Dai Peng, Feng Jing, Dong Yanyan, Zhang Shujing, Cao Jianghong, Cui Xiaopeng, Qin Xueliang, Yang Shiming, Fan Daguang
Department of Hepato-Pancreatic-Biliary Surgery, Shanxi Provincial People's Hospital, Taiyuan, 030000, China.
Department of Gastroenterology, Shanxi Provincial People's Hospital, Taiyuan, 030000, China.
J Transl Med. 2025 Jun 11;23(1):644. doi: 10.1186/s12967-025-06698-7.
Metabolic reprogramming is an important cancer hallmark. Recent studies have indicated that lipid metabolic reprogramming play a potential role in the development of hepatocellular carcinoma (HCC). However, the underlying mechanisms remain incompletely understood. In this study, we employed an integrated multi-omics approach, combining transcriptomic, proteomic, and metabolomic analyses, to explore the lipid metabolism pathways in HCC and evaluate their diagnostic potential.We collected ten pairs of HCC tissues (HCT) and adjacent non-tumor tissues (ANT) from patients undergoing surgical resection. Transcriptomic analysis identified 4,023 differentially expressed genes (DEGs) between HCT and ANT, with significant enrichment in lipid metabolism-related pathways, including fatty acid degradation and steroid hormone biosynthesis. Proteomic analysis revealed 2,531 differentially expressed proteins (DEPs), further highlighting lipid metabolism as a critical driver of HCC development. Metabolomic profiling identified 88 differentially expressed metabolites (DEMs), with notable alterations in lipid-related metabolites. Integrated analysis of transcriptomic, proteomic, and metabolomic data identified six key genes (LCAT, PEMT, ACSL1, GPD1, ACSL4, and LPCAT1) involved in lipid metabolism, which exhibited significant changes at both mRNA and protein levels and correlated strongly with lipid-related metabolites in HCT. Additionally, nine lipid-related metabolites were identified as potential diagnostic biomarkers for HCC, with six metabolites demonstrating high discriminative ability (AUC > 0.8) between HCT and ANT.Our findings provide new insights into the molecular mechanisms of lipid metabolism reprogramming in HCC, emphasize the critical role of lipid metabolism in its pathogenesis. The identification of lipid-related metabolites as potential diagnostic biomarkers holds significant promise for early detection and improved clinical management of HCC. The integrated multi-omics approach as a powerful tool for identifying novel biomarkers and therapeutic targets.
代谢重编程是一种重要的癌症特征。最近的研究表明，脂质代谢重编程在肝细胞癌（HCC）的发展中发挥着潜在作用。然而，其潜在机制仍未完全了解。在本研究中，我们采用了一种综合多组学方法，结合转录组学、蛋白质组学和代谢组学分析，以探索HCC中的脂质代谢途径并评估其诊断潜力。我们从接受手术切除的患者中收集了十对HCC组织（HCT）和相邻的非肿瘤组织（ANT）。转录组分析确定了HCT和ANT之间4023个差异表达基因（DEG），在脂质代谢相关途径中显著富集，包括脂肪酸降解和类固醇激素生物合成。蛋白质组分析揭示了2531个差异表达蛋白质（DEP），进一步突出了脂质代谢作为HCC发展的关键驱动因素。代谢组分析确定了88个差异表达代谢物（DEM），脂质相关代谢物有显著变化。对转录组、蛋白质组和代谢组数据的综合分析确定了六个参与脂质代谢的关键基因（LCAT、PEMT、ACSL1、GPD1、ACSL4和LPCAT1），它们在mRNA和蛋白质水平均表现出显著变化，并且与HCT中脂质相关代谢物密切相关。此外，九种脂质相关代谢物被确定为HCC的潜在诊断生物标志物，其中六种代谢物在HCT和ANT之间表现出高鉴别能力（AUC>0.8）。我们的研究结果为HCC中脂质代谢重编程的分子机制提供了新见解，强调了脂质代谢在其发病机制中的关键作用。将脂质相关代谢物鉴定为潜在诊断生物标志物对HCC的早期检测和改善临床管理具有重要意义。综合多组学方法是识别新型生物标志物和治疗靶点的有力工具。
