Hepatocellular carcinoma (HCC), which has become one of the most significant malignancies causing cancer-related mortality, presents genetic and phenotypic heterogeneity that makes predicting prognosis challenging. Aging-related genes have been increasingly reported as significant risk factors for many kinds of malignancies, including HCC. In this study, we comprehensively dissected the features of transcriptional aging-relevant genes in HCC from multiple perspectives. We applied public databases and self-consistent clustering analysis to classify patients into C1, C2, and C3 clusters. The C1 cluster had the shortest overall survival time and advanced pathological features. Least absolute shrinkage and selection operator (LASSO) regression analysis was adopted to build the prognostic prediction model based on six aging-related genes (HMMR, S100A9, SPP1, CYP2C9, CFHR3, and RAMP3). These genes were differently expressed in HepG2 cell lines compared with LO2 cell lines measured by the mRNA expression level. The high-risk score group had significantly more immune checkpoint genes, higher tumor immune dysfunction and exclusion score, and stronger chemotherapy response. The results indicated that the age-related genes have a close correlation with HCC prognosis and immune characteristics. Overall, the model based on six aging-associated genes demonstrated great prognostic prediction ability.

中文翻译：

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对衰老相关基因的基于特征的表型进行分类，以确定 HCC 的预后和免疫特征

肝细胞癌 (HCC) 已成为导致癌症相关死亡率的最重要的恶性肿瘤之一，其具有遗传和表型异质性，这使得预测预后具有挑战性。越来越多的报道称，衰老相关基因是多种恶性肿瘤（包括 HCC）的重要危险因素。在本研究中，我们从多个角度全面剖析了 HCC 中转录衰老相关基因的特征。我们应用公共数据库和自洽聚类分析将患者分为 C1、C2 和 C3 集群。C1 簇具有最短的总生存时间和先进的病理特征。采用最小绝对收缩和选择算子（LASSO）回归分析建立基于6个衰老相关基因的预后预测模型（HMMR、S100A9、SPP1、CYP2C9、CFHR3和RAMP3）。与通过 mRNA 表达水平测量的 LO2 细胞系相比，这些基因在 HepG2 细胞系中的表达不同。高危评分组免疫检查点基因明显增多，肿瘤免疫功能障碍和排除评分更高，化疗反应更强。结果表明，年龄相关基因与HCC预后和免疫特征密切相关。总体而言，基于六个衰老相关基因的模型表现出强大的预后预测能力。