Table_2_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（HCC）是一种危及生命且难以治疗的恶性肿瘤，其预后不佳。遗传突变是癌症的标志。迄今为止，尚无由突变基因转录组构建的全面预后模型。突变基因特征在HCC中的预后价值尚不明确。方法：从癌症基因组图谱（TCGA）和国际癌症基因组联盟（ICGC）数据库中招募了RNA表达谱和相应的临床信息。采用最小绝对收缩和选择算子（LASSO）Cox回归分析建立基因特征。通过Kaplan-Meier曲线和时间依赖性受试者工作特征曲线评估预后价值。采用Wilcoxon检验分析不同风险组中免疫检查点基因、细胞周期基因和肿瘤耐药基因的表达。最后，在独立队列中通过定量实时PCR（qRT-PCR）和免疫组化（IHC）验证了HCC与相邻非肿瘤组织之间mRNA和蛋白表达。结果：通过LASSO Cox回归分析建立了包含五个突变基因的预后模型。该模型将患者分为高风险组和低风险组。与低风险组相比，高风险组的患者生存结果显著较差。该预后模型可以准确预测HCC患者的总生存期，并且结合分期时预测总生存期更为准确。此外，与低风险组相比，高风险组中免疫检查点基因、细胞周期基因和肿瘤耐药基因的表达水平更高。此外，在独立样本队列中验证了预后特征基因的表达水平，与TCGA数据库中的RNA测序表达一致。结论：利用与突变相关的基因构建的HCC预测模型对于临床决策和HCC患者的个性化治疗具有重要意义。