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.
Department of General Surgery, the First Medical Centre, Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, Beijing, 100853, China.
Cancer Genet. 2021 Apr;252-253:80-86. doi: 10.1016/j.cancergen.2020.12.009. Epub 2021 Jan 2.
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.
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.
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.
We established a prognosis prediction model based on 10 methylation sites, which could evaluate the prognosis of CRC patients.
结直肠癌（CRC）是一种常见的消化道恶性肿瘤，具有较高的发病率和死亡率。准确预测 CRC 患者的预后对于降低死亡率和疾病负担至关重要。
本研究综合分析了来自癌症基因组图谱（TCGA）的 CRC 样本的基因表达和甲基化数据。首先鉴定了肿瘤组织与 CRC 相邻正常组织相比的差异表达基因（DEGs）和差异甲基化 CpGs（DMCs）。通过数据库注释、可视化和综合发现（DAVID）对 DEGs 和 DMCs 进行功能富集分析。采用 Spearman 相关分析筛选与基因表达呈负相关的 DMCs，随后通过 Cox 回归分析进行逐步回归，筛选出用于 CRC 预后预测模型构建的最优 CpGs。
我们在 CRC 肿瘤样本与相邻正常样本相比，共鉴定出 1774 个 DEGs（663 个上调和 1111 个下调）和 11975 个 DMCs（7385 个高甲基化和 4590 个低甲基化）。高甲基化的位点主要位于 CpG 岛，而低甲基化的位点主要位于 N-shore。Spearman 相关分析筛选出 321 个与注释基因表达呈负相关的 DMCs。最终建立了一个由 10 个 CpG 组成的 Cox 回归模型，可以有效地对 CRC 患者进行分层，其总体生存概率的差异与年龄、性别和病理分期无关。
我们建立了一个基于 10 个甲基化位点的预后预测模型，可用于评估 CRC 患者的预后。
