Li Yang, Sun Rongrong, Zhang Youwei, Yuan Yuan, Miao Yufeng
Department of Central Laboratory, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, 221009 China.
Department of Medical Oncology, Xuzhou Central Hospital, Clinical School of Xuzhou Medical University, Xuzhou, 221009 China.
Cancer Cell Int. 2020 Jul 6;20:284. doi: 10.1186/s12935-020-01374-w. eCollection 2020.
Evidence suggests that altered DNA methylation plays a causative role in the occurrence, progression and prognosis of gastric cancer (GC). Thus, methylated-differentially expressed genes (MDEGs) could potentially serve as biomarkers and therapeutic targets in GC.
Four genomics profiling datasets were used to identify MDEGs. Gene Ontology enrichment and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis were used to explore the biological roles of MDEGs in GC. Univariate Cox and LASSO analysis were used to identify survival-related MDEGs and to construct a MDEGs-based signature. The prognostic performance was evaluated in two independent cohorts.
We identified a total of 255 MDEGs, including 192 hypermethylation-low expression and 63 Hypomethylation-high expression genes. The univariate Cox regression analysis showed that 83 MDEGs were associated with overall survival. Further we constructed an eight-MDEGs signature that was independent predictive of prognosis in the training cohort. By applying the eight-MDEGs signature, patients in the training cohort could be categorized into high-risk or low-risk subgroup with significantly different overall survival (HR = 2.62, 95% CI 1.71-4.02, P < 0.0001). The prognostic value of the eight-MDEGs signature was confirmed in another independent GEO cohort (HR = 1.35, 95% CI 1.03-1.78, P = 0.0302) and TCGA-GC cohort (HR = 1.85, 95% CI 1.16-2.94, P = 0.0084). Multivariate cox regression analysis proved the eight-MDEGs signature was an independent prognostic factor for GC.
We have thus established an innovative eight-MDEGs signature that is predictive of overall survival and could be a potentially useful guide for personalized treatment of GC patients.
有证据表明,DNA甲基化改变在胃癌(GC)的发生、发展和预后中起因果作用。因此,甲基化差异表达基因(MDEGs)可能作为GC的生物标志物和治疗靶点。
使用四个基因组分析数据集来鉴定MDEGs。采用基因本体富集分析和京都基因与基因组百科全书通路富集分析来探索MDEGs在GC中的生物学作用。使用单变量Cox分析和LASSO分析来鉴定与生存相关的MDEGs,并构建基于MDEGs的特征。在两个独立队列中评估预后性能。
我们共鉴定出255个MDEGs,包括192个高甲基化低表达基因和63个低甲基化高表达基因。单变量Cox回归分析显示,83个MDEGs与总生存期相关。进一步构建了一个由八个MDEGs组成的特征,该特征在训练队列中是独立的预后预测指标。应用这八个MDEGs组成的特征,训练队列中的患者可分为高风险或低风险亚组,其总生存期有显著差异(HR = 2.62,95%CI 1.71 - 4.02,P < 0.0001)。在另一个独立的GEO队列(HR = 1.35,95%CI 1.03 - 1.78,P = 0.0302)和TCGA - GC队列(HR = 1.85,95%CI 1.16 - 2.94,P = 0.0084)中证实了这八个MDEGs组成的特征的预后价值。多变量Cox回归分析证明,这八个MDEGs组成的特征是GC的独立预后因素。
因此,我们建立了一种创新的由八个MDEGs组成的特征,可预测总生存期,可能为GC患者的个性化治疗提供有用指导。