4.8 Article

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

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FRONTIERS IN IMMUNOLOGY
卷 13, 期 -, 页码 -

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FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2022.857934

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metabolism; antitumor immune cycling; immunotherapy; prognosis; individualized precision therapy

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In this study, a metabolism-related gene prognostic index (MRGPI) for head and neck squamous cell carcinoma (HNSCC) was constructed, which bridged metabolic characteristics and antitumor immune cycling, and the immunophenotype, genetic alterations, potential targeted inhibitors, and the benefit of immunotherapy were identified in MRGPI-defined HNSCC subgroups. Patients with a low MRGPI score displayed lower metabolic activities and an active antitumor immunity status and had more benefit from immunotherapy, while a higher MRGPI score was associated with higher metabolic activities, lower antitumor immunity ability, an immunosuppressive tumor microenvironment, and less benefit from immunotherapy.
BackgroundIn 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. MethodsBased 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. ResultsThe 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. ConclusionThe 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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