ArticleJournal of translational medicine2025
Metabolic reprogramming in hepatocellular carcinoma: an integrated omics study of lipid pathways and their diagnostic potential.
Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Cell-cycle reactivation and hepatocyte identity loss in hepatocellular carcinoma: Transcriptomic hallmarks and validation strategies (Review).Oncology letters · 2026Review
- METTL3- and IGF2BP1-associated m6A regulation of FADS2 contributes to lipid droplet accumulation and malignant progression in non-small cell lung cancer.Translational cancer research · 2026Article
- A Prognostic Risk Model for Hepatocellular Carcinoma Integrating Ferroptosis and Metabolic Reprogramming Signatures.Journal of Cancer · 2026Article
- Artificial intelligence-driven gastrointestinal functional assessment: multimodal imaging, digital biomarkers, and real-time monitoring.Frontiers in physiology · 2026Review
- Cholesterol metabolic rewiring shapes immune remodeling across hepatocarcinogenesis.Frontiers in immunology · 2026Review
- Identification of plasma lipidomic biomarkers for prognostic stratification in advanced gastric cancer treated with PD-1 inhibitor plus chemotherapy.Frontiers in immunology · 2026Article
- Noninvasive Prediction of High Ki-67 Expression in Hepatocellular Carcinoma Using Multiparametric MRI and Clinical Biomarkers.Journal of hepatocellular carcinoma · 2026Article
- The impact of metabolic reprogramming in hepatocellular carcinoma on T cell.Frontiers in immunology · 2025Review
- The U-Shaped Association Between Remnant Cholesterol and Postoperative Survival in Hepatocellular Carcinoma: Development and Validation of an Interpretable Machine Learning Model.Journal of hepatocellular carcinoma · 2025Article
- Cancer stem cells in hepatocellular carcinoma: therapy resistance and emerging treatments.Frontiers in immunology · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.