Table_4_Comprehensive Analysis Identified Mutation-Gene Signature Impacts the Prognosis Through Immune Function in Hepatocellular Carcinoma.xlsx

BackgroundHepatocellular carcinoma (HCC) is a life-threatening and refractory malignancy with poor outcome. Genetic mutations are the hallmark of cancer. Thus far, there is no comprehensive prognostic model constructed by mutation-gene transcriptome in HCC. The prognostic value of mutation-gene signature in HCC remains elusive.
MethodsRNA expression profiles and the corresponding clinical information were recruited from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was employed to establish gene signature. Kaplan–Meier curve and time-dependent receiver operating characteristic curve were implemented to evaluate the prognostic value. The Wilcoxon test was performed to analyze the expression of immune checkpoint genes, cell cycle genes, and tumor drug resistance genes in different risk groups. Finally, quantitative real-time PCR (qRT-RCR) and immunohistochemistry (IHC) were performed to validate the mRNA and protein expression between HCC and adjacent nontumorous tissues in an independent cohort.
ResultsA prognostic model consisting of five mutated genes was established by LASSO Cox regression analysis. The prognostic model classified patients into high- and low-risk groups. Compared with the low‐risk group, patients in the high‐risk group had significantly worse survival results. The prognostic model can accurately predict the overall survival of HCC patients and predict overall survival more accurately when combined with stage. Furthermore, the immune checkpoint genes, cell cycle genes, and tumor drug resistance genes were higher expressed in the high-risk group compared in the low-risk group. In addition, the expression level of prognostic signature genes was validated in an independent sample cohort, which was consistent with RNA sequencing expression in the TCGA database.
ConclusionThe prediction model of HCC constructed using mutation-related genes is of great significance for clinical decision making and the personalized treatment of patients with HCC.

背景
肝细胞癌（Hepatocellular carcinoma, HCC）是一类致命且难治的恶性肿瘤，预后不佳。基因突变是癌症的标志性特征。迄今为止，尚未有基于突变基因转录组构建的肝细胞癌综合预后模型，突变基因特征在肝细胞癌中的预后价值仍有待阐明。
方法
本研究从癌症基因组图谱（The Cancer Genome Atlas, TCGA）与国际癌症基因组联盟（International Cancer Genome Consortium, ICGC）数据库中获取RNA表达谱及对应临床信息。采用最小绝对收缩和选择算子（Least Absolute Shrinkage and Selection Operator, LASSO）Cox回归分析构建基因特征模型。通过Kaplan-Meier曲线与时间依赖性受试者工作特征曲线评估其预后价值，使用Wilcoxon检验分析不同风险组中免疫检查点基因、细胞周期基因及肿瘤耐药基因的表达差异。最后，在独立队列中采用实时定量聚合酶链反应（quantitative real-time PCR, qRT-RCR）与免疫组织化学（IHC）验证肝细胞癌组织与癌旁非肿瘤组织的mRNA及蛋白表达水平。
结果
本研究通过LASSO Cox回归分析构建了由5个突变基因组成的预后模型，该模型可将患者划分为高风险组与低风险组。与低风险组患者相比，高风险组患者的生存结局显著更差。该预后模型能够准确预测肝细胞癌患者的总生存期，且结合临床分期后预测准确性进一步提升。此外，高风险组中免疫检查点基因、细胞周期基因及肿瘤耐药基因的表达水平均显著高于低风险组。最后，在独立样本队列中验证了预后特征基因的表达水平，其结果与TCGA数据库中的RNA测序表达结果一致。
结论
本研究基于突变相关基因构建的肝细胞癌预测模型，对肝细胞癌患者的临床决策与个体化治疗具有重要的指导意义。