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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.<\/jats:p>\n          <jats:p>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\u2009&gt;\u20090.8) between HCT and ANT.<\/jats:p>\n          <jats:p>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.<\/jats:p>","DOI":"10.1186\/s12967-025-06698-7","type":"journal-article","created":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T10:50:32Z","timestamp":1749639032000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Metabolic reprogramming in hepatocellular carcinoma: an integrated omics study of lipid pathways and their diagnostic potential"],"prefix":"10.1186","volume":"23","author":[{"given":"Peng","family":"Dai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanyan","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shujing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianghong","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaopeng","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueliang","family":"Qin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiming","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daguang","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,6,11]]},"reference":[{"issue":"3","key":"6698_CR1","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1007\/s10555-023-10084-4","volume":"42","author":"Y Wang","year":"2023","unstructured":"Wang Y, Deng B. 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