Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, P. R. China.
Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, P. R. China.
Aging (Albany NY). 2020 Nov 16;12(22):22814-22839. doi: 10.18632/aging.103949.
Aberrant promoter methylation and ensuing abnormal gene expression are important epigenetic mechanisms that contribute to colorectal oncogenesis. Yet, the prognostic significance of such methylation-driven genes in colorectal cancer (CRC) remains obscure. Herein, a total of 181 genes were identified as the methylation-driven molecular features of CRC by integrated analysis of the expression profiles and the matched DNA methylation data from The Cancer Genome Atlas (TCGA) database. Among them, a five-gene signature (POU4F1, NOVA1, MAGEA1, SLCO4C1, and IZUMO2) was developed as a risk assessment model for predicting the clinical outcomes in CRC. The Kaplan-Meier analysis and Harrell's C index demonstrated that the risk assessment model significantly distinguished the patients in high or low-risk groups (-value < 0.0001 log-rank test, HR: 2.034, 95% CI: 1.419-2.916, C index: 0.655). The sensitivity and specificity were validated by the receiver operating characteristic (ROC) analysis. Furthermore, different pharmaceutical treatment responses were observed between the high-risk and low-risk groups. Indeed, the methylation-driven gene signature could act as an independent prognostic evaluation biomarker for assessing the OS of CRC patients and guiding the pharmaceutical treatment. Compared with known biomarkers, the methylation-driven gene signature could reveal cross-omics molecular features for improving clinical stratification and prognosis.
异常启动子甲基化和随之而来的异常基因表达是导致结直肠癌发生的重要表观遗传机制。然而，这种甲基化驱动基因在结直肠癌（CRC）中的预后意义仍然不清楚。在此，通过综合分析癌症基因组图谱（TCGA）数据库中的表达谱和匹配的 DNA 甲基化数据，确定了 181 个基因作为 CRC 的甲基化驱动分子特征。其中，开发了一个由五个基因（POU4F1、NOVA1、MAGEA1、SLCO4C1 和 IZUMO2）组成的风险评估模型，用于预测 CRC 的临床结局。Kaplan-Meier 分析和 Harrell 的 C 指数表明，风险评估模型显著区分了高风险和低风险组的患者（-值<0.0001 对数秩检验，HR：2.034，95%CI：1.419-2.916，C 指数：0.655）。通过接受者操作特征（ROC）分析验证了敏感性和特异性。此外，在高风险组和低风险组之间观察到了不同的药物治疗反应。事实上，甲基化驱动基因特征可以作为评估 CRC 患者 OS 的独立预后评估生物标志物，并指导药物治疗。与已知的生物标志物相比，甲基化驱动基因特征可以揭示跨组学的分子特征，以改善临床分层和预后。
