【摘要】 目的 本研究旨在鉴定肝细胞癌(HCC)中与琥珀酸代谢相关的分子亚型并构建预后模型，以期为HCC患者的预后评估和个性化治疗提供新的生物标志物和理论支持。方法 从公共数据库中下载HCC相关数据集，筛选差异表达的琥珀酸代谢相关基因(SMRGs)。随后对HCC样本进行聚类，鉴定琥珀酸代谢相关亚型。接着通过单因素Cox及最小绝对收缩和选择算子(LAASO)分析鉴定出预后基因，并构建风险模型和预后模型。结果 共筛选出227个差异表达的SMRGs,并确定了两个分子亚型，这两个亚型的生存期存在显著差异。同时还鉴定出6个预后基因，并基于这6个预后基因构建了一个可靠的风险模型。独立预后分析表明，风险评分和病理分期显著影响患者生存期，风险评分对HCC预后具有重要预测价值。结论 本研究确定了两个分子亚型，并构建了一个基于6个基因的风险模型，该模型能够有效预测HCC患者的预后，为HCC的早期诊断、预后评估和个体化治疗提供了新的视角和潜在的生物标志物。更多还原

【Abstract】 Objective To identify the molecular subtypes associated with succinic acid metabolism in hepatocellular carcinoma(HCC) and construct a prognostic model, with a view to providing new biomarkers and theoretical support for prognosis assessment and personalized treatment of HCC patients.Methods HCC-related datasets were downloaded from public databases.Differentially expressed succinic acid metabolism-related genes(DE-SMRGs) were screened.HCC samples were clustered to identify succinic acid metabolism-related subtypes using consensus clustering.Prognostic genes were identified through univariate Cox and least absolute shrinkage and selection operator(LASSO) regression analyses, and a risk model was subsequently constructed.Results A total of 227 DE-SMRGs were identified.Two molecular subtypes with significant differences in survival time were determined.Six prognostic genes were identified, and a reliable 6-gene risk model was constructed.Independent prognostic analysis indicates that risk scores and pathological staging significantly impact patient survival, with risk scores having significant predictive value for HCC prognosis.Conclusion This study identified two molecular subtypes and successfully constructed a risk model based on 6 genes, which can effectively predict the prognosis of HCC patients, providing a new perspective and potential biomarkers for early diagnosis, prognosis assessment and individualized treatment of HCC.更多还原