Identification Of Colorectal Cancer Research Articles

Exon-Skipping–Based Subtyping of Colorectal Cancers

The identification of colorectal cancer (CRC) molecular subtypes has prognostic and potentially diagnostic value for patients, yet reliable subtyping remains unavailable in the clinic. The current consensus molecular subtype (CMS) classification in CRCs is based on complex RNA expression patterns quantified at the gene level. The clinical application of these methods, however, is challenging due to high uncertainty of single-sample classification and associated costs. Alternative splicing, which strongly contributes to transcriptome diversity, has rarely been used for tissue type classification. Here, we present an AS-based CRC subtyping framework sensitive to differential exon use that can be adapted for clinical application. Unsupervised clustering was used to measure the strength of association between different categories of alternative splicing and CMS. To build a classifier, the ground truth for CMS labels was derived from expression data quantified at the gene level. Feature selection was achieved through bootstrapping and L1-penalized estimation. The resulting feature space was used to construct a subtype prediction framework applicable to single and multiple samples. The performance of the models was evaluated on unseen CRCs from 2 independent sources (Indivumed, n= 129; The Cancer Genome Atlas, n= 99). We developed a CRC subtype identifier based on 29 exon-skipping events that accurately classifies unseen tumors and enables more precise differentiation of subtypes characterized by distinct biological and prognostic features as compared to classifiers based on gene expression. Here, we demonstrate that a small number of exon-skipping events can reliably classify CRC subtypes using individual patient specimens in a manner suitable to clinical application.

Identification of colorectal cancer using structured and free text clinical data.

Colorectal cancer incidence has continually fallen among those 50years old and over. However, the incidence has increased in those under 50. Even with the recent screening guidelines recommending that screening begins at age 45, nearly half of all early-onset colorectal cancer will be missed. Methods are needed to identify high-risk individuals in this age group for targeted screening. Colorectal cancer studies, as with other clinical studies, have required labor intensive chart review for the identification of those affected and risk factors. Natural language processing and machine learning can be used to automate the process and enable the screening of large numbers of patients. This study developed and compared four machine learning and statistical models: logistic regression, support vector machine, random forest, and deep neural network, in their performance in classifying colorectal cancer patients. Excellent classification performance is achieved with AUCs over 97%.

Correction for: Identification of colorectal cancer associated biomarkers: an integrated analysis of miRNA expression

Correction for: Identification of colorectal cancer associated biomarkers: an integrated analysis of miRNA expression

Comparison in the development of colorectal cancer after screening colonoscopy between elderly and younger population.

This study aimed to evaluate and compare the incidence of colorectal cancer (CRC) in elderly participants aged ≥75 years and those <75 years who had previously undergone a colonoscopy. This retrospective cohort study was conducted at the Center for Preventive Medicine at St. Luke's International Hospital in Japan. All participants who underwent screening colonoscopy between 2005 and 2015 were included and followed up until 2020. Our primary outcome was the identification of CRC as confirmed by pathology after screening colonoscopy. We compared the development of CRC between the two groups using survival analyses. A sub-analysis to evaluate the incidence of CRC among participants with and without neoplastic polyp resection at initial colonoscopy was also performed. A total of 8350 participants were enrolled; the median follow-up period was 2982 days (interquartile range:1932-4141), mean age was 52.5 years (SD: 11.5) and 5274 (61.3%) participants were men. The incidence of CRC during the follow-up period was 82 (0.95%) among all participants and 11 (4.31%) among the elderly participants. Elderly participants showed a significantly higher incidence of CRC than the other group [hazard ratio, 2.56; 95% confidence interval (CI), 1.14-5.75]. The sub-analysis showed that out of 2878 participants with a neoplastic polyp at the initial colonoscopy, 52 (1.81%) developed CRC (hazard ratio, 2.85; 95% CI, 1.16-6.98). A repeat colonoscopy might be warranted in people with high activities of daily living and few comorbidities, especially if there is a history of neoplastic polypectomy at the first colonoscopy.

Artificial intelligence (AI) real-time detection vs. routine colonoscopy for colorectal neoplasia: a meta-analysis and trial sequential analysis.

Studies analyzing artificial intelligence (AI) in colonoscopies have reported improvements in detecting colorectal cancer (CRC) lesions, however its utility in the realworld remains limited. In this systematic review and meta-analysis, we evaluate the efficacy of AI-assisted colonoscopies against routine colonoscopy (RC). We performed an extensive search of major databases (through January 2021) for randomized controlled trials (RCTs) reporting adenoma and polyp detection rates. Odds ratio (OR) and standardized mean differences (SMD) with 95% confidence intervals (CIs) were reported. Additionally, trial sequential analysis (TSA) was performed to guard against errors. Six RCTs were included (4996 participants). The mean age (SD) was 51.99 (4.43) years, and 49% were females. Detection rates favored AI over RC for adenomas (OR 1.77; 95% CI: 1.570-2.08) and polyps (OR 1.91; 95% CI: 1.68-2.16). Secondary outcomes including mean number of adenomas (SMD 0.23; 95% CI: 0.18-0.29) and polyps (SMD 0.23; 95% CI: 0.17-0.29) detected per procedure favored AI. However, RC outperformed AI in detecting pedunculated polyps. Withdrawal times (WTs) favored AI when biopsies were included, while WTs without biopsies, cecal intubation times, and bowel preparation adequacy were similar. Colonoscopies equipped with AI detection algorithms could significantly detect previously missed adenomas and polyps while retaining the ability to self-assess and improve periodically. More effective clearance of diminutive adenomas may allow lengthening in surveillance intervals, reducing the burden of surveillance colonoscopies, and increasing its accessibility to those at higher risk. TSA ruled out the risk for false-positive results and confirmed a sufficient sample size to detect the observed effect. Currently, these findings suggest that AI-assisted colonoscopy can serve as a useful proxy to address critical gaps in CRC identification.

The effectiveness of the colorectal cancer referral pathway – identification of colorectal cancer in a Swedish region

Introduction To shorten the time for diagnosis of suspected colorectal cancer (CRC), a standardized colorectal cancer referral pathway (CCRP) was introduced in Sweden in September 2016. However, the effects of the CCRP are still uncertain, and CRC is also found in patients undergoing a routine colonoscopy. Objective To identify all CRC-cases in the Region Örebro County and to investigate via which diagnostic pathway they were diagnosed. Furthermore, to investigate the reasons for and possible effect of not being included in the CCRP for cases found via colonoscopy. Methods Review of medical records of patients with CRC referred to the department of surgery in the Region Örebro County in 2016–2018 (n = 459). Results In CRC-cases found through colonoscopy (n = 347), 37.5% were diagnosed via a routine waiting list and 62.5% within the CCRP. No difference in tumor stage or tumor grade was found between the two groups. The non-CCRP showed a longer time to diagnosis than the CCRP group (21.5 days, IQR 7–43 vs. 13 days, IQR 8–17 (p < .001), respectively). Non-rectal cancer was more common in the non-CCRP group (81.5% vs. 57.6%, p < .001). The non-CCRP group had lower median Hb-value (106, IQR 87–129 vs. 117, IQR 101–136, p = .001). 85% of the non-CCRP group was found to meet one or more CCRP referral criteria, with bleeding anemia being the dominant criterion to meet. Conclusion The CCRP did not appear to improve prognostic outcomes for CRC-patients. ClinicalTrials.gov Identifier: NCT04585516

Identification of colorectal cancers with defective DNA damage repair by immunohistochemical profiling of mismatch repair proteins, CDX2 and BRCA1.

Colorectal cancer (CRC) is a complex disease as shown by consensus classification. The present study attempted to identify subtypes with known prognostic markers for better clinical management. A total of 72 CRC tumors were examined for the expression of mismatch repair (MMR) proteins, along with caudal-type homeobox protein 2 (CDX2) and BRCA1, by immunohistochemistry. Tumors were assigned based on the presence or loss of MMR proteins as proficient or deficient. Correlations were examined with CDX2 and BRCA1 along with clinico-pathological features. Expressional pattern of microRNAs (miRs/miRNAs), such as miR-183-96-182, known to be associated with defective DNA damage repair were evaluated by reverse transcription-quantitative PCR. A total of 22% of the CRC tumors were assigned as deficient in mismatch repair. 71% of the tumors expressed CDX2 while only 21% had nuclear expression of BRCA1. Loss of CDX2 protein was higher in the deficient subtype compared with the proficient subtype. A total of 14% of the tumors had dual loss of MMR and BRCA1 proteins and showed aggressive clinical features in addition to elevated expression of DNA damage repair microRNAs. The present study shows the presence of a small proportion of colorectal tumors with dual loss of key proteins involved in DNA damage repair which may be amenable to specific therapy. The implication of the present observations warrants investigation in a larger patient cohort with prognostic information.

PAICS, a Purine Nucleotide Metabolic Enzyme, is Involved in Tumor Growth and the Metastasis of Colorectal Cancer.

The identification of colorectal cancer (CRC) molecular targets is needed for the development of drugs that improve patient survival. We investigated the functional role of phosphoribosylaminoimidazole carboxylase, phosphoribosylaminoimidazole succinocarboxamide synthetase (PAICS), a de novo purine biosynthetic enzyme involved in DNA synthesis, in CRC progression and metastasis by using cell and animal models. Its clinical utility was assessed in human CRC samples. The expression of PAICS was regulated by miR-128 and transcriptionally activated by Myc in CRC cells. Increased expression of PAICS was involved in proliferation, migration, growth, and invasion of CRC cells irrespective of the p53 and microsatellite status. In mice, the depletion of PAICS in CRC cells led to reduced tumor growth and metastatic cell dissemination to the liver, lungs, and bone. Positron emission tomography imaging showed significantly reduced metastatic lesions in stable PAICS knockdown CRC cells. In cells with PAICS knockdown, there was upregulation of the epithelial mesenchymal transition marker, E-cadherin, and bromodomain inhibitor, JQ1, can target its increased expression by blocking Myc. PAICS was overexpressed in 70% of CRCs, and was associated with poor 5-year survival independent of the pathologic stage, patient’s race, gender, and age. Overall, the findings point to the usefulness of PAICS targeting in the treatment of aggressive colorectal cancer.

Long-Term Tracking of Cancer Cell Nucleus and Identification of Colorectal Cancer with an Aggregation-Induced Emission-Based Fluorescent Probe.

In clinical diagnosis and treatment, it is very important to distinguish cancer cells from normal cells. Nuclear-selective fluorescent probe that specifically target tumors can not only make the difference in assessing tumor margins during surgery and then facilitating accurate resection of the tumor, but also can provide crucial biomedical information of tumor progress if it can be used for long-term dynamic visualization of nucleus in cancer. Herein, a novel fluorescent probe 3 was designed and characterized to be of low-toxicity and water-solubility. The biological evaluation indicated that probe 3 prefers nucleic acids rather than accumulation in non-neuclear sites while superior to the commercial available agent DAPI (4',6-diamidino-2-phenylindole), in terms of its character of aggregation-induced emission (AIE), large Stokes shift (175 nm) and light stability. Further experiments demonstrated that probe 3 can not only differentiate SW480 and SW620 (cancer cells) from GES-1 (normal cells) with high contrast (dyed in nuclear of cancer cells and not in nuclear of normal cells), but also used for tracking cancer cell nuclear for long time. Furthermore, 3D reconstruction fluorescence imaging proved that probe 3 was able for identifying colorectal cancer tissues from para-carcinoma tissues by a strong contrast. Therefore, in precise surgery of colorectal cancer, probe 3 may be a promising-agent for guiding of intraoperation.

Characterization and Identification of Colorectal Cancer in Persons Younger Than 50 Years

The proportion of colorectal cancer (CRC) cases in persons younger than age 50, referred to as early onset CRC (EOCRC), has increased from 6% to 11% over the past 25 years, whereas the incidence of CRC has decreased in persons age 50 and older, referred to as late-onset CRC (LOCRC) in the United States.1 It is not known if EOCRC is caused by the same factors that cause LOCRC, or whether there are unique causes that alter the clinical features.2 This study was designed to analyze the clinical and genetic characteristics of EOCRC as presented at a community hospital.

Identification of Colorectal Cancer Using Near-Infrared Spectroscopy and Adaboost with Decision Stump

ABSTRACTRapid and objective detection of cancer is crucial for successful treatment. Near-infrared (NIR) spectroscopy is a vibrational technique capable of optically probing molecular changes associated with disease. The purpose of this study was to explore NIR spectroscopy for discriminating cancer from normal colorectal tissues. A total of 110 tissue samples from patients who underwent operations were characterized in this study. The popular ensemble technique AdaBoost was used to construct the diagnostic model. A decision stump was used as the weak learning algorithm. Adaboost with decision stump, an ensemble of weak classifiers, was compared with the most suitable single model, a strong classifier. Only the 20 most significant variables were selected as inputs for the model based on measured defined variable importance. Using an independent test set, the single strong classifier provided diagnostic accuracy of 89.1%, sensitivity of 100%, and specificity of 78.6%, whereas the ensemble of weak stumps provided accuracy of 96.3%, sensitivity of 96.3%, and specificity of 96.3% for distinguishing cancer from normal colorectal tissues. Therefore, NIR spectroscopy in combination with AdaBoost with decision stumps has demonstrated potential for rapid and objective diagnosis of colorectal cancer.

Practical opportunities to improve early detection and prevention of colorectal cancer (CRC) in members of high-risk families.

Colorectal cancer (CRC) incidence and mortality are steadily declining and CRC screening rates are increasing in the United States. Although this a very good news, several definable groups still have very low screening rates including younger (under age 50) members of high-risk CRC families. This opinion piece describes five strategies that could be incorporated into routine practice to improve identification and guideline-based screening in members of high-risk families. Routine incorporation of a simple family history screening tool and outreach to high-risk family members could substantially improve guideline-based screening in this population. Identification of CRCs and advanced adenomas in the endoscopy suite defines another group of high-risk families for similar outreach. Lynch syndrome families can be identified by testing CRCs and selected adenomas for microsatellite instability or loss of DNA repair protein expression. Finally, selective addition of aspirin to surveillance endoscopy can decrease the risk of new adenomas and CRCs. The rationale for these strategies as well as mechanisms for their implementation and evaluation in clinical practice is described.

Identification of metastasis-associated genes in colorectal cancer through an integrated genomic and transcriptomic analysis.

Identification of colorectal cancer (CRC) metastasis genes is one of the most important issues in CRC research. For the purpose of mining CRC metastasis-associated genes, an integrated analysis of microarray data was presented, by combined with evidence acquired from comparative genomic hybridization (CGH) data. Gene expression profile data of CRC samples were obtained at Gene Expression Omnibus (GEO) website. The 15 important chromosomal aberration sites detected by using CGH technology were used for integrated genomic and transcriptomic analysis. Significant Analysis of Microarray (SAM) was used to detect significantly differentially expressed genes across the whole genome. The overlapping genes were selected in their corresponding chromosomal aberration regions, and analyzed by using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Finally, SVM-T-RFE gene selection algorithm was applied to identify metastasis-associated genes in CRC. A minimum gene set was obtained with the minimum number [14] of genes, and the highest classification accuracy (100%) in both PRI and META datasets. A fraction of selected genes are associated with CRC or its metastasis. Our results demonstrated that integration analysis is an effective strategy for mining cancer-associated genes.

Abstract 1934: Novel mutation and hypomethylation define distinct biological subgroups of altered KRAS colon tumors.

Abstract Background: Several driver mutations have been discovered in colorectal cancer (CRC) progressions including KRAS and BRAF that has a practical significant therapeutic and prognostic value. Sequencing technology has advanced and now provides a tool for the discovery of novel driver mutations. In addition, sequencing technologies now provide a tool for whole genome methylation analysis. Here, we performed whole exome sequencing (WES) and whole genome methylation analysis to elucidate the involvement of novel candidate genes the KRAS pathway that may effect colorectal carcinogenesis. Patients and Methods: WES was carried out on genomic DNA extracted from 8 normal-tumor pairs of frozen biopsies from African Americans patients with CRC. WES and Reduced Representation Bisulfite Sequencing (RRBS) were performed. Pyrosequencing and sanger sequencing used for validation of methylation and single nucleotide variants (SNV) respectively. For WES, base call quality recalibration, realignment around indels, SNV calling and variant call recalibration were carried out using Genome Analysis Tool Kit. Variants were then annotated using Annovar. Results: WES uncovered somatic mutations alteration in many genes that are known be mutated in CRC including APC, BRAF, KRAS, Notch1, PIK3C2A, and NDRG4. We discovered a number of Novel SNVs in EID3, RGS3, HNRNPF, and GNAS in tumor samples. One GNAS missense mutation was discovered among KRAS mutated tumors. In addition, the tumor with the GNAS mutation was significantly hypomethylated (P&amp;lt;0.05) in the CpG sites of GNAS promoter as compared with paired normal tissue. The tumor was located in the cecum and identified to be invasive adenocarcinoma with stage IV1b (T4b, N2a, M1). Ingenuity pathway analysis (IPA) showed that GNAS were involved in CRC metastasis signaling via APC, BRAF, GSK3A, KRAS, MLH1, MLH2, MLH3, Notch family, and PIK3C family. Conclusion: This work provides insight into identification of novel somatic mutations in GNAS coupled with promoter hypomethylation at the same locus using WES and RRBS. GNAS SNV resulted in gain of function of G-protein signaling that may play a pivotal role in CRC Identification the biological significance of GNAS in CRC may introduce a new target for colorectal cancer diagnosis and treatment. Citation Format: Hamed Rahi, Sohaila Soltani, Mohammad Daremipouran, Hassan Brim, Eward L. Lee, Alfreda Woods, Wayne Frederick, Adeyinka O. Laiyemo, Joe Devaney, Ron Leavitt, Xueguang Sun, Hassan Ashktorab. Novel mutation and hypomethylation define distinct biological subgroups of altered KRAS colon tumors. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1934. doi:10.1158/1538-7445.AM2013-1934

Routine universal screening for Lynch syndrome in colorectal cancer patients in the community setting.

1512 Background: Identification of colorectal cancer (CRC) cases that are due to Lynch Syndrome (LS) is important to prevent secondary malignancies or development of additional malignancies among relatives. Utilization of clinical criteria to select CRC patients for laboratory testing fails to identify a significant proportion of patients whose CRC is due to LS. Therefore, universal screening for LS among CRC patients has been advocated by the Evaluation of Genomic Applications in Practice and Prevention Working Group. However, the feasibility of routine universal screening has not been evaluated in a community-based, non-research setting. We implemented a universal screening protocol for LS as part of routine care of CRC at Norton Healthcare, a multi-institutional community-based healthcare organization. Methods: Beginning in October 2009, all resected CRC tumors automatically underwent immunohistochemistry analysis (IHC) for Lynch Syndrome-associated mismatch repair gene (MMR) expression. Selected patients who underexpressed MLH1 also underwent testing for the BRAF V600E mutation. Patients who had a BRAF V600E mutation were considered to have sporadic CRC. All other patients with abnormal IHC were automatically referred for genetic counseling. We retrospectively reviewed the outcomes of genetic counseling in all patients referred through this universal screening protocol. Results: Between October 2009 and December 2011, 388 patients underwent resection of CRC, all of whom had IHC for MMR expression. Seventy patients were identified as having abnormal IHC. Sixty-two had MLH1/PMS2 underexpression, of which 18 underwent BRAF testing and 13 had a BRAF V600E mutation. Eight had MSH2/MSH6 underexpression. Nine patients have been confirmed to have LS, 31 have been found not to have LS, and 19 are in the process of evaluation. Seven patients declined genetic counseling, and 4 died before they could be adequately evaluated. Conclusions: Universal screening for CRC due to LS, using IHC with select BRAF V600E mutation testing and automated referral for genetic counseling, is feasible in the community setting. Funded in part with federal funds: NCI, NIH, Contract No. HHSN261200800001.

Colorectal Cancer Due to Deficiency in DNA Mismatch Repair Function

Lynch syndrome (LS) is an autosomal dominant cancer predisposition syndrome attributable to deleterious germline mutations in mismatch repair (MMR) genes. The syndrome is typified by early-onset, frequently right-sided colorectal cancers (CRCs) with characteristic histologic features and tendency for multiplicity and an increased risk for extracolonic tumors at particular sites; it accounts for 1% to 5% of CRC. Deficient mismatch repair (dMMR) function manifests as immunohistochemically detectable absence of one or more MMR proteins and microsatellite instability (MSI). Approximately 15% of sporadic, noninherited CRC are characterized by high-level MSI, nearly always owing to transcriptional silencing of MLH1; these sporadic and LS cases exhibit considerable phenotypic overlap. Identification of CRC with dMMR is desirable to identify LS and because MSI status is prognostic and potentially predictive. This review will discuss the history of LS, the principles of MMR and MSI, the clinicopathologic features of LS-associated and sporadic high-level MSI CRC, the fundamentals of clinical testing for dMMR CRC, and the results of the Columbus-area Lynch syndrome study. We conclude with our approach to population-based LS screening based on institutional experience with nearly 2000 cases.

Circulating microRNAs as potential blood-based biomarkers for detection of colorectal cancer

e15040 Background: Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. While there is a strong correlation between stage and prognosis in this disease, current screening methods for CRC have significant limitations, and newer technological approaches are desired. Circulating nucleic acids in body fluids have been studied as a source for diagnostic information and for cancer screening, yet the potential of microRNAs, a family of small non-coding regulatory RNAs, has not yet been thoroughly explored. Here we investigated the utility of microRNAs as potential serum biomarkers for early detection of CRC. Methods: We developed protocols for extracting and quantifying microRNA levels in serum. Serum levels of more than 350 microRNAs were measured using qRT-PCR on samples from 10 healthy controls and 10 CRC patients. Most microRNAs showed consistent levels across different individuals. A subset of microRNAs had significant differences in abundance between the two groups and was studied on a larger cohort of 118 patients and controls. Results: We initially identified a subset of microRNAs that showed significant differential abundance between sera of CRC patients and controls. Measuring the serum levels of 22 microRNAs on a cohort of 118 patients and controls, we showed that levels of circulating microRNAs can be very informative in the identification of CRC. Conclusions: The results demonstrate the potential of the microRNA processing and analysis methods that we developed. Certain microRNAs were found in different amounts in sera of CRC patients compared to healthy controls. Thus, circulating microRNAs represent promising candidates for diagnostic biomarkers in CRC. [Table: see text]

T2091 A Clinical-Pathological Predictive Model for the Identification of Colorectal Cancer with Mismatch Repair Deficit

T2091 A Clinical-Pathological Predictive Model for the Identification of Colorectal Cancer with Mismatch Repair Deficit

Identification of colorectal cancer, adenoma, and inflammatory bowel disease specific gene expression patterns using whole genomic oligonucleotide microarray system

Discrimination and classification of colorectal diseases (adenoma, colorectal cancer, inflammatory bowel disease) using biopsy samples and expression microarrays, has not been solved yet, nevertheless, it can contribute to the understanding of the colonic diseases. Total ribonucleic acid was extracted, amplified and biotinylated from frozen colonic biopsies of 15 patients with colorectal cancer, 15 with adenoma, 14 with inflammatory bowel disease and 8 normal controls. Genome-wide gene expression profile was evaluated by Human Genome U133 Plus 2.0 microarrays. Two independent methods were used for data normalization and "Prediction Analysis of Microarrays" was performed for feature selection. Leave one-out stepwise discriminant analysis was performed. The expression results were verified by real-time polymerase chain reaction. Top validated genes included CD44 antigen, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; collagen IValpha1, lipocalin-2, calumenin, aquaporin-8 genes in colorectal cancer; and lipocalin-2, ubiquitin D and interferon induced transmembrane protein 2 genes in inflammatory bowel disease. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes. The expression of 94% of the 52 genes measured by Taqman real-time polymerase chain reaction correlated with the results obtained using Affymetrix microarrays at a significance of p < 0.05. We successfully performed whole genomic microarray analysis to identify discriminative signatures using routine biopsy samples. The results set up data warehouse which can be further mined.

Identification of colorectal cancer using proteomic patterns in serum

At present there is no serological parameter with high sensitivity and specificity to diagnose colorectal cancer. This study aimed at establishing a serum protein fingerprinting technique coupled with a pattern-matching algorithm to distinguish colorectal cancer from benign colorectal diseases and healthy people. Preliminary group and test group were both random selected serum samples, which each comprises 73 cases of colorectal cancer, 31 healthy people, and 16 cases of benign colorectal diseases. The sera of the test group was combined with the surface of the IMAC3 proteinchip. Then reading data of surface enhanced laser desorption/ionization- time of flight-mass spectrometry (SELDI-TOF-MS) was analyzed by Biomarker Wizard software and Biomarker pattern software to get a classification rule of tree, which is standard configuration that can distinguish the sera of colorectal cancer patients from the sera of benign colorectal disease patients and healthy people, and the standard was approved test validity by double-blindly in the test group. At the key M/Z values of 4 467 Da, 8 131 Da, 8 939 Da, 9 192 Da, 9 134 Da, 8 221 Da, 5 928 Da, 8 324 Da, 11 732 Da, protein contents of the three classes in preliminary group are obviously different by the software analysis. And the classification rule of tree was discovered, and corresponding correct ratio was 98.33% (118/120), corresponding sensitivity was 97.26% (71/73) and corresponding specificity was 100% (47/47); after double-blind examining the test group with that rule, the corresponding correct ratio was 96.77% (116/120),the corresponding sensitivity was 95.89% (70/73) and the corresponding specificity was 97.87%(46/47). Via comparative proteomics research in the sera of colorectal cancer patients and benign colorectal disease patients and healthy people, the group of protein was obviously different in pathological process in discovering colorectal cancer.