Identification of the mitochondrial-Related Prognostic Biomarkers in patients with Head and Neck Squamous Cell Carcinoma

Abstract

Abstract Mitochondria play an essential role in the malignant development of tumors. The purpose of this study was to reveal the vast landscape in mitochondria of head and neck squamous carcinoma (HNSCC), establish a new prognosis model of mitochondrial-related genes (Mito-RGs), and explore its clinical potential and predictive value for treatment response. In this study, using HNSCC data in the Cancer Genome Atlas (TCGA) database, we constructed a classifier containing 13 Mito-RGs risk models for predicting the prognosis of HNSCC by the univariate Cox regression analysis and a minor absolute shrinkage and selection operator (Lasso) regression analysis, and then verified in both internal and external validation cohort. According to the risk score calculated by the classifier, the samples were divided into high-risk and low-risk groups. Survival analysis showed that the survival outcome of high-risk group patients was significantly worse (p < 0.001). We used the Nomogram model to further predict the prognosis of patients. The results showed that the Mito-RGs-related prognostic model had good prediction performance. Identification of metabolic pathways with significant differences between high-risk and low-risk groups by gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). We also evaluated the infiltration of immune cells and used the tumor immune dysfunction and exclusion (TIDE) algorithm to estimate the potential response of immunotherapy in different risk groups. Our study constructed and validated a promising 13 Mito-RGs classifier for monitoring outcomes, which may provide potential indicators for metabolic therapy and therapeutic response prediction in HNSCC.