Table_1_A Prognostic Model of 15 Immune-Related Gene Pairs Associated With Tumor Mutation Burden for Hepatocellular Carcinoma.DOCX

IntroductionTumor mutation burden (TMB) is an emerging biomarker for immunotherapy of hepatocellular carcinoma (HCC), but its value for clinical application has not been fully revealed.Materials and MethodsWe used the Wilcox test to identify the differentially expressed immune-related genes (DEIRGs) in groups with high and low TMB as well as screened the immune gene pairs related to prognosis using univariate Cox regression analysis. A LASSO Cox regression prognostic model was developed by combining The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) with the International Cancer Genome Consortium (ICGC) LIRI-JP cohort, and internal (TCGA, ICGC) and external (GSE14520) validation analyses were conducted on the predictive value of the model. We also explored the relationship between the prognostic model and tumor microenvironment via the ESTIMATE algorithm and performed clinical correlation analysis by the chi-square test, revealing its underlying molecular mechanism with the help of Gene Set Enrichment Analysis (GSEA).ResultsThe prognostic model consisting of 15 immune gene pairs showed high predictive value for short- and long-term survival of HCC in three independent cohorts. Based on univariate multivariate Cox regression analysis, the prognostic model could be used to independently predict the prognosis in each independent cohort. The immune score, stromal score, and estimated score values were lower in the high-risk group than in the low-risk group. As shown by the chi-square test, the prognostic model exhibited an obvious correlation with the tumor stage [American Joint Committee on Cancer tumor–node–metastasis (AJCC-TNM) (p < 0.001), Barcelona Clinic Liver Cancer (BCLC) (p = 0.003)], histopathological grade (p = 0.033), vascular invasion (p = 0.009), maximum tumor diameter (p = 0.013), and background of liver cirrhosis (p < 0.001). GSEA revealed that the high-risk group had an enrichment of many oncology features, including the cell cycle, mismatch repair, DNA replication, RNA degradation, etc.ConclusionOur research developed and validated a reliable prognostic model associated with TMB for HCC, which may help to further enrich the therapeutic targets of HCC.

引言肿瘤突变负荷（TMB）作为肝癌（HCC）免疫治疗的潜在生物标志物，日益受到关注，但其临床应用价值尚未得到充分揭示。研究方法中，我们采用Wilcox检验识别高、低TMB组别中差异表达的免疫相关基因（DEIRGs），并通过单因素Cox回归分析筛选与预后相关的免疫基因对。结合癌症基因组图谱肝脏肝癌（TCGA-LIHC）与国际癌症基因组联盟（ICGC）LIRI-JP队列，构建了LASSO Cox回归预后模型，并在内部（TCGA、ICGC）及外部（GSE14520）数据集上进行了模型的预测价值验证。此外，通过ESTIMATE算法探究预后模型与肿瘤微环境之间的关系，并借助卡方检验进行临床相关性分析，辅以基因集富集分析（GSEA）揭示其潜在的分子机制。结果显示，由15对免疫基因组成的预后模型在三个独立队列中对HCC的短期及长期生存具有较高的预测价值。基于单因素多因素Cox回归分析，该模型可独立预测每个独立队列中的预后。高风险组的免疫评分、间质评分和估计评分值均低于低风险组。卡方检验结果表明，预后模型与肿瘤分期[美国癌症联合委员会肿瘤-节点-转移（AJCC-TNM）分期（p < 0.001）、巴塞罗那肝脏癌症（BCLC）分期（p = 0.003）]、病理学分级（p = 0.033）、血管侵袭（p = 0.009）、最大肿瘤直径（p = 0.013）和肝硬化的背景（p < 0.001）表现出显著的相关性。GSEA分析发现，高风险组在多种肿瘤特征中富集，包括细胞周期、错配修复、DNA复制、RNA降解等。结论本研究开发并验证了一种与TMB相关的HCC可靠预后模型，该模型有望进一步丰富HCC的治疗靶点。