Construction and Validation of a Novel Butyrylation-Related Gene Signature Related to Prognosis, Clinical Implications, and Immune Microenvironment Characterization of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common and highly lethal malignant tumor that poses a serious threat to human health. The post-transcriptional modification of proteins known as butyrylation has emerged as a critical factor in tumorigenesis, playing a pivotal role in the initiation and progression of cancer. This study aimed to develop a prognostic risk model for HCC using butyrylation-related genes (BRGs). Differentially expressed BRGs were identified from the LIHC–TCGA data sets, and a prognostic risk model was constructed using LASSO and multivariate regression analysis. The model’s robustness was further confirmed in the GSE14520 cohort. The clinicopathological characteristics, immune features, enrichment pathways, and antitumor drug sensitivity of the BRG signature were also assessed. Additionally, a nomogram was created to improve the predictive accuracy of the model. A set of 16 BRGs, including MMP1, ACOT7, AGPAT5, FLAD1, PDSS1, HSPD1, FKBP1A, AKR1B10, HDAC1, HDAC2, MAPT, ACADS, ACAT1, ACSL6, PDE2A, and PON1, were identified. Kaplan–Meier survival analysis showed that patients in the high-risk group had worse overall survival (OS) and progression-free survival (PFS) compared with those in the low-risk group. Univariate and multivariate Cox regressions, along with LASSO analysis, consistently indicated that the BRG signature is an independent prognostic factor for HCC. Clinical line plots accurately predicted 1, 3, and 5 year survival with AUC values of 0.805, 0.729, and 0.710, respectively. Additionally, the distribution of immune cells varied between different risk groups, and the low-risk group showed more potential for immunotherapy and chemotherapy. This study provides a novel biological basis for prognostic prediction in HCC and offers insights into personalized treatment strategies, including candidate drug selection, for clinicians to guide therapeutic decisions.肝细胞癌（Hepatocellular carcinoma, HCC）是一类常见且高致死性的恶性肿瘤，严重威胁人类健康。蛋白质的丁酰化修饰作为关键的转录后修饰方式，现已被证实为肿瘤发生发展的核心调控因素，在癌症的起始与进展过程中发挥关键作用。本研究旨在基于丁酰化相关基因（butyrylation-related genes, BRGs）构建肝细胞癌的预后风险模型。研究从LIHC-TCGA数据集内筛选得到差异表达的BRGs，通过LASSO回归与多因素回归分析构建预后风险模型，并在GSE14520队列中验证了该模型的稳健性。本研究同时评估了BRG特征的临床病理特征、免疫浸润特征、富集通路及抗肿瘤药物敏感性，此外还构建了列线图以进一步提升模型的预测精准度。 本研究共鉴定出16个丁酰化相关基因，具体包括MMP1、ACOT7、AGPAT5、FLAD1、PDSS1、HSPD1、FKBP1A、AKR1B10、HDAC1、HDAC2、MAPT、ACADS、ACAT1、ACSL6、PDE2A及PON1。Kaplan-Meier生存分析结果显示，高危组患者的总生存期（overall survival, OS）与无进展生存期（progression-free survival, PFS）均显著劣于低危组患者。单因素、多因素Cox回归分析联合LASSO分析均证实，BRG特征是肝细胞癌的独立预后危险因素。该列线图可精准预测患者1年、3年及5年生存率，对应的受试者工作特征曲线下面积（Area Under Curve, AUC）分别为0.805、0.729与0.710。进一步分析显示，不同风险分组的免疫细胞浸润分布存在显著差异，且低危组患者更具备免疫治疗与化疗的潜在获益优势。 本研究为肝细胞癌的预后预测提供了全新的生物学基础，同时为临床医师制定个体化治疗策略（包括候选药物遴选）提供了参考思路，以指导临床治疗决策。