Peng Qiliang, Zhou Yibin, Jin Lu, Cao Cheng, Gao Cheng, Zhou Jianfang, Yang Dongrong, Zhu Jin
Department of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Institute of Radiotherapy & Oncology, Soochow University, Suzhou, China.
Transl Androl Urol. 2020 Jun;9(3):1082-1098. doi: 10.21037/tau-19-853.
Growing evidence has shown that genetic or epigenetic alterations are highly involved in the initiation and progression of renal cell carcinoma (RCC). This study aimed to find prognostic methylation markers in clear cell RCC (ccRCC).
In this study, we developed and confirmed an integrated and comprehensive methylation signature by integrating DNA methylation, gene expression, and The Cancer Genome Atlas (TCGA) survival data. First, the methylation signature was found and checked based on data analysis of published datasets. Then, independent predictive factors were selected using the Cox proportional model and incorporated into the nomogram. Finally, the predictive nomogram was derived and validated using a concordance index and calibration plots.
A series of differentially expressed and methylated genes were identified. After intersection analysis, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, protein-protein interaction (PPI) analysis, and correlation analysis, FCGR1A, F2, and NOD2 were established as a predictive signature. According to the Kaplan-Meier survival analysis, the risk score system based on the predictive signature was able to stratify the patients into high- and low-risk groups with significantly different overall survival. The receiver operating characteristic (ROC) analysis further showed that the predictive signature yielded high sensitivity and specificity in predicting the prognosis outcome of ccRCC patients. Moreover, univariate and multivariate Cox regression analysis confirmed that the three-gene methylation signature was an independent prognostic factor in ccRCC. Finally, a nomogram comprising the predictive signature and several independent variables were constructed and proved to effectively predict ccRCC patient survival.
The three-gene methylation signature was revealed to be a potential novel and independent adverse predictor of prognosis for ccRCC patients and may serve as a promising marker for treatment management and survival outcome improvement. However, substantial validation experiments are required to characterize the molecular background of the predictive signature.
越来越多的证据表明，基因或表观遗传改变在肾细胞癌（RCC）的发生和发展中高度相关。本研究旨在寻找透明细胞肾细胞癌（ccRCC）的预后甲基化标志物。
在本研究中，我们通过整合DNA甲基化、基因表达和癌症基因组图谱（TCGA）生存数据，开发并验证了一个综合全面的甲基化特征。首先，基于已发表数据集的数据分析找到并检查甲基化特征。然后，使用Cox比例模型选择独立预测因子并纳入列线图。最后，使用一致性指数和校准图推导并验证预测列线图。
鉴定出一系列差异表达和甲基化的基因。经过交集分析、基因本体（GO）分析、京都基因与基因组百科全书（KEGG）通路分析、蛋白质-蛋白质相互作用（PPI）分析和相关性分析，FCGR1A、F2和NOD2被确立为预测特征。根据Kaplan-Meier生存分析，基于预测特征的风险评分系统能够将患者分为总生存期有显著差异的高风险和低风险组。受试者工作特征（ROC）分析进一步表明，预测特征在预测ccRCC患者的预后结果方面具有高敏感性和特异性。此外，单因素和多因素Cox回归分析证实，三基因甲基化特征是ccRCC的独立预后因素。最后，构建了一个包含预测特征和几个独立变量的列线图，并证明其能有效预测ccRCC患者的生存情况。
三基因甲基化特征被揭示为ccRCC患者预后的一种潜在新型独立不良预测因子，可能作为治疗管理和改善生存结果的有前景标志物。然而，需要大量验证实验来表征预测特征的分子背景。
