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Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma

BACKGROUND: This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response. METHODS: Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Geno...

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Autores principales: Chen, Dan, Aierken, Ayinuer, Li, Hui, Chen, Ruihua, Ren, Lei, Wang, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10597634/
https://www.ncbi.nlm.nih.gov/pubmed/37881434
http://dx.doi.org/10.3389/fimmu.2023.1232390
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author Chen, Dan
Aierken, Ayinuer
Li, Hui
Chen, Ruihua
Ren, Lei
Wang, Kai
author_facet Chen, Dan
Aierken, Ayinuer
Li, Hui
Chen, Ruihua
Ren, Lei
Wang, Kai
author_sort Chen, Dan
collection PubMed
description BACKGROUND: This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response. METHODS: Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients. RESULTS: Thirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients. CONCLUSION: Results showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients.
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spelling pubmed-105976342023-10-25 Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma Chen, Dan Aierken, Ayinuer Li, Hui Chen, Ruihua Ren, Lei Wang, Kai Front Immunol Immunology BACKGROUND: This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response. METHODS: Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients. RESULTS: Thirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients. CONCLUSION: Results showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients. Frontiers Media S.A. 2023-10-10 /pmc/articles/PMC10597634/ /pubmed/37881434 http://dx.doi.org/10.3389/fimmu.2023.1232390 Text en Copyright © 2023 Chen, Aierken, Li, Chen, Ren and Wang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Chen, Dan
Aierken, Ayinuer
Li, Hui
Chen, Ruihua
Ren, Lei
Wang, Kai
Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma
title Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma
title_full Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma
title_fullStr Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma
title_full_unstemmed Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma
title_short Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma
title_sort identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10597634/
https://www.ncbi.nlm.nih.gov/pubmed/37881434
http://dx.doi.org/10.3389/fimmu.2023.1232390
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