Liu Bing, Dong Zhicheng, Lu Yingzhi, Ma Jianhua, Ma Zhaoming, Wang Hongwei
Department of Radiotherapy, The Second People's Hospital of Lianyungang (Lianyungang Cancer Hospital), Lianyungang, China.
Oncology Department, The Second People's Hospital of Lianyungang (Lianyungang Cancer Hospital), Lianyungang, China.
Evid Based Complement Alternat Med. 2022 Aug 18;2022:3478861. doi: 10.1155/2022/3478861. eCollection 2022.
Identifying gene mutation signatures will enable a better understanding for the occurrence, development, and prognosis of hepatocellular carcinoma (HCC) and provide some potential biomarkers for clinical practice. This study investigated the mutated genes in HCC patients and assessed their relationship with tumor mutation burden (TMB) and prognosis.
The somatic mutation annotation format (MAF) document, mRNA expression matrix, and clinical information of HCC patients were obtained from the International Cancer Genome Consortium (ICGC) and the Cancer Genome Atlas (TCGA) database. The differences of TMB between the mutant type and the wild-type genes were detected using the Mann-Whitney test. The link of gene mutations with prognosis was explored by the Kaplan-Meier analysis. The proportion of 22 immune cells' composition was measured using CIBERSORT algorithm.
The two databases screened 16 common mutated genes, which included TP53, TTN, LRP1B, ZFHX4, MUC16, OBSCN, CSMD3, FLG, CSMD1, SYNE1, SPTA1, USH2A, KMT2C, PCLO, HMCN1, and FAT3. After a series of analysis, MUC16 mutation was found to be highly correlated with TMB and was regarded as an independent factor predicting HCC. Furthermore, gene set enrichment analysis (GSEA) indicated that the MUC16 mutation was significantly involved in HCC cell metabolism.
MUC16 mutation seems to be a valuable potential biomarker for HCC development and its overall survival.
识别基因突变特征将有助于更好地理解肝细胞癌（HCC）的发生、发展和预后，并为临床实践提供一些潜在的生物标志物。本研究调查了HCC患者的突变基因，并评估了它们与肿瘤突变负荷（TMB）和预后的关系。
从国际癌症基因组联盟（ICGC）和癌症基因组图谱（TCGA）数据库中获取HCC患者的体细胞突变注释格式（MAF）文件、mRNA表达矩阵和临床信息。使用曼-惠特尼检验检测突变型和野生型基因之间TMB的差异。通过Kaplan-Meier分析探索基因突变与预后的联系。使用CIBERSORT算法测量22种免疫细胞组成的比例。
两个数据库筛选出16个常见突变基因，包括TP53、TTN、LRP1B、ZFHX4、MUC16、OBSCN、CSMD3、FLG、CSMD1、SYNE1、SPTA1、USH2A、KMT2C、PCLO、HMCN1和FAT3。经过一系列分析，发现MUC16突变与TMB高度相关，并被视为预测HCC的独立因素。此外，基因集富集分析（GSEA）表明MUC16突变显著参与HCC细胞代谢。
MUC16突变似乎是HCC发展及其总生存期的一个有价值的潜在生物标志物。
