Chen Jie, Wang Xicheng, Wang Xining, Li Wenxin, Shang Changzhen, Chen Tao, Chen Yajin
Department of Hepatobiliary Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Front Genet. 2020 Feb 27;11:99. doi: 10.3389/fgene.2020.00099. eCollection 2020.
Although great progress has been made in treatment against hepatitis virus infection, the prognosis of hepatocellular carcinoma (HCC) remains unsatisfied. Therefore, there is an unmet need to explore biomarkers or prognostic models for monitoring non-viral hepatocellular carcinoma. Accumulating evidence indicates that DNA methylation participates in carcinogenesis of malignancies. In the present study, we analyzed 101 non-viral HCC patients from TCGA database to figure out methylation-driven genes (MDGs) that might get involved in non-viral HCC pathogenesis using MethyMix algorithm. Then we picked out 8 key genes out of 137 MDGs that could affect the overall survival (OS) of both methylation and expression level. Using PCA, Uni-variate, Multi-variate, and LASSO cox regression analyses, we confirmed the potential prognostic value of these eight epigenetic genes. Ultimately, combined with immunohistochemistry (IHC), ROC, OS, and GSEA analyses, fat storage-inducing transmembrane protein1 (FITM1) was identified as a novel tumor suppressor gene in non-viral HCC and an applicable FITM1-methylation-based signature was built in a training set and validated in a testing set. Briefly, our work provides several potential biomarkers, especially FITM1, as well as a new method for disease surveillance and treatment strategy development.
尽管在抗肝炎病毒感染治疗方面取得了巨大进展，但肝细胞癌（HCC）的预后仍不尽人意。因此，迫切需要探索用于监测非病毒性肝细胞癌的生物标志物或预后模型。越来越多的证据表明，DNA甲基化参与恶性肿瘤的致癌过程。在本研究中，我们分析了来自TCGA数据库的101例非病毒性HCC患者，使用MethyMix算法找出可能参与非病毒性HCC发病机制的甲基化驱动基因（MDG）。然后，我们从137个MDG中挑选出8个关键基因，这些基因在甲基化和表达水平上均会影响总生存期（OS）。通过主成分分析（PCA）、单变量、多变量和LASSO Cox回归分析，我们证实了这八个表观遗传基因的潜在预后价值。最终，结合免疫组化（IHC）、受试者工作特征曲线（ROC）、总生存期（OS）和基因集富集分析（GSEA），脂肪储存诱导跨膜蛋白1（FITM1）被确定为非病毒性HCC中的一种新型肿瘤抑制基因，并在训练集中构建了基于FITM1甲基化的适用特征，并在测试集中进行了验证。简而言之，我们的工作提供了几种潜在的生物标志物，尤其是FITM1，以及一种用于疾病监测和治疗策略制定的新方法。
