Dong-Hai Li1, Xiao-Hui Du2, Ming Liu3, Rui Zhang3. 1. Medical School of Chinese PLA; Department of General Surgery, the First Medical Centre, Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, Beijing, 100853, China; Department of General Surgery, The Affiliated Hospital of Inner Mongolia Medical University, No.1,North Passage, Huimin District, Hohhot, Inner Mongolia 010050, China. 2. Department of General Surgery, the First Medical Centre, Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, Beijing, 100853, China. Electronic address: bjduxiaohui@outlook.com. 3. Department of General Surgery, The Affiliated Hospital of Inner Mongolia Medical University, No.1,North Passage, Huimin District, Hohhot, Inner Mongolia 010050, China.
Abstract
BACKGROUND: Colorectal cancer (CRC) is a common malignant tumor of digestive tract which has high incidence and mortality rates. Accurate prognosis prediction of CRC patients is pivotal to reduce the mortality and disease burden. METHODS: In this study, we comprehensively analyzed the gene expression and methylation data of CRC samples from The Cancer Genome Atlas (TCGA). Differential expression genes (DEGs) and methylation CpGs (DMCs) in tumor tissues compared with adjacent normal tissues of CRC were first identified. Functional enrichment analysis of DEGs and DMCs was performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). Spearman correlation analysis was used to screen DMCs that negatively correlated with gene expressions which were subsequently applied to sure independence screening (SIS) along with stepwise regression for screening optimal CpGs for CRC prognosis prediction model construction by Cox regression analysis. RESULTS: We identified a total of 1774 DEGs (663 upregulated and 1111 downregulated) and 11,975 DMCs (7385 hypermethylated and 4590 hypomethylated) in CRC tumor samples compared with adjacent normal samples. The hypermethylated loci were mainly located on CpG island, while the hypomethylated loci were mainly located on N-shore. Spearman correlation analysis screened 321 DMCs that negatively correlated with expressions of their annotated genes. Cox regression model consist of 10 CpGs was finally established which could effectively stratified CRC patients that exhibited significantly different overall survival probability independent of age, gender, and pathological staging. CONCLUSION: We established a prognosis prediction model based on 10 methylation sites, which could evaluate the prognosis of CRC patients.
BACKGROUND:Colorectal cancer (CRC) is a common malignant tumor of digestive tract which has high incidence and mortality rates. Accurate prognosis prediction of CRCpatients is pivotal to reduce the mortality and disease burden. METHODS: In this study, we comprehensively analyzed the gene expression and methylation data of CRC samples from The Cancer Genome Atlas (TCGA). Differential expression genes (DEGs) and methylation CpGs (DMCs) in tumor tissues compared with adjacent normal tissues of CRC were first identified. Functional enrichment analysis of DEGs and DMCs was performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). Spearman correlation analysis was used to screen DMCs that negatively correlated with gene expressions which were subsequently applied to sure independence screening (SIS) along with stepwise regression for screening optimal CpGs for CRC prognosis prediction model construction by Cox regression analysis. RESULTS: We identified a total of 1774 DEGs (663 upregulated and 1111 downregulated) and 11,975 DMCs (7385 hypermethylated and 4590 hypomethylated) in CRC tumor samples compared with adjacent normal samples. The hypermethylated loci were mainly located on CpG island, while the hypomethylated loci were mainly located on N-shore. Spearman correlation analysis screened 321 DMCs that negatively correlated with expressions of their annotated genes. Cox regression model consist of 10 CpGs was finally established which could effectively stratified CRCpatients that exhibited significantly different overall survival probability independent of age, gender, and pathological staging. CONCLUSION: We established a prognosis prediction model based on 10 methylation sites, which could evaluate the prognosis of CRCpatients.