Cargando…

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 (...

Descripción completa

Detalles Bibliográficos
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
Descripción
Sumario: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.