【摘要】 目的：探讨基于脂肪酸代谢（FAM）相关基因构建预测模型评估肝细胞癌（HCC）预后的生物信息学问题。方法：从公共数据库中收集HCC患者RNA测序数据和临床信息，通过单变量Cox回归分析、LASSO分析和多因素Cox回归分析构建FAM相关基因模型，根据特征基因的表达量及权重构建风险评分系统，将样品分为高、低风险组，分析不同风险HCC患者预后、免疫特征的差异。结果：成功构建FAM相关基因模型，并验证此模型在HCC预后评估中具有稳健预测价值。高风险组患者肿瘤促进细胞显著富集。结论：FAM相关基因与HCC患者预后和免疫状态密切相关，可为HCC的个体化治疗提供新思路。更多还原

【Abstract】 Objective: To construct a fatty acid metabolism(FAM)-related gene model for prognostic evaluation in hepatocellular carcinoma(HCC). Methods: RNA sequencing data and clinical information of HCC patients were collected from public databases. Univariate Cox regression, LASSO regression, and multivariate Cox regression analyses were employed to establish a FAM-related gene model. A risk scoring system was developed based on gene expression and coefficients, stratifying patients into high-and low-risk groups. Prognosis and immune characteristics were compared between groups. Results: The FAM-related gene model demonstrated robust prognostic value. High-risk patients exhibited significant enrichment of tumor-promoting cells. Conclusion: FAM-related genes are closely associated with HCC prognosis and immune status, providing insights for personalized therapy.更多还原