Liu Xiao-Ping, Ju Lingao, Chen Chen, Liu Tongzu, Li Sheng, Wang Xinghuan
Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
Front Cell Dev Biol. 2020 Oct 15;8:572628. doi: 10.3389/fcell.2020.572628. eCollection 2020.
DNA methylation based prognostic factor for patients with clear cell renal cell carcinoma (ccRCC) remains unclear. In the present study, we identified survival-related DNA methylation sites based on the differentially methylated DNA CpG sites between normal renal tissue and ccRCC. Then, these survival-related DNA methylation sites were included into an elastic net regularized Cox proportional hazards regression (CoxPH) model to build a DNA methylation-based panel, which could stratify patients into different survival groups with excellent accuracies in the training set and test set. External validation suggested that the DNA methylation-based panel could effectively distinguish normal controls from tumor samples and classify patients into metastasis group and non-metastasis group. The nomogram containing DNA methylation-based panel was reliable in clinical settings. Higher total mutation number, SCNA level, and MATH score were associated with higher methylation risk. The innate immune, ratio between CD8T cell versus Treg cell as well as Th17 cell versus Th2 cell were significantly decreased in high methylation risk group. In inclusion, we developed a DNA methylation-based panel which might be independent prognostic factor in ccRCC. Patients with higher methylation risk were associated genomic alteration and poor immune microenvironment.
基于DNA甲基化的肾透明细胞癌(ccRCC)患者预后因素仍不明确。在本研究中,我们基于正常肾组织和ccRCC之间差异甲基化的DNA CpG位点,鉴定出与生存相关的DNA甲基化位点。然后,将这些与生存相关的DNA甲基化位点纳入弹性网络正则化Cox比例风险回归(CoxPH)模型,构建基于DNA甲基化的模型,该模型可在训练集和测试集中以优异的准确性将患者分层为不同的生存组。外部验证表明,基于DNA甲基化的模型能够有效区分正常对照和肿瘤样本,并将患者分为转移组和非转移组。包含基于DNA甲基化模型的列线图在临床环境中是可靠的。较高的总突变数、SCNA水平和MATH评分与较高的甲基化风险相关。高甲基化风险组中先天免疫、CD8T细胞与Treg细胞的比例以及Th17细胞与Th2细胞的比例显著降低。此外,我们开发了一种基于DNA甲基化的模型,它可能是ccRCC的独立预后因素。甲基化风险较高的患者与基因组改变和不良免疫微环境相关。