Dataset Information

Novel recurrently mutated genes and a prognostic mutation signature in colorectal cancer.

ABSTRACT:

Background

Characterisation of colorectal cancer (CRC) genomes by next-generation sequencing has led to the discovery of novel recurrently mutated genes. Nevertheless, genomic data has not yet been used for CRC prognostication.

Objective

To identify recurrent somatic mutations with prognostic significance in patients with CRC.

Method

Exome sequencing was performed to identify somatic mutations in tumour tissues of 22 patients with CRC, followed by validation of 187 recurrent and pathway-related genes using targeted capture sequencing in additional 160 cases.

Results

Seven significantly mutated genes, including four reported (APC, TP53, KRAS and SMAD4) and three novel recurrently mutated genes (CDH10, FAT4 and DOCK2), exhibited high mutation prevalence (6-14% for novel cancer genes) and higher-than-expected number of non-silent mutations in our CRC cohort. For prognostication, a five-gene-signature (CDH10, COL6A3, SMAD4, TMEM132D, VCAN) was devised, in which mutation(s) in one or more of these genes was significantly associated with better overall survival independent of tumor-node-metastasis (TNM) staging. The median survival time was 80.4 months in the mutant group versus 42.4 months in the wild type group (p=0.0051). The prognostic significance of this signature was successfully verified using the data set from the Cancer Genome Atlas study.

Conclusions

The application of next-generation sequencing has led to the identification of three novel significantly mutated genes in CRC and a mutation signature that predicts survival outcomes for stratifying patients with CRC independent of TNM staging.

SUBMITTER: Yu J

PROVIDER: S-EPMC4392212 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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Publications

Novel recurrently mutated genes and a prognostic mutation signature in colorectal cancer.

Yu Jun J Wu William K K WK Li Xiangchun X He Jun J Li Xiao-Xing XX Ng Simon S M SS Yu Chang C Gao Zhibo Z Yang Jie J Li Miao M Wang Qiaoxiu Q Liang Qiaoyi Q Pan Yi Y Tong Joanna H JH To Ka F KF Wong Nathalie N Zhang Ning N Chen Jie J Lu Youyong Y Lai Paul B S PB Chan Francis K L FK Li Yingrui Y Kung Hsiang-Fu HF Yang Huanming H Wang Jun J Sung Joseph J Y JJ

Gut 20140620 4

<h4>Background</h4>Characterisation of colorectal cancer (CRC) genomes by next-generation sequencing has led to the discovery of novel recurrently mutated genes. Nevertheless, genomic data has not yet been used for CRC prognostication.<h4>Objective</h4>To identify recurrent somatic mutations with prognostic significance in patients with CRC.<h4>Method</h4>Exome sequencing was performed to identify somatic mutations in tumour tissues of 22 patients with CRC, followed by validation of 187 recurren ...[more]

PMID: 24951259

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Project description:Colorectal cancer (CRC) is second most commonly diagnosed cancer with high morbidity and mortality. The heterogeneity of CRC makes clinical treatment tremendously challenging. Here, we aimed to comprehensively analyze the prognosis of CRC patients based on ANOIKIS- and immune-related genes. ANOIKIS-related genes were identified by differentially analysis of high anoikis score group (ANOIKIS_high group) and low anoikis score group (ANOIKIS_low group) divided by the cutoff value of anoikis score. Immune-related genes were screened by differentially analysis of high immune score group (ImmuneScore_high group) and low immune score group (ImmuneScore_low group) classified by the cutoff value of ImmuneScore. Prognostic ANOIKIS- and immune-related genes were identified by univariate Cox regression analysis. Multivariate Cox regression analysis were used for prognostic model construction. Ferroptosis expression profiles, the infiltration of immune cells, and the somatic mutation status were analyzed and compared. Univariate and multivariate Cox-regression analyses were performed to identify independent prognostic factors for CRC patient. Nomogram that contained the independent prognostic factors was established to predict 1-, 3-, and 5-year OS probability of CRC patients. Three ANOIKIS- and immune-related signatures were applied to construct a prognostic model, which divided the CRC patients into high-risk and low-risk groups. The patients with high-risk scores had obviously shorter OSs than those with low-risk scores. The time dependent ROC curve indicated that the risk score model had a stable performance to predict survival rates. Notably, the age, pathologic T, and risk score could be used independent indicators for CRC prognosis prediction. A nomogram containing the independent prognostic factors showed that the nomogram accurately predicted 1-, 3-, and 5-year survival rates of CRC patients. In our research, a novel prognostic model was developed based on ANOIKIS- and immune-related genes in CRC, which could be used for prognostic prediction of CRC patients.

Project description:Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with an estimated 1.8 million new cases worldwide and associated with high mortality rates of 881 000 CRC-related deaths in 2018. Screening programs and new therapies have only marginally improved the survival of CRC patients. Immune-related genes (IRGs) have attracted attention in recent years as therapeutic targets. The aim of this study was to identify an immune-related prognostic signature for CRC. To this end, we combined gene expression and clinical data from the CRC data sets of The Cancer Genome Atlas (TCGA) into an integrated immune landscape profile. We identified a total of 476 IRGs that were differentially expressed in CRC vs normal tissues, of which 18 were survival related according to univariate Cox analysis. Stepwise multivariate Cox proportional hazards analysis established an immune-related prognostic signature consisting of SLC10A2, FGF2, CCL28, NDRG1, ESM1, UCN, UTS2 and TRDC. The predictive ability of this signature for 3- and 5-year overall survival was determined using receiver operating characteristics (ROC), and the respective areas under the curve (AUC) were 79.2% and 76.6%. The signature showed moderate predictive accuracy in the validation and GSE38832 data sets as well. Furthermore, the 8-IRG signature correlated significantly with tumour stage, invasion, lymph node metastasis and distant metastasis by univariate Cox analysis, and was established an independent prognostic factor by multivariate Cox regression analysis for CRC. Gene set enrichment analysis (GSEA) revealed a relationship between the IRG prognostic signature and various biological pathways. Focal adhesions and ECM-receptor interactions were positively correlated with the risk scores, while cytosolic DNA sensing and metabolism-related pathways were negatively correlated. Finally, the bioinformatics results were validated by real-time RT-qPCR. In conclusion, we identified and validated a novel, immune-related prognostic signature for patients with CRC, and this signature reflects the dysregulated tumour immune microenvironment and has a potential for better CRC patient management.

Dataset Information

Novel recurrently mutated genes and a prognostic mutation signature in colorectal cancer.

Background

Objective

Method

Results

Conclusions

Publications

Novel recurrently mutated genes and a prognostic mutation signature in colorectal cancer.

Similar Datasets

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