Abstract:
The present application discloses a diagnostic method and a kit for prognosis assessment of colorectal cancer (CRC) and a novel tumor suppressor gene to be used for diagnosis of colorectal cancer (CRC), the method comprising the steps of: (a) identifying recurrently altered regions (RAR) on a chromosome; and (b) detecting genomic alterations in the RAR. The present method makes it possible to perform early diagnosis as well as prognosis assessment for various cancers and tumors including colorectal cancer (CRC).

Description:
RELATED APPLICATIONS/PATENTS &amp; INCORPORATION BY REFERENCE 
     The present application claims the benefit of Korean Patent Application No. 10-2006-0061741 filed Jul. 3, 2006 and U.S. Provisional Application No. 60/864,413 filed Nov. 6, 2006, the entire contents of which are hereby incorporated by reference. 
    
    
     Also, documents or references are cited in this text, either in a Reference List before the claims, or in the text itself; and, each of these documents or references (“herein cited references”), as well as each document or reference cited in each of the herein cited references (including any manufacturer&#39;s specifications, instructions, etc.), is hereby expressly incorporated herein by reference. 
     BACKGROUND 
     1. Technical Field 
     The present invention relates to novel diagnostic methods and kits for colorectal cancer (CRC). More specifically, the present invention relates to diagnostic methods, comprising the steps of; a) identifying recurrently altered regions (RAR) on chromosome; and (b) detecting genomic alterations in RAR. 
     Also the present invention relates to kits for prognosis assessment of colorectal cancer (CRC) and novel tumor suppressor genes for diagnosis of colorectal cancer (CRC). 
     2. Background Art 
     Colorectal cancer (CRC) accounted for about 1 million new cases in 2002 worldwide (9.4% of the world total). In terms of incidence, CRC ranks fourth in men and third in women. Mortality is about one half of incidence (about 529,000 deaths in 2002), while prevalence is second only to that of breast cancer worldwide, with an estimated 2.8 million persons alive with CRC diagnosed within 5 years of diagnosis. There is at least a 25-fold variation in occurrence of CRC worldwide. The incidence rates are highest in developed countries, while they tend to be low in Africa and Asia. In Korea, CRC cancer became the fourth leading cause of cancer death in 2004 and the age-standardized incidence rates of CRC in both sexes are higher than world average rates. These geographic differences are probably due to genetic background as well as environmental factors since CRC is one of multifactorial diseases; environmental and genetic factors interact and may work synergistically to develop a disease. 
     It is known that multiple mutations accumulate during the pathogenesis of CRC. Two major forms of genetic instability in CRC have been classified as either microsatellite instability (MIN) or chromosomal instability (CIN). In about 13% of CRC, mismatch repair deficiency leads to MIN, whereas in the remaining 87%, CIN appears to result in gains and losses of genetic materials. So, characterization of CIN may help to identify potential oncogenes and/or tumor suppressor genes and furthermore elucidate the pathogenesis of CRC. 
     To characterize CIN, conventional comparative genomic hybridization (CGH) has been used to identify multiple chromosomal imbalances in a sample from a single experiment. However, resolution of the conventional CGH is insufficient for precise identification of sub-microscopic changes. As accumulated evidence suggests that changes in genomic dosage contribute to tumorigenesis by altering the expression levels of cancer-related genes, more detailed analyses with high resolution are necessary. 
     There is thus a need for an improved diagnostic method. 
     The information disclosed in this Background section is only for enhancement of understanding of the background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art that is already known to a person skilled in the art. 
     SUMMARY OF THE INVENTION 
     The present invention has been made in an effort to provide a new diagnostic method and a kit for prognostic assessment of colorectal cancer. The present invention has been made based, at least in part, on the following discovery. To see genomic alterations and their clinicopatholigical implications in CRC, the present inventor applied genome-wide array CGH to the genomic DNAs extracted from microdissected tissues of 59 colorectal cancer cases. Using this strategy, various genomic copy number changes related to CRC including novel recurrently altered regions (RAR) were identified and associations between genetic alterations detected by array CGH and clinicopathological variables were examined. 
     As a result, twenty-seven RARs were identified in CRC and RAR-L1 and RAR-L20 found to be independent indicators of poor prognosis. Expression of CAMTA1, located in RAR-L1, was frequently reduced in CRCs and low CAMTA1 expression was significantly associated with poor prognosis, which indicates CAMTA1 plays as a tumor suppressor in CRC. 
     The present invention is broadly directed to a method for prognosis assessment of colorectal cancer (CRC) by identifying recurrently altered genomic regions (RAR) in colorectal cancer with high resolution (one Mb-resolution) microarray based comparative genomic hybridization (array CGH), and using the specific recurrently altered genomic regions in colorectal cancer as a prognostic marker for colorectal cancer progress. 
     In one aspect, the present invention provides a diagnostic method for prognostic assessment of colorectal cancer, comprising the steps of: (a) obtaining a nucleic acid sample from a subject; (b) identifying recurrently altered regions (RAR) on chromosome by array CGH; (C) detecting variation of expression of a specific gene in the RAR; and (d) performing prognostic assessment based on the detected variation. 
     In a preferred embodiment, the RAR in the step (b) may be one or more region selected from group consisting of RAR-L1 (loss of chromosome 1p36) and RAR-L20 (loss of chromosome 21q22). Preferably, the specific gene in the step (c) may be a cancer suppressor gene located in the RAR. More preferably, the cancer suppressor gene may be CAMTA1. When reduced gene expression level of CAMTA1 is detected, it may be assessed as poor prognosis. 
     In another aspect, the present invention provides a diagnostic kit for prognostic assessment of colorectal cancer, which comprises: (a) an array CGH instrument for identifying recurrently altered regions (RAR) on a chromosome; and (b) an image analysis device for detecting variation of expression of a specific gene in the RAR. The kit may further include a container for holding the instrument and device. 
     In still another aspect, the present invention provides a use of cancer suppressor gene CAMTA1 for prognostic assessment of colorectal cancer. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows an analysis result for genome of patients with colorectal cancer. A: Genome-wide profiles of patients with colorectal cancer, B: Frequencies of all significant gains and losses on chromosome 
         FIG. 2  shows an analysis result for verification of array-CGH copy number profiles. A: normal tissue DNA, B: tumor tissue DNA of CCRC80, C: tumor versus normal peak ratio plot 
         FIG. 3  shows an analysis result for examples of recurrently altered regions (RAR) and survival curves. A: Stage, B: RAR-L1 on 1p36, C: RAR-L4 on 1p31, D: RAR-L20 on 21q22, E: Graph of RAR-L1 (loss of chromosome 1p36), F: Graph of RAR-L20 (loss of chromosome 21q22). 
         FIG. 4  shows an analysis result for expression profiles of cancer suppressor genes. A: Plots of tumor/normal intensity ratios, B: Kaplan-Meier survival curves, C: Examples of missense mutation (SEQ ID NOS 35 and 36, respectively, in order of appearance). 
     
    
    
     DETAILED DESCRIPTION 
     Hereinafter, the present invention will be described in further detail with reference to examples. It is to be understood, however, that these examples are for illustrative purposes only and are not to be construed to limit the scope of the present invention. 
     Example 1 
     General Characteristics of Genomic Alterations in Colorectal Cancer 
     (1) Collection of Tissue Samples from Patients with Colorectal Cancer 
     Surgical specimens from 59 CRC patients, who underwent surgical resection during 1995 and 1997 at Dankook University Hospital, Cheonan, Korea, were examined in this invention. This examination was performed under the approval of Institutional Review Boards of Kangnam St. Mary&#39;s Hospital, The Catholic University of Korea, Korea. After surgical resection, tumor and adjacent normal tissues from each patient were collected separately and snap frozen in deep freezer. Frozen sections were prepared of 10 μm thickness on a gelatin coated slide using cryotom (Reighert-Jung, Germany). After H&amp;E staining of frozen section, tumor cell rich area (more than 60% of tumor cells) and normal cell area were selected under the microscope and dissected manually. Microdissected tissues were transferred into the cell lysis buffer (1% proteinase-K in TE buffer) and genomic DNA was extracted by incubating at 50° C. for 12 hours. DNA from normal tissue was used as reference for array CGH. Extracted DNA was purified using a DNA purification Kit (Solgent, Daejon, Korea) and quantified using NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Delaware USA). Histopathological review of the tumors was performed by experienced pathologist according to the standard TNM classification in the American Joint Committee on Cancer guidelines. 
     (2) Array Comparative Genomic Hybridization and Data Processing 
     We used human large-insert clone arrays with 1 Mb resolution across the whole genome printed by the Sanger Institute Microarray Facility (Fiegler et al, Genes Chromosomes Cancer 2003; 36:361-374; Kim T M et al, Clin Cancer Res 2005; 11:8235-8242.) Details of DNA labeling, pre-hybridization, hybridization, and post-hybridization processes are described below. Genomic DNA from cancer tissue was labeled with Cy3-dCTP and DNA from normal tissue of the same patient was labeled with Cy5-dCTP. Open-well hybridization was done as described previously. Arrays were scanned using GenePix 4100A scanner (Axon Instruments, USA) and the image was processed using GenePix Pro 6.0. Normalization and re-aligning of raw array CGH data were performed using the web-based array CGH analysis interface, ArrayCyGHt (URL: genomics.catholic.ac.kr/arrayCGH/). In brief, we used print-tip loess normalization method for analysis. Mapping of large insert clones was done according to the genomic location in the Ensembl and UCSC genome browser. In sum, 2,981 BAC clones out of initial 3,014 clones were processed. Information of whole clone set is available in the Ensembl human genome browser (URL: ensembl.org/Homo_sapiens/index.html). 
     (3) Data Analysis for Chromosomal Alterations 
     To set the cutoff value for chromosomal alterations of individual clones, we performed four independent series of normal hybridization (three self to self and one male to female hybridizations) as controls. Based on the control hybridizations, the cutoff value for copy number aberration was set to above or below 3-fold of standard deviation at individual data point. Regional copy number change was defined as DNA copy number alterations stretching across more than 2 consecutive BAC clones, but not across entire chromosomes. High-level amplification of clones was defined when their intensity ratios were higher than 1.0 in log 2 scale, and vice versa for homozygous deletion. The boundary of the copy number changes was assigned to the halfway between two neighboring clones. RAR was defined as regional copy number changes, which appear in at least 10 tumor samples. 
     (4) The Data of Genomic Alterations 
     The clinicopathological data of all 59 patients are summarized in Table 1. There were 39 men and 20 women and the mean patient age at the time of surgery was 58.7 years (range from 23 to 81). Among the 59 cases, 41 patients (69.5%) had rectosigmoid cancer. Thirty six cancers (61.0%) were categorized as early stage tumors. At the end of the follow up, 23 patients were dead. 
     
       
         
               
             
               
               
               
             
               
             
               
               
               
             
               
             
               
               
               
             
               
             
               
               
               
             
           
               
                 TABLE 1 
               
             
             
               
                   
               
               
                 General characteristics of study subjects 
               
             
          
           
               
                   
                 Number of patients 
                 59 (100%) 
               
               
                   
                   
               
               
                   
                 male 
                 39 (66.1%) 
               
               
                   
                 female 
                 20 (33.9%) 
               
             
          
           
               
                 Age group 
               
             
          
           
               
                   
                 Male 
                 59.2 
               
               
                   
                 Female 
                 57.8 
               
               
                   
                 &lt;60 
                 31 (52.5%) 
               
               
                   
                 &gt;=60 
                 28 (47.5%) 
               
             
          
           
               
                 Stage 
               
             
          
           
               
                   
                 Early (Satge I and II) 
                 36 (61.0%) 
               
               
                   
                 Advanced (Stage III and IV) 
                 23 (39.0%) 
               
             
          
           
               
                 Tumor site 
               
             
          
           
               
                   
                 Rectosigmoid 
                 41 (69.5%) 
               
               
                   
                 Other sites 
                 18 (30.5%) 
               
               
                   
                   
               
               
                   
                 Note: 
               
               
                   
                 other sites denote ascending, transverse, descending colon and cecum 
               
             
          
         
       
     
     The overall genomic alterations detected in 59 colorectal cancers are illustrated in  FIG. 1A . The frequency plot of the chromosomal changes shows that they are not randomly distributed, but clustered in several hot regions across the whole genome ( FIG. 1B ). The array CGH signal intensity ratio (log 2 scale) data of the 59 cases can be downloaded from our website (URL: lib.cuk.ac.kr/micro/CGH/colon.htm). 
     The mean number of altered clones per case was 764.8 out of total 2,981 clones (range from 58 to 1,540). The mean numbers of altered clones are significantly higher in males (832.6 vs. 632.6, p=0.04), advanced stage group (897.7 vs. 679.9, p=0.03), and rectosigmoid cancer (826.7 vs. 623.8, p=0.03). The most frequent changes of entire chromosomal arms were gains of 13q (31/59, 52.5%), 20q (30/59, 50.8%), 20p (23/59, 40.0%), 7p (21/59, 35.6%), 8q (20/59, 33.9%) as well as losses of 18q (29/59, 49.2%), 18p (27/59, 45.8%) and 17p (26/59, 44.1%). 
     Example 2 
     Verification of Copy Number Alterations 
     To verify the copy number changes identified, multiplex ligation-dependent probe amplification (MLPA) analysis was performed using MLPA-Aneuploidy test kit P095 (MRC Holland, Amsterdam, Netherlands) as described below. Briefly, genomic DNA (250 ng) was denatured for 10 minutes at 98° C. and 3 μl of probe-mix including buffer was added. Then the mixture was heated at 95° C. for 1 minute and incubated at 60° C. for 16 hours. Ligation reaction was performed using a heat stable ligase-65 enzyme at 54° C. for 15 minutes. Ten μl of ligation reaction was mixed with 40 μl of PCR reaction mix containing universal primers. One primer is unlabelled and the other is labeled with FAM [N-(3-fluoranthyl)maleimide]. The thermal cycling was as follows: 1 minute at 95° C. followed by 35 cycles of 30 sec at 95° C., 30 sec at 60° C., and 60 sec at 72° C. Analysis of the amplified fragments was performed using ABI PRISM 3730 XL DNA Analyzer (Applied Biosystems, Foster City, USA) with ROX-500 (ROX-500 Genescan, ABI, USA) as a size standard. The peak area of the PCR products was determined by Genotyper software (Applied Biosystems, Foster City, USA) and data analysis was performed using a simplified analysis method from Coffalyser macro (URL: mlpa.com). 
     To verify the copy number changes identified by array-CGH, we performed MLPA analysis with 13 primary CRCs showing copy number aberrations. Copy number alterations identified by array-CGH were generally consistent with MLPA results.  FIG. 2  illustrates example of MLPA validation results. Twelve peaks (numbered at each peak) are the examples of copy number alterations on chromosome 13, 18, 21, and X. 
     Example 3 
     Recurrently Altered Regions 
     In addition to the entire chromosomal changes, a lot of regional copy number changes were identified. Among those regional changes, we defined the chromosomal region recurrently altered in at least 10 cases as RAR. In sum, 7 RAR gains (RAR-G) and 20 RAR losses (RAR-L) were detected. Table 2 lists the map position, size and cancer-related genes located in 27 RARs. Five RARs were detected in more than 40% of cases; RAR-G4 (28/59, 47.5%), RAR-L2 (27/59, 45.8%), RAR-L5 (25/59, 42.4%), RAR-L14 (28/59, 47.5%), and RAR-L17 (28/59, 47.5%) (Table 2). 
     
       
         
               
             
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
             
           
               
                 TABLE 2 
               
             
             
               
                   
               
               
                 Recurrent genetic alteration regions in 59 colorectal cancers 
               
             
          
           
               
                   
                   
                   
                 Boundary 
                 Size 
                   
                 Putative cancer 
               
               
                 Alterations 
                 BAC clone ID 
                 Cytoband 
                 (Mb) 
                 (Mb) 
                 Frequency 
                 related genes 
               
               
                   
               
             
          
           
               
                 Gain 
                 RAR-G1 
                 RP11-440P5-RP11-373L24 
                 2p16.1-p15  
                 59.90-61.92 
                 2.01 
                 15/59 
                 BCL11A, REL 
               
               
                   
                 RAR-G2 
                 RP11-163H6-RP11-4S4D1S 
                  3q26.2-q26.32 
                 172.14-178.64 
                 6.49 
                 12/59 
                 PLD1, ECT2, 
               
               
                   
                 RAR-G3 
                 RP11-196O16-RP11-486P11 
                 7p21.1 
                 15.35-20.32 
                 4.97 
                 21/59 
                 AGR2, TWIST1 
               
               
                   
                 RAR-G4 
                 RP11-495D4-RP11-17E16 
                  8q24.13-q24.21 
                 126.22-131.11 
                 4.88 
                 28/59 
                 MYC 
               
               
                   
                 RAR-G5 
                 RP11-121C18-RP11-34N19 
                 11p15.1-p14.3 
                 20.97-23.47 
                 2.49 
                 11/59 
                   
               
               
                   
                 RAR-G6 
                 RP11-31I23-RP1-68D18 
                 11p13 
                 34.47-35.49 
                 1.01 
                 19/59 
                 CD44 
               
               
                   
                 RAR-G7 
                 RP3-404F18-RP3-394F12 
                  Xq24-q25 
                 117.92-125.02 
                 7.10 
                 21/59 
                 BIRC4 
               
               
                 Loss 
                 RAR-L1 
                 RP3-438L4-RP11-338N10 
                  1p36.31-p36.23 
                 6.52-8.43 
                 1.90 
                 15/59 
                 CAMTA1 
               
               
                   
                 RAR-L2 
                 RP11-428D12-RP1-86A18 
                   1p33-p32.3 
                 48.50-51.17 
                 2.66 
                 27/59 
                 FAF1 
               
               
                   
                 RAR-L3 
                 RP5-944F13-RP11-175G14 
                 1p31.1 
                 69.56-72.27 
                 2.70 
                 15/59 
                 CTH, PTGER3 
               
               
                   
                 RAR-L4 
                 RP5-963M5-RP4-739M21 
                 1p31.1 
                 76.26-77.47 
                 1.20 
                 23/59 
                   
               
               
                   
                 RAR-L5 
                 RP11-22A3-RP11-446J8 
                  4p15.33-p15.32 
                 12.05-17.17 
                 5.11 
                 25/59 
                   
               
               
                   
                 RAR-L6 
                 RP11-100N21-RP11-415L23 
                 4p12 
                 46.67-48.32 
                 1.65 
                 19/59 
                 TEC 
               
               
                   
                 RAR-L7 
                 RP11-87F15-RP11-347K3 
                  4q34.1-q26.33 
                 177.12-189.92 
                 12.79 
                 10/59 
                 CLDN22, IRF2, 
               
               
                   
                   
                   
                   
                   
                   
                   
                 ING2, CASP3 
               
               
                   
                 RAR-L8 
                 CTD-2011L22-RP11-20O13 
                 5q14.3-q15  
                 91.52-93.36 
                 1.83 
                 12/59 
                   
               
               
                   
                 RAR-L9 
                 RP11-391B7-CTC-279E3 
                 5q33.3-q34  
                 157.36-160.78 
                 3.41 
                 12/59 
                   
               
               
                   
                 RAR-L10 
                 RP3-365E2-RP1-13D10 
                   6p23-p22.3 
                 13.97-17.02 
                 3.04 
                 19/59 
                   
               
               
                   
                 RAR-L11 
                 RP11-338B22-RP11-16H11 
                  8p23.3-p23.2 
                 0.46-4.49 
                 4.02 
                 23/59 
                   
               
               
                   
                 RAR-L12 
                 RP11-325D15-RP11-619F23 
                 10q22.2-q22.3 
                 77.33-79.26 
                 1.91 
                 13/59 
                   
               
               
                   
                 RAR-L13 
                 RP11-381K7-RP11-426E5 
                 10q25.2 
                  112.7-114.46 
                 1.75 
                 12/59 
                 ACSL5 
               
               
                   
                 RAR-L14 
                 RP11-164H13-RP11-76E12 
                 14q32.13-q32.2  
                 95.15-97.53 
                 2.40 
                 28/59 
                   
               
               
                   
                 RAR-L15 
                 RP11-353B9-RP11-105D1 
                 15q21.1-q21.2 
                 47.35-49.35 
                 1.99 
                 17/59 
                   
               
               
                   
                 RAR-L16 
                 RP11-231A23-RP11-24N10 
                  15q22.2-q22.31 
                 57.44-61.74 
                 4.29 
                 21/59 
                 ANXA2, RORA 
               
               
                   
                 RAR-L17 
                 RP11-401O9-RP11-219A15 
                 17p13.1-p11.2 
                  9.83-17.02 
                 7.18 
                 28/59 
                 SCO1 
               
               
                   
                 RAR-L18 
                 RP5-836L9-RP11-121A13 
                 17p11.2 
                 19.88-22.24 
                 0.35 
                 23/59 
                   
               
               
                   
                 RAR-L19 
                 RP1-270M7-RP1-152M24 
                 21q11.2-q21.1 
                 15.21-16.83 
                 1.61 
                 18/59 
                   
               
               
                   
                 RAR-L20 
                 RP11-98O13-RP5-1031P17 
                 21q22.13-q22.2  
                 37.50-40.67 
                 3.16 
                 13/59 
               
               
                   
               
               
                 Note: 
               
               
                 The frequency represents the number of samples with the corresponding genomic change out of 59 colorectal cancers. 
               
             
          
         
       
     
     Several cancer-related genes are included in the RARs. For example, known oncogenes such as MYC and REL as well as putative oncogens such as BLC11A, PLD1, ECT2, AGR2, TWIST1, and BIRC4 are included in the RAR-Gs. Also, a number of known or putative tumor suppressor genes such as CAMTA1, FAF1, CTH, PTGER3, TEC, CLDN22, ING2, IRF2, ACSL5, ANXA2, RORA, and SCO1 are located in the RAR-Ls. 
     Example 4 
     High Copy Number Changes 
     All high-level amplifications and homozygous deletions along with the putative cancer-related genes located in them are summarized in Table 3. 
     
       
         
               
             
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
             
           
               
                 TABLE 3 
               
             
             
               
                   
               
               
                 Genomic segments representing high copy number changes in 59 colorectal cancers 
               
             
          
           
               
                   
                   
                   
                 Boundary 
                 Size 
                 Observed 
                 Putative cancer- 
               
               
                 Change 
                 BAC clone ID 
                 Cytoband 
                 (Mb) 
                 (Mb) 
                 cases  a   
                 related genes 
               
               
                   
               
             
          
           
               
                 Amp 
                 RP11-449G3-RP4-725G10 
                  7p12.1-p11.2 
                 53.47-56.26 
                 2.78 
                 CCRC93 
                 EGFR 
               
               
                   
                 RP4-550A13-RP11-506M12 
                 7q22.1 
                 97.86-99.59 
                 1.72 
                 CCRC29 
                 MCM7 
               
               
                   
                 RP11-90J7-RP11-20E23 
                  10q22.3-q23.1 
                 79.26-83.53 
                 4.27 
                 CCRC37 
                   
               
               
                   
                 RP5-1096D14-RP11-319E16 
                  12p13.33-p13.31 
                 1.43-5.57 
                 4.13 
                 CCRC33 
                 CCND2, FGF6, FGF23, 
               
               
                   
                   
                   
                   
                   
                   
                 AKAP3 
               
               
                   
                 RP11-129M14-RP11-332E3 
                 13q21.31-q22.2 
                 64.90-75.98 
                 11.07 
                 CCRC59 
                 KLF5 
               
               
                   
                 RP11-564N10-RP11-255P5 
                 13q33.1 
                 100.86-102.84 
                 1.97 
                 CCRC72 
                 FGF14 
               
               
                   
                 RP11-265C7-RP11-245B11 
                 13q34 
                 112.49-113.85 
                 1.35 
                 CCRC19 
                 CUL4A, TFDP1 
               
               
                   
                 RP11-390P24-RP11-94L15 
                   17q12-q21.2 
                 34.71-35.45 
                 0.73 
                 CCRC17, 
                 PPARBP, PPP1R1B, 
               
               
                   
                   
                   
                   
                   
                 81 
                 STARD3, TCAP, PNMT, 
               
               
                   
                   
                   
                   
                   
                   
                 ERBB2, GRB7, CDC6, 
               
               
                   
                   
                   
                   
                   
                   
                 RARA 
               
               
                   
                 RP11-13L22-RP11-28F1 
                 18q21.33 
                 57.72-59.73 
                 2 
                 CCRC80 
                   
               
               
                   
                 RP3-324O17-RP4-633O20 
                  20q11.21-q11.23 
                 28.92-36.34 
                 7.41 
                 CCRC12, 
                 ID1, BCL2L1, HCK, 
               
               
                   
                   
                   
                   
                   
                 90, 93 
                 TPX2, MYLK2, PLAGL2, 
               
               
                   
                   
                   
                   
                   
                   
                 TGIF2, SRC 
               
               
                   
                 RP5-1028D15-RP4-719C8 
                  20q13.12-q13.33 
                 41.66-58.31 
                 16.64 
                 CCRC 11, 
                 MYBL2, RAB22A 
               
               
                   
                   
                   
                   
                   
                 43, 72, 90, 
                   
               
               
                   
                   
                   
                   
                   
                 93 
                   
               
               
                 HD 
                 RP11-350K6-RP11-520K18 
                  18q21.31-q21.33 
                 54.78-57.70 
                 2.91 
                 CCRC73 
                 PMAIP1/NOXA 
               
               
                   
                 RP11-25L3-RPU-396D4 
                 18q22.3-q23  
                 69.26-71.83 
                 2.56 
                 CCRC73 
                 — 
               
               
                   
               
               
                 Note: 
               
               
                 Amp, amplification; HD, homozygous deletion. 
               
               
                   a  In case of more than two cases observed, the boundary of high copy number change was defined as the most extended set of clones, so they were not necessarily overlapping. 
               
             
          
         
       
     
     In sum, 11 genomic segments of high-level amplifications and 2 homozygous deletions were identified at least in one case. Although, most high copy number changes were identified in single case, amplifications on 17q12, 20q11 and 20q13 were observed in more than two cases. There are known oncogenes such as EGFR, CCND2, ERBB2, and MYBL2 in the amplified regions. Also, there are several putative cancer-related genes in the high copy number change regions (Table 3). 
     Example 5 
     Correlation Between Genomic Alterations 
     Pairwise correlation analysis between the RARs was done to investigate the significant co-occurrence of them. For comparison, all possible pairs of RARs located on different chromosomal arms were considered. Five pairs of RARs were found to be significantly correlated to each other after adjusting for multiple testing. The RAR-L5 on 4p15 correlates with the RAR-L2 on 1p33 (r=0.66; padj=0.0001) and the RAR-G7 on Xq24 (r=0.51; padj=0.042). The RAR-L17 on 17p13 correlates with the RAR-L5 on 4p15 (r=0.56; padj=0.0073) and the RAR-L14 on 14q32 (r=0.59; padj=0.0022). The RAR-L6 on 4p12 correlates with the RAR-L2 on 1p33 (r=0.53, padj=0.02). 
     We further investigated whether significantly correlated RARs share functionally related genes using public gene database, Gene Ontology (GO). We selected genes that have the same functional annotations (e.g. signal transduction) but are separately located on two correlated RARs. Three RAR pairs were found to share functionally related genes across 12 annotations. 
     
       
         
               
             
               
               
               
               
               
               
               
             
               
               
               
               
               
               
             
               
               
               
               
               
               
             
               
               
               
               
               
               
             
               
               
               
               
               
               
               
             
           
               
                 TABLE 4 
               
             
             
               
                   
               
               
                 Functionally related genes shared by significantly co-occurred RARs 
               
             
          
           
               
                 Pathway 
                 RefSeq 
                 Symbol 
                 RAR-G7 
                 RAR-L5 
                 RAR-L17 
                 RAR-L14 
               
               
                   
               
             
          
           
               
                   
                   
                   
                 0.0428 
                   
                   
               
             
          
           
               
                   
                 adjusted p-value 
                   
                   
                 0.0073 
                   
               
             
          
           
               
                   
                   
                   
                   
                   
                 0.0022 
               
             
          
           
               
                 Receptor activity 
                 NM_000623 
                 BDKRB2 
                   
                   
                   
                 1 
               
               
                   
                 NM_000676 
                 ADORA2B 
                   
                   
                 1 
                   
               
               
                   
                 NM_000710 
                 BDKRB1 
                   
                   
                   
                 1 
               
               
                   
                 NM_001775 
                 CD38 
                   
                 1 
                   
                   
               
               
                   
                 NM_006667 
                 PGRMC1 
                 1 
                   
                   
                   
               
               
                   
                 NM_012452 
                 TNFRSF13B 
                   
                   
                 1 
                   
               
               
                 Regulation of transcription, DNA-dependent 
                 NM_001189 
                 BAPX1 
                   
                 1 
                   
                   
               
               
                   
                 NM_006777 
                 ZBTB33 
                 1 
                   
                   
                   
               
               
                   
                 NM_017544 
                 NKRF 
                 1 
                   
                   
                   
               
               
                   
                 NM_020653 
                 ZNF287 
                   
                   
                 1 
                   
               
               
                   
                 NM_020787 
                 ZNF624 
                   
                   
                 1 
                   
               
               
                   
                 NM_032498 
                 PEPP-2 
                 1 
                   
                   
                   
               
               
                   
                 NM_144680 
                 ZNF18 
                   
                   
                 1 
                   
               
               
                   
                 NM_153604 
                 MYOCD 
                   
                   
                 1 
                   
               
               
                 Transcription factor activity 
                 NM_001189 
                 BAPX1 
                   
                 1 
                   
                   
               
               
                   
                 NM_006470 
                 TRIM16 
                   
                   
                 1 
                   
               
               
                   
                 NM_020653 
                 ZNF287 
                   
                   
                 1 
                   
               
               
                   
                 NM_032498 
                 PEPP-2 
                 1 
                   
                   
                   
               
               
                   
                 NM_144680 
                 ZNF18 
                   
                   
                 1 
                   
               
               
                 Sensory perception 
                 NM_000623 
                 BDKRB2 
                   
                   
                   
                 1 
               
               
                   
                 NM_006017 
                 PROM1 
                   
                 1 
                   
                   
               
               
                   
                 NM_016113 
                 TRPV2 
                   
                   
                 1 
                   
               
               
                 Signal transduction 
                 NM_000676 
                 ADORA2B 
                   
                   
                 1 
                   
               
               
                   
                 NM_000710 
                 BDKRB1 
                   
                   
                   
                 1 
               
               
                   
                 NM_001775 
                 CD38 
                   
                 1 
                   
                   
               
               
                   
                 NM_003010 
                 MAP2K4 
                   
                   
                 1 
                   
               
               
                   
                 NM_005130 
                 FGFBP1 
                   
                 1 
                   
                   
               
               
                   
                 NM_016084 
                 RASD1 
                   
                   
                 1 
                   
               
               
                 Development 
                 NM_001290 
                 LDB2 
                   
                 1 
                   
                   
               
               
                   
                 NM_004334 
                 BST1 
                   
                 1 
                   
                   
               
               
                   
                 NM_006978 
                 RNF113A 
                 1 
                   
                   
                   
               
               
                 ATP binding 
                 NM_002470 
                 MYH3 
                   
                   
                 1 
                   
               
               
                   
                 NM_002472 
                 MYH8 
                   
                   
                 1 
                   
               
               
                   
                 NM_003010 
                 MAP2K4 
                   
                   
                 1 
                   
               
               
                   
                 NM_003384 
                 VRK1 
                   
                   
                   
                 1 
               
               
                   
                 NM_003802 
                 MYH13 
                   
                   
                 1 
                   
               
               
                   
                 NM_005963 
                 MYH1 
                   
                   
                 1 
                   
               
               
                   
                 NM_017533 
                 MYH4 
                   
                   
                 1 
                   
               
               
                   
                 NM_017534 
                 MYH2 
                   
                   
                 1 
                   
               
               
                 Generation of precursor metabolites and energy 
                 NM_001775 
                 CD38 
                   
                 1 
                   
                   
               
               
                   
                 NM_004541 
                 NDUFA1 
                 1 
                   
                   
                   
               
               
                 Hydrolase activity 
                 NM_001775 
                 CD38 
                   
                 1 
                   
                   
               
               
                   
                 NM_004278 
                 PIGL 
                   
                   
                 1 
                   
               
               
                   
                 NM_004334 
                 BST1 
                   
                 1 
                   
                   
               
               
                 Protein amino acid phosphorylation 
                 NM_003010 
                 MAP2K4 
                   
                   
                 1 
                   
               
               
                   
                 NM_003384 
                 VRK1 
                   
                   
                   
                 1 
               
               
                 G-protein coupled receptor protein signaling pathway 
                 NM_000623 
                 BDKRB2 
                   
                   
                   
                 1 
               
               
                   
                 NM_000676 
                 ADORA2B 
                   
                   
                 1 
                   
               
               
                   
                 NM_000710 
                 BDKRB1 
                   
                   
                   
                 1 
               
               
                   
                 NM_016084 
                 RASD1 
                   
                   
                 1 
                   
               
               
                 Transcription 
                 NM_020653 
                 ZNF287 
                   
                   
                 1 
                   
               
               
                   
                 NM_032632 
                 PAPOLA 
                   
                   
                   
                 1 
               
               
                   
               
             
          
         
       
     
     Example 6 
     Differential Distribution of Genetic Alterations According to Clinicopathologic Parameters 
     Four types of clinical variables (age, stage, sex, tumor site) were analysed for their associations with the genomic alterations identified. The RAR-G7, RAR-L11, RAR-L12, RAR-L13, RAR-L16, RAR-L17, RAR-L18, gains of 8q, 19p, X, loss of 14q, 15q, Xq, and Y were associated with sex. The RAR-G3, RAR-L1, RAR-L2, RAR-L5, RAR-L6, RAR-L20, loss of 1p, and 4p were found to be associated with advanced tumor stage. The RAR-G7, RAR-L4, RAR-L9, RAR-L11, RAR-L12, gains of 13q, 20p, 20q, losses of 18p, and 18q were associated with rectosigmoid tumor site. 
     Example 7 
     Survival Analysis with Genomic Alterations 
     Survival analysis was performed to assess the prognostic values of the clinicopathological parameters and the RARs. In univariate analysis, advanced stage (p=0.001), RAR-L1 (p=0.000), RAR-L4 (p=0.026), and RAR-L20 (p=0.031) were significantly associated with poor survival ( FIG. 3 ). The statistically highest significance was observed for the existence of RAR-L1. 
     Multivariate analysis using all the significant genomic alterations identified in univariate analysis as well as clinical variables such as age, sex and stage of tumor revealed that two RARs (RAR-L1 and RAR-L20), age, and stage are independent predictors for poor outcome in CRC (Table 5). Representative diagrams of these two RARs showing significant association with patient survival are illustrated in  FIGS. 3E  and F. 
     
       
         
               
             
               
               
               
             
               
               
               
               
               
             
           
               
                 TABLE 5 
               
             
             
               
                   
               
               
                 Result of Cox regression analysis 
               
             
          
           
               
                   
                 95% Confidence interval 
                   
               
             
          
           
               
                 Variable 
                 Hazard ratio 
                 Lower 
                 Upper 
                 p value 
               
               
                   
               
               
                 Age 
                 9.979 
                 2.688 
                 37.050 
                 0.001 
               
               
                 Stage 
                 5.073 
                 1.880 
                 13.689 
                 0.001 
               
               
                 RAR-L1 
                 8.151 
                 2.167 
                 30.657 
                 0.002 
               
               
                 RAR-L20 
                 3.528 
                 1.098 
                 11.339 
                 0.034 
               
               
                 Age 
                 6.455 
                 2.034 
                 20.488 
                 0.002 
               
               
                 Stage 
                 7.409 
                 2.481 
                 22.124 
                 0.000 
               
               
                 Low CAMTA1 
                 7.089 
                 2.121 
                 23.688 
                 0.001 
               
               
                   
               
               
                 Note: 
               
               
                 upper table, Cox regression using all the significant genomic alterations identified in univariate analysis as well as clinical variables such as age, sex and stage; lower table, Cox regression using CAMTA1 expression status and clinical variables such as age, sex and stage. 
               
             
          
         
       
     
     Example 8 
     Expression of Putative Cancer-Related Gene in Survival-Associated RARs 
     (1) Real-Time Quantitative PCR Assay 
     The first-strand cDNA was synthesized from total RNA of 44 pairs of cancer/normal tissues and 3 cell lines (RKO, HT29 and HCT116) using M-MLV reverse transcriptase (Invitrogen, Carlsbad, Calif.). Real-time quantitative PCR for analyzing CAMTA1 expression profile was performed using Mx3000P qPCR system and MxPro Version 3.00 software (Stratagene, CA, USA). The real-time qPCR mixture of 20 μl contained 10 ng of cDNA, 1X SYBR® Green Tbr polymerase mixture (FINNZYMES, Finland), 0.5×ROX, and primers of 20 pmole. GAPDH was used as an internal control in each procedure. The thermal cycling was as follows: 10 min at 95° C. followed by 40 cycles of 10 sec at 94° C., 30 sec at 54° C. and 30 sec at 72° C. To verify specific amplification, melting curve analysis was performed (55-95° C., 0.5° C./sec). Relative quantification was performed by the ΔΔCT method. We defined 40% reduction of expression in cancer tissue as low CAMTA1 expression. All the experiments were repeated twice and mean value of intensity ratio with standard deviation was plotted for each case. Primer sequences for CAMTA1 real-time quantitative PCR were as follows: 5′-AGTGCAGAAAATGAAGAATGCG-3′ (SEQ ID NO: 1) and 5′-CAAAATTCTCCTGCTTGATTCG-3′ (SEQ ID NO: 2) for forward and reverse, respectively. 
     (2) CAMTA1 Mutation Analysis 
     Somatic mutation of CAMTA1 was screened by PCR-direct sequencing. Primer sets for amplification of specific exons were prepared as described previously with some modifications. All the amplification was performed using Phusion™ High-Fidelity DNA polymerase (FINNZYMES, Finland). PCR products were purified using MEGA-spin™ gel extraction kit (iNtRON, Korea). 
     
       
         
               
             
               
               
               
             
           
               
                 TABLE 6 
               
             
             
               
                   
               
               
                 Primer sequences for CAMTA1 mutation analysis 
               
               
                 (SEQ ID NOS 3-34, 
               
               
                 respectively, in order of appearance) 
               
             
          
           
               
                   
                 Forward primer 
                 Reverse primer 
               
               
                   
               
               
                 Exon1 
                 CCACTAGGAAGCTTTGTTTAG 
                 CTCTTACCTTCCGGCCTTGTT 
               
               
                   
                 GT 
                 T 
               
               
                   
               
               
                 Exon2 
                 TTGGCAGGAATATCACAGAAG 
                 TTTTGCTACCCCAGAAGGATT 
               
               
                   
                 AG 
                 A 
               
               
                   
               
               
                 Exon3 
                 GGAGATTTTATCTATTATTTT 
                 GGACTATGTGAAGCAACCTAA 
               
               
                   
                 CTCTA 
                   
               
               
                   
               
               
                 Exon4 
                 AACAGCAAAAACTTTCTTACC 
                 CCAAATCAGGTAATCAATGCA 
               
               
                   
                 TCTC 
                   
               
               
                   
               
               
                 Exon5 
                 TTTCTTCTACTTGGTACTCTT 
                 AATGACATTTGTGCACCAAGG 
               
               
                   
                 GGTA 
                   
               
               
                   
               
               
                 Exon6 
                 CCCTCTTTCCAACTGAATTCT 
                 CCAGAGACAGAAGAAGAATCC 
               
               
                   
                 C 
                   
               
               
                   
               
               
                 Exon7 
                 AGTCTGCTAATATCCCACATG 
                 TGGTTGATGCCAGCCTGGTTC 
               
               
                   
                 CGC 
                   
               
               
                   
               
               
                 Exon9 
                 CCAGCACCATGGCCTACATGC 
                 CAGCGGCGGCAGCTTACCTCT 
               
               
                   
               
               
                 Exon10 
                 AACTCTGTTCCCCTCTCTGTT 
                 CAGGCCATCACACTCACCTTG 
               
               
                   
                 CTCT 
                   
               
               
                   
               
               
                 Exon11 
                 CATTAAGGAGAGCTGGACATT 
                 ACGACCCAAGCACTGTTCTTA 
               
               
                   
                 A 
                   
               
               
                   
               
               
                 Exon13 
                 GTGGTATGCGAGAAGATGATG 
                 CAGTGCTCAGGAAGAATGTGA 
               
               
                   
               
               
                 Exon14 
                 TACCCAGTTGGGTTTCATCTT 
                 ATGCCAGACTGGAAGAACAGC 
               
               
                   
                 GGTG 
                 AAG 
               
               
                   
               
               
                 Exon15-1 
                 GGTCTTGACCTCTGATTGAGA 
                 CTCTGCTAATTTCACATGACC 
               
               
                   
               
               
                 Exon15-2 
                 ATCTCGATTCCCGACTCTCTA 
                 ATAACAGTGACTCCCTTGGGT 
               
               
                   
                 G 
                   
               
               
                   
               
               
                 Exon19 
                 AAGCTGACATTTCTGGTAGTT 
                 TTTAGCCAAACCAGGATCTTC 
               
               
                   
                 AATC 
                   
               
               
                   
               
               
                 Exon20 
                 TTCTCTTCTTCCCTTCCCGGT 
                 AAGTCAGAGTTCTCTTCCCTA 
               
               
                   
                 A 
                 GGG 
               
               
                   
               
             
          
         
       
     
     Among the coding genes in RAR-L1 and RAR-20, CAMTA1 was suggested as a putative tumor suppressor gene in neuronal tumor. Therefore, we examined the expression profile of this gene in three CRC cell lines and 44 pairs primary CRCs by real-time quantitative PCR. Ratio of gene expression values (cancer versus normal) was calculated. All three cell lines and 26 CRCs out of 44 (59.1%) showed low expression of CAMTA1 compared with normal tissue ( FIG. 4A ). Low CAMTA1 expression was significantly associated with poor survival than CAMTA1 intact cases (p=0.029) ( FIG. 4B ). After being adjusted for age, sex and stage by Cox regression, low CAMTA1 expression showed more significant association with poor survival as an independent predictor (HR=7.089, p=0.001) (Table 5). 
     Low CAMTA1 expression was observed more frequently in the CRCs with RAR-L1 (70%, 7/10) than those without RAR-L1 (55.9%, 19/34) and expression level was also lower in CRCs with RAR-L1 (mean ratio 0.74) than those without RAR-L1 (mean ratio 0.93), but not significantly. For further exploring putative mechanisms of low CAMTA1 expression, we screened somatic mutations (26 CRCs) and methylation status (38 CRCs). One missense mutation was found in a primary CRC (CCRC71), which showed low CAMTA1 expression but without RAR-L1 ( FIG. 4C ). However, no hypermethylation was observed in the promoter region of CAMTA1 (data not shown). 
     The invention has been described in detail with reference to preferred embodiments thereof. However, it will be appreciated by those skilled in the art that changes may be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents. 
     All patents and publications mentioned in this specification are herein incorporated by reference to the same extent as if each independent patent and publication was specifically and individually indicated to be incorporated by reference. 
     REFERENCES 
     
         
         1. Parkin D M, Bray F, Ferlay J, Pisani P. Global cancer statistics, 2002. CA Cancer J Clin 2005; 55:74-108. 
         2. National Statistical Office, Korea. Korean Statistical Information System. 2006. Available from: URL: ncc.re.kr. 
         3. Shin H R, Won Y J, Jung K W, Kong H J, Yim S H, Lee J K, Noh H I, Lee J K, Park J G. Nationwide Cancer Incidence in Korea, 1999-2001; First result using the National Cancer Incidence Database. Cancer Res Treat 2006; 37:in press. 
         4. Michor F, Iwasa Y, Lengauer C, Nowak M A. Dynamics of colorectal cancer. Semin Cancer Biol 2005; 15:484-493. 
         5. Yim S H, Chung Y J. Current Status and Future Clinical Applications of Array based Comparative Genomic Hybridization. Genomics &amp; Informatics 2004; 2:113-120. 
         6. Pinkel D, Segraves R, Sudar D, Clark S, Poole I, Kowbel D, Collins C, Kuo W L, Chen C, Zhai Y, Dairkee S H, Ljung B M, Gray J W, Albertson D G. High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat Genet 1998; 20:207-211. 
         7. Fiegler H, Carr P, Douglas E J, Burford D C, Hunt S, Scott C E, Smith J, Vetrie D, Gorman P, Tomlinson I P, Carter N P. DNA microarrays for comparative genomic hybridization based on DOP-PCR amplification of BAC and PAC clones. Genes Chromosomes Cancer 2003; 36:361-374. 
         8. Kim T M, Yim S H, Lee J S, Kwon M S, Ryu J W, Kang H M, Fiegler H, Carter N P, Chung Y J. Genome-wide screening of genomic alterations and their clinicopathologic implications in non-small cell lung cancers. Clin Cancer Res 2005; 11:8235-8242. 
         9. Chung Y J, Jonkers J, Kitson H, Fiegler H, Humphray S, Scott C, Hunt S, Yu Y, Nishijima I, Velds A, Holstege H, Carter N, Bradley A. A whole-genome mouse BAC microarray with 1-Mb resolution for analysis of DNA copy number changes by array comparative genomic hybridization. Genome Res 2004; 14:188-196. 
         10. Kim S Y, Nam S W, Lee S H, Park W S, Yoo N J, Lee J Y, Chung Y J. ArrayCyGHt: a web application for analysis and visualization of array-CGH data. Bioinformatics 2005; 21:2554-2555. 
         11. Livak K J, Schmittgen T D. Analysis of relative gene expression data using real-time quantitative PCR and the 2 (-Delta Delta C(T)) Method. Methods 2001; 25: 402-408. 
         12. Henrich K O, Fischer M, Mertens D, Benner A, Wiedemeyer R, Brors B, Oberthuer A, Berthold F, Wei J S, Khan J, Schwab M, Westermann F. Reduced expression of CAMTA1 correlates with adverse outcome in neuroblastoma patients. Clin Cancer Res 2006; 12:131-138. 
         13. Barbashina V, Salazar P, Holland E C, Rosenblum M K, Ladanyi M. Allelic losses at 1p36 and 19q13 in gliomas: correlation with histologic classification, definition of a 150-kb minimal deleted region on 1p36, and evaluation of CAMTA1 as a candidate tumor suppressor gene. Clin Cancer Res 2005; 11:1119-1128. 
         14. Schouten J P, McElgunn C J, Waaijer R, Zwijnenburg D, Diepvens F, Pals G. Relative quantification of 40 nucleic acid sequences by multiplex ligation-dependent probe amplification. Nucleic Acids Res 2002; 30:e57. 
         15. He Q J, Zeng W F, Sham J S, Xie D, Yang X W, Lin H L, Zhan W H, Lin F, Zeng S D, Nie D, Ma L F, Li C J, Lu S, Guan X Y. Recurrent genetic alterations in 26 colorectal carcinomas and 21 adenomas from Chinese patients. Cancer Genet Cytogenet 2003; 144:112-118. 
         16. Poeaim S, Rerkamnuaychoke B, Jesdapatarakul S, Campiranon A. Chromosome alterations in colorectal cancer in That patients. Cancer Genet Cytogenet 2005; 160:152-159. 
         17. Ried T, Knutzen R, Steinbeck R, Blegen H, Schrock E, Heselmeyer K, du Manoir S, Auer G. Comparative genomic hybridization reveals a specific pattern of chromosomal gains and losses during the genesis of colorectal tumors. Genes Chromosomes Cancer 1996; 15:234-245. 
         18. Nakao K, Mehta K R, Fridlyand J, Moore D H, Jain A N, Lafuente A, Wiencke J W, Terdiman J P, Waldman F M. High-resolution analysis of DNA copy number alterations in colorectal cancer by array-based comparative genomic hybridization. Carcinogenesis 2004; 25:1345-1357. 
         19. Knosel T, Petersen S, Schwabe H, Schluns K, Stein U, Schlag P M, Dietel M, Petersen I. Incidence of chromosomal imbalances in advanced colorectal carcinomas and their metastases. Virchows Arch 2002; 440:187-194. 
         20. Jones A M, Douglas E J, Halford S E, Fiegler H, Gorman P A, Roylance R R, Carter N P, Tomlinson I P. Array-CGH analysis of microsatellite-stable, near-diploid bowel cancers and comparison with other types of colorectal carcinoma. Oncogene 2005; 24:118-129. 
         21. Knosel T, Schluns K, Stein U, Schwabe H, Schlag P M, Dietel M, Petersen I. Genetic imbalances with impact on survival in colorectal cancer patients. Histopathology 2003; 43:323-331. 
         22. Aragane H, Sakakura C, Nakanishi M, Yasuoka R, Fujita Y, Taniguchi H, Hagiwara A, Yamaguchi T, Abe T, Inazawa J, Yamagishi H. Chromosomal aberrations in colorectal cancers and liver metastases analyzed by comparative genomic hybridization. Int J Cancer 2001; 94:623-629. 
         23. Douglas E J, Fiegler H, Rowan A, Halford S, Bicknell D C, Bodmer W, Tomlinson I P, Carter N P. Array comparative genomic hybridization analysis of colorectal cancer cell lines and primary carcinomas. Cancer Res 2004; 64:4817-4825. 
         24. De Angelis P M, Clausen O P, Schjolberg A, Stokke T. Chromosomal gains and losses in primary colorectal carcinomas detected by CGH and their associations with tumour DNA ploidy, genotypes and phenotypes. Br J Cancer 1999; 80:526-535. 
         25. Shivapurkar N, Maitra A, Milchgrub S, Gazdar A F. Deletions of chromosome 4 occur early during the pathogenesis of colorectal carcinoma. Hum Pathol 2001; 32:169-177. 
         26. Finch R, Moore H G, Lindor N, Jalal S M, Markowitz A, Suresh J, Offit K, Guillem J G. Familial adenomatous polyposis and mental retardation caused by a de novo chromosomal deletion at 5q15-q22: report of a case. Dis Colon Rectum 2005; 48:2148-2152. 
         27. Flanagan J M, Healey S, Young J, Whitehall V, Trott D A, Newbold R F, Chenevix-Trench G. Mapping of a candidate colorectal cancer tumor-suppressor gene to a 900-kilobase region on the short arm of chromosome 8. Genes Chromosomes Cancer 2004; 40:247-260. 
         28. Frayling I M, Bodmer W F, Tomlinson I P. Allele loss in colorectal cancer at the Cowden disease/juvenile polyposis locus on 10q. Cancer Genet Cytogenet 1997; 97:64-69. 
         29. Bando T, Kato Y, Ihara Y, Yamagishi F, Tsukada K, Isobe M. Loss of heterozygosity of 14q32 in colorectal carcinoma. Cancer Genet Cytogenet 1999; 111:161-165. 
         30. Park W S, Park J Y, Oh R R, Yoo N J, Lee S H, Shin M S, Lee H K, Han S, Yoon S K, Kim S Y, Choi C, Kim P J, Oh S T, Lee J Y. A distinct tumor suppressor gene locus on chromosome 15q21.1 in sporadic form of colorectal cancer. Cancer Res 2000; 60:70-73. 
         31. Risio M, Casorzo L, Chiecchio L, De Rosa G, Rossini F P. Deletions of 17p are associated with transition from early to advanced colorectal cancer. Cancer Genet Cytogenet 2003; 147:44-49. 
         32. Knosel T, Petersen S, Schwabe H, Schluns K, Stein U, Schlag P M, Dietel M, Petersen I. Incidence of chromosomal imbalances in advanced colorectal carcinomas and their metastases. Virchows Arch 2002; 440:187-194. 
         33. Donzelli M, Bernardi R, Negri C, Prosperi E, Padovan L, Lavialle C, Brison O, Scovassi A I. Apoptosis-prone phenotype of human colon carcinoma cells with a high level amplification of the c-myc gene. Oncogene 1999; 18:439-448. 
         34. Lakshman M, Subramaniam V, Rubenthiran U, Jothy S. CD44 promotes resistance to apoptosis in human colon cancer cells. Exp Mol Pathol 2004; 77:18-25. 
         35. Cummins J M, Kohli M, Rago C, Kinzler K W, Vogelstein B, Bunz F. X-linked inhibitor of apoptosis protein (XIAP) is a nonredundant modulator of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-mediated apoptosis in human cancer cells. Cancer Res 2004; 64:3006-3008. 
         36. Satterwhite E, Sonoki T, Willis T G, Harder L, Nowak R, Arriola E L, Liu H, Price H P, Gesk S, Steinemann D, Schlegelberger B, Oscier D G, Siebert R, Tucker P W, Dyer M J. The BCL11 gene family: involvement of BCL11A in lymphoid malignancies. Blood 2001; 98:3413-3420. 
         37. Ahn B H, Kim S Y, Kim E H, Choi K S, Kwon T K, Lee Y H, Chang J S, Kim M S, Jo Y H, Min D S. Transmodulation between phospholipase D and c-Src enhances cell proliferation. Mol Cell Biol 2003; 23:3103-3115. 
         38. Zhang J S, Gong A, Cheville J C, Smith D I, Young C Y. AGR2, an androgen-inducible secretory protein overexpressed in prostate cancer. Genes Chromosomes Cancer 2005; 43:249-259. 
         39. Shoji Y, Takahashi M, Kitamura T, Watanabe K, Kawamori T, Maruyama T, Sugimoto Y, Negishi M, Narumiya S, Sugimura T, Wakabayashi K. Downregulation of prostaglandin E receptor subtype EP3 during colon cancer development. Gut 2004; 53:1151-1158. 
         40. Bjorling-Poulsen M, Seitz G, Guerra B, Issinger O G. The pro-apoptotic FAS-associated factor 1 is specifically reduced in human gastric carcinomas. Int J Oncol 2003; 23:1015-1023. 
         41. Dunn J R, Risk J M, Langan J E, Marlee D, Ellis A, Campbell F, Watson A J, Field J K. Physical and transcript map of the minimally deleted region III on 17p implicated in the early development of Barrett&#39;s oesophageal adenocarcinoma. Oncogene 2003; 22:4134-4142. 
         42. Kuo T, Fisher G A. Current status of small-molecule tyrosine kinase inhibitors targeting epidermal growth factor receptor in colorectal cancer. Clin Colorectal Cancer 2005; Suppl 2:S62-70. 
         43. Gunther K, Leier J, Henning G, Dimmler A, Weissbach R, Hohenberger W, Forster R. Prediction of lymph node metastasis in colorectal carcinoma by expression of chemokine receptor CCR7. Int J Cancer 2005; 116:726-733. 
         44. Aligayer H, Boyd D D, Heiss M M, Abdalla E K, Curley S A, Gallick G E. Activation of Src kinase in primary colorectal carcinoma: an indicator of poor clinical prognosis. Cancer 2002; 94:344-351. 
         45. Villunger A, Michalak E M, Coultas L, Mullauer F, Bock G, Ausserlechner M J, Adams J M, Strasser A. p53- and drug-induced apoptotic responses mediated by BH3-only proteins puma and noxa. Science 2003; 302:1036-1038. 
         46. Ogunbiyi O A, Goodfellow P J, Gagliardi G, Swanson P E, Birnbaum E H, Fleshman J W, Kodner I J, Moley J F. Prognostic value of chromosome 1p allelic loss in colon cancer. Gastroenterology 1997; 113:761-766. 
         47. Ray R, Cabal-Manzano R, Moser A R, Waldman T, Zipper L M, Aigner A, Byers S W, Riegel A T, Wellstein A. Up-regulation of fibroblast growth factor-binding protein, by beta-catenin during colon carcinogenesis. Cancer Res 2003; 63:8085-8089.