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A Metabolism-Related Gene Prognostic Index Bridging Metabolic Signatures and Antitumor Immune Cycling in Head and Neck Squamous Cell Carcinoma

BACKGROUND: In the era of immunotherapy, predictive or prognostic biomarkers for head and neck squamous cell carcinoma (HNSCC) are urgently needed. Metabolic reprogramming in the tumor microenvironment (TME) is a non-negligible reason for the low therapeutic response to immune checkpoint inhibitor (...

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Autores principales: Du, Kunpeng, Zou, Jingwen, Wang, Baiyao, Liu, Chunshan, Khan, Muhammad, Xie, Tao, Huang, Xiaoting, Shen, Piao, Tian, Yunhong, Yuan, Yawei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9282908/
https://www.ncbi.nlm.nih.gov/pubmed/35844514
http://dx.doi.org/10.3389/fimmu.2022.857934
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author Du, Kunpeng
Zou, Jingwen
Wang, Baiyao
Liu, Chunshan
Khan, Muhammad
Xie, Tao
Huang, Xiaoting
Shen, Piao
Tian, Yunhong
Yuan, Yawei
author_facet Du, Kunpeng
Zou, Jingwen
Wang, Baiyao
Liu, Chunshan
Khan, Muhammad
Xie, Tao
Huang, Xiaoting
Shen, Piao
Tian, Yunhong
Yuan, Yawei
author_sort Du, Kunpeng
collection PubMed
description BACKGROUND: In the era of immunotherapy, predictive or prognostic biomarkers for head and neck squamous cell carcinoma (HNSCC) are urgently needed. Metabolic reprogramming in the tumor microenvironment (TME) is a non-negligible reason for the low therapeutic response to immune checkpoint inhibitor (ICI) therapy. We aimed to construct a metabolism-related gene prognostic index (MRGPI) for HNSCC bridging metabolic characteristics and antitumor immune cycling and identified the immunophenotype, genetic alternations, potential targeted inhibitors, and the benefit of immunotherapy in MRGPI-defined subgroups of HNSCC. METHODS: Based on The Cancer Genome Atlas (TCGA) HNSCC dataset (n = 502), metabolism-related hub genes were identified by the weighted gene co-expression network analysis (WGCNA). Seven genes were identified to construct the MRGPI by using the Cox regression method and validated with an HNSCC dataset (n = 270) from the Gene Expression Omnibus (GEO) database. Afterward, the prognostic value, metabolic activities, genetic alternations, gene set enrichment analysis (GSEA), immunophenotype, Connectivity map (cMAP), and benefit of immunotherapy in MRGPI-defined subgroups were analyzed. RESULTS: The MRGPI was constructed based on HPRT1, AGPAT4, AMY2B, ACADL, CKM, PLA2G2D, and ADA. Patients in the low-MRGPI group had better overall survival than those in the high-MRGPI group, consistent with the results in the GEO cohort (cutoff value = 1.01). Patients with a low MRGPI score display lower metabolic activities and an active antitumor immunity status and more benefit from immunotherapy. In contrast, a higher MRGPI score was correlated with higher metabolic activities, more TP53 mutation rate, lower antitumor immunity ability, an immunosuppressive TME, and less benefit from immunotherapy. CONCLUSION: The MRGPI is a promising indicator to distinguish the prognosis, the metabolic, molecular, and immune phenotype, and the benefit from immunotherapy in HNSCC.
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spelling pubmed-92829082022-07-15 A Metabolism-Related Gene Prognostic Index Bridging Metabolic Signatures and Antitumor Immune Cycling in Head and Neck Squamous Cell Carcinoma Du, Kunpeng Zou, Jingwen Wang, Baiyao Liu, Chunshan Khan, Muhammad Xie, Tao Huang, Xiaoting Shen, Piao Tian, Yunhong Yuan, Yawei Front Immunol Immunology BACKGROUND: In the era of immunotherapy, predictive or prognostic biomarkers for head and neck squamous cell carcinoma (HNSCC) are urgently needed. Metabolic reprogramming in the tumor microenvironment (TME) is a non-negligible reason for the low therapeutic response to immune checkpoint inhibitor (ICI) therapy. We aimed to construct a metabolism-related gene prognostic index (MRGPI) for HNSCC bridging metabolic characteristics and antitumor immune cycling and identified the immunophenotype, genetic alternations, potential targeted inhibitors, and the benefit of immunotherapy in MRGPI-defined subgroups of HNSCC. METHODS: Based on The Cancer Genome Atlas (TCGA) HNSCC dataset (n = 502), metabolism-related hub genes were identified by the weighted gene co-expression network analysis (WGCNA). Seven genes were identified to construct the MRGPI by using the Cox regression method and validated with an HNSCC dataset (n = 270) from the Gene Expression Omnibus (GEO) database. Afterward, the prognostic value, metabolic activities, genetic alternations, gene set enrichment analysis (GSEA), immunophenotype, Connectivity map (cMAP), and benefit of immunotherapy in MRGPI-defined subgroups were analyzed. RESULTS: The MRGPI was constructed based on HPRT1, AGPAT4, AMY2B, ACADL, CKM, PLA2G2D, and ADA. Patients in the low-MRGPI group had better overall survival than those in the high-MRGPI group, consistent with the results in the GEO cohort (cutoff value = 1.01). Patients with a low MRGPI score display lower metabolic activities and an active antitumor immunity status and more benefit from immunotherapy. In contrast, a higher MRGPI score was correlated with higher metabolic activities, more TP53 mutation rate, lower antitumor immunity ability, an immunosuppressive TME, and less benefit from immunotherapy. CONCLUSION: The MRGPI is a promising indicator to distinguish the prognosis, the metabolic, molecular, and immune phenotype, and the benefit from immunotherapy in HNSCC. Frontiers Media S.A. 2022-06-30 /pmc/articles/PMC9282908/ /pubmed/35844514 http://dx.doi.org/10.3389/fimmu.2022.857934 Text en Copyright © 2022 Du, Zou, Wang, Liu, Khan, Xie, Huang, Shen, Tian and Yuan 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
Du, Kunpeng
Zou, Jingwen
Wang, Baiyao
Liu, Chunshan
Khan, Muhammad
Xie, Tao
Huang, Xiaoting
Shen, Piao
Tian, Yunhong
Yuan, Yawei
A Metabolism-Related Gene Prognostic Index Bridging Metabolic Signatures and Antitumor Immune Cycling in Head and Neck Squamous Cell Carcinoma
title A Metabolism-Related Gene Prognostic Index Bridging Metabolic Signatures and Antitumor Immune Cycling in Head and Neck Squamous Cell Carcinoma
title_full A Metabolism-Related Gene Prognostic Index Bridging Metabolic Signatures and Antitumor Immune Cycling in Head and Neck Squamous Cell Carcinoma
title_fullStr A Metabolism-Related Gene Prognostic Index Bridging Metabolic Signatures and Antitumor Immune Cycling in Head and Neck Squamous Cell Carcinoma
title_full_unstemmed A Metabolism-Related Gene Prognostic Index Bridging Metabolic Signatures and Antitumor Immune Cycling in Head and Neck Squamous Cell Carcinoma
title_short A Metabolism-Related Gene Prognostic Index Bridging Metabolic Signatures and Antitumor Immune Cycling in Head and Neck Squamous Cell Carcinoma
title_sort metabolism-related gene prognostic index bridging metabolic signatures and antitumor immune cycling in head and neck squamous cell carcinoma
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9282908/
https://www.ncbi.nlm.nih.gov/pubmed/35844514
http://dx.doi.org/10.3389/fimmu.2022.857934
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