25, NDUFA9, WHSC1, C17orf25,
	CA2, ME2, CXCL11, TLK1, SLC4A4,
	RBM25, BRRN1, DDAH2, MARCH5, PBK,
	PSAT1, BRIP1, KLHL24, STAT1,
	LOC146909, ECT2, BM039, GTF3C4
402	WARS, EPAS1, STAT1, EIF4E, MTHFD2,	81%	79%	88%	79%	81%	79%
	TK1, GMFB, DLGAP4, TYMS, USP4, CTSS,
	DCK, ARF6, CDC40, CXCL9, CXCL10,
	PLK4, HNRPA3P1, TRIM25, KITLG,
	SLC25A11, NDUFA9, WHSC1, C17orf25,
	CA2, HNRPD, ME2, CXCL11, IFT20, TLK1,
	SLC4A4, RBM25, AK2, CAMSAP1L1,
	ATP5A1, SOCS6, SFRS2, DDAH2, FAS,
	RBBP4, MARCH5, SEC10L1, FLJ13220,
	PBK, PSAT1, BRIP1, KLHL24, MS4A12,
	SMCHD1, RANBP2L1, SP110, SE57-1
403	WARS, SFRS2, EPAS1, STAT1, EIF4E,	73%	86%	81%	83%	69%	79%
	MTHFD2, PSME2, MCM6, TK1, GMFB,
	DLGAP4, TYMS, TES, CDC40, SLC4A4,
	CXCL9, IRF8, GTSE1, CXCL10, FAS,
	CHEK1, SLC25A1, C1QBP, NDUFA9,
	WHSC1, C17orf25, CA2, ME2, FUT4, TLK1,
	RBM25, CAMSAP1L1, hCAP-D3, DDAH2,
	RBBP4, FLJ10534, PBK, PSAT1, BRIP1,
	KLHL24, ETNK1, CAND1

Example 20

Specific Application of Prediction Methods

In selection of the gene signatures described here, two different statistical methods were used to characterise the signatures: k-nearest neighbours, and support vector machines. These methods are provided as packages to the R statistical software system (ref), through the packages class (ref) and e1071 (ref).
The signatures described in this document were tested as follows. In both cases, the data used to develop the prediction models for a given signature were the gene expression values (raw normalised intensities from the Affymetrix array data) for the probes corresponding to genes that comprise that signature, across both recurrent and non-recurrent samples:

- For k-nearest neighbours, we used leave-one-out cross validation with k=1 and k=3 to obtain sensitivity (proportion of positive, i.e. recurrent, samples correctly classified) and specificity (proportion of negative samples, i.e. non-recurrent samples correctly classified) described in table 9
- The dataset was used to generate leave-one-out cross-validation sensitivity and specificity data using the following support-vector machine parameters: The support vector machine models were generated using a linear kernel, and all other parameters used were the default values obtained from the svm function of the e1071 package.

Note the genes comprising the signatures were themselves obtained from the list of significantly differentially expressed probes, and those from the list of genes which were found to correlate with genes from the NZ 22-gene signature. In some cases there was more than one significant (or correlated) probe per gene. In these cases, the prediction models used the median intensity data across all significant probes (i.e. those in the significant probe list, see table 1) for that gene.

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Wherein in the description reference has been made to integers or components having known equivalents, such equivalents are herein incorporated as if individually set fourth.
Although the invention has been described by way of example and with reference to possible embodiments thereof, it is to be appreciated that improvements and/or modifications may be made without departing from the scope thereof.

Claims

What is claimed is:

1. A prognostic signature for determining progression of CRC, comprising two or more genes selected from Tables 1 and 2.

2. The signature of claim 1, selected from any one of the signatures in any one of Tables 3, 4 or Table 9.

3. A device for determining prognosis of CRC, comprising:

a substrate having one or more locations thereon, each location having two or more oligonucleotides thereon, each oligonucleotide selected from the group of genes from Tables 1 and 2.

4. The device of claim 3, wherein said the two or more oligonucleotides are a prognostic signature selected from in any one of Tables 3, 4 or Table 9.

5. A method for determining the prognosis of CRC in a patient, comprising the steps of;

(i) determining the expression level of a prognostic signature comprising two or more genes from Tables 1 and 2 in CRC tumour sample from the patient,

(ii) applying a predictive model, established by applying a predictive method to expressions levels of the predictive signature in recurrent and non-recurrent tumour samples,

(iii) establishing a prognosis.

6. The method of claim 5, wherein the signature is selected from any one of Tables 3, 4 or Table 9.

7. The method of claim 5, wherein said predictive method is selected from the group consisting of linear models, support vector machines, neural networks, classification and regression trees, ensemble learning methods, discriminant analysis, nearest neighbor method, bayesian networks, independent components analysis.

8. The method of any one of claims 5 to 7, wherein the step of determining the expression level of a prognostic signature is carried out by detecting the expression level of mRNA of each gene.

9. The method of any one of claims 5 to 7, wherein the step of determining the expression level of a prognostic signature is carried out by detecting the expression level of cDNA of each gene.

10. The method of claim 9, wherein the step of determining the expression level of a prognostic signature is carried out using a nucleotide complementary to at least a portion of said cDNA.

11. The method of claim 8, wherein the step of determining the expression level of a prognostic signature is carried out using qPCR method using a forward primer and a reverse primer.

12. The method of claim 8, wherein the step of determining the expression level of a prognostic signature is carried out using a device according to claim 3 or claim 4.

13. The method of any one of claims 5 to 7, wherein the step of determining the expression level of a prognostic signature is carried out by detecting the expression level of the protein of each marker.

14. The method of any one of claims 5 to 7, wherein the step of determining the expression level of a prognostic signature is carried out by detecting the expression level of the peptide of each marker.

15. The method of claim 12 or claim 13, wherein said step of detecting is carried out using an antibody directed against each marker.

16. The method of any one of claims 12 to 14, wherein said step of detecting is carried out using a sandwich-type immunoassay method.

17. The method of any one of claims 12 to 15, wherein said antibody is a monoclonal antibody.

18. The method of any one of claims 12 to 15, wherein said antibody is a polyclonal antiserum.