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Hepatocellular carcinoma subtypes based on metabolic pathways reveals potential therapeutic targets.
He, Zehua; Chen, Qingfeng; He, Wanrong; Cao, Junyue; Yao, Shunhan; Huang, Qingqiang; Zheng, Yu.
Afiliação
  • He Z; College of Life Science and Technology, Guangxi University, Nanning, Guangxi, China.
  • Chen Q; School of Computer, Electronic and Information, Guangxi University, Nanning, Guangxi, China.
  • He W; Department of Gastroenterology, People's Hospital of Guangxi, Zhuang Autonomous Region, Nanning, Guangxi, China.
  • Cao J; College of Life Science and Technology, Guangxi University, Nanning, Guangxi, China.
  • Yao S; Medical College, Guangxi University, Nanning, Guangxi, China.
  • Huang Q; Guigang City Department of Radiology, People's Hospital, Guigang, Guangxi, China.
  • Zheng Y; Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, Australia.
Front Oncol ; 13: 1086604, 2023.
Article em En | MEDLINE | ID: mdl-36937389
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Oncol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Oncol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China País de publicação: Suíça