ArticleFrontiers in oncology2023
Hepatocellular carcinoma subtypes based on metabolic pathways reveals potential therapeutic targets.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 8 citations in OpenAlex.
- Integrated Multi-Omics Analysis Reveals Cytokine Network Dynamics and Prognostic Signatures in Hepatitis B Virus-Associated Hepatocellular Carcinoma.Applied biochemistry and biotechnology · 2026Article
- Molecular classification of hepatocellular carcinoma based on zoned metabolic feature and oncogenic signaling pathway.Clinical and molecular hepatology · 2025Article
- Unraveling the Heterogeneity of Tumor Immune Microenvironment in Hepatocellular Carcinoma by SingleCell RNA Sequencing and its Implications for Prognosis and Therapeutic Response.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2024Review
- Magnesium Ion: A New Switch in Tumor Treatment.Biomedicines · 2024Review
- Novel phloretin-based combinations targeting glucose metabolism in hepatocellular carcinoma through GLUT2/PEPCK axis of action: in silico molecular modelling and in vivo studies.Medical oncology (Northwood, London, England) · 2023Article
- Construction of a hepatocytes-related and protein kinase-related gene signature in HCC based on ScRNA-Seq analysis and machine learning algorithm.Journal of physiology and biochemistry · 2023Article
- Single-cell transcriptome analysis reveals the clinical implications of myeloid-derived suppressor cells in head and neck squamous cell carcinoma.Pathology oncology research : POR · 2023Article
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Authors and funding
7 authors at 4 institutions in 2 countries.
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Abstract
Introduction: Hepatocellular carcinoma (HCC) is an aggressive malignancy with steadily increasing incidence rates worldwide and poor therapeutic outcomes. Studies show that metabolic reprogramming plays a key role in tumor genesis and progression. In this study, we analyzed the metabolic heterogeneity of epithelial cells in the HCC and screened for potential biomarkers. Methods: The hepatic single-cell RNA sequencing (scRNA-seq) datasets of HCC patients and healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Based on data intergration and measurement of differences among groups, the metabolic epithelial cell subpopulations were identified. The single-cell metabolic pathway was analyzed and the myeloid subpopulations were identified. Cell-cell interaction analysis and single-cell proliferation analysis were performed. The gene expression profiles of HCC patients were obtained from the GSE14520 dataset of GEO and TCGA-LIHC cohort of the UCSC Xena website. Immune analysis was performed. The differentially expressed genes (DEGs) were identified and functionally annotated. Tumor tissues from HCC patients were probed with anti-ALDOA, anti-CD68, anti-CD163, anti-CD4 and anti-FOXP3 antibodies. Results We analyzed the scRNA-seq data from 48 HCC patients and 14 healthy controls. The epithelial cells were significantly enriched in HCC patients compared to the controls (p = 0.011). The epithelial cells from HCC patients were classified into two metabolism-related subpopulations (MRSs) - pertaining to amino acid metabolism (MRS1) and glycolysis (MRS2). Depending on the abundance of these metabolic subpopulations, the HCC patients were also classified into the MRS1 and MRS2 subtype distinct prognoses and immune infiltration. The MRS2 group had significantly worse clinical outcomes and more inflamed tumor microenvironment (TME), as well as a stronger crosstalk between MRS2 cells and immune subpopulations that resulted in an immunosuppressive TME. We also detected high expression levels of ALDOA in the MRS2 cells and HCC tissues. In the clinical cohort, HCC patients with higher ALDOA expression showed greater enrichment of immunosuppressive cells including M2 macrophages and T regulatory cells. Discussion: The glycolytic subtype of HCC cells with high ALDOA expression is associated with an immunosuppressive TME and predicts worse clinical outcomes, providing new insights into the metabolism and prognosis of HCC.
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