Comprehensive Analysis of mTORC1 Signaling Pathway–Related Genes in the Prognosis of HNSCC and the Response to Chemotherapy and Immunotherapy - Ding, Zhao; Shen, Hailong; Xu, Ke; Wu, Yu; Wang, Shuhao; Yi, Fangzheng; Wang, Daming; Liu, Yehai (Frontiers in Molecular Biosciences, 2022)
Objective: The mammalian target of rapamycin complex 1 (mTORC1) signaling pathway has emerged as a crucial player in the oncogenesis and development of head and neck squamous cell carcinoma (HNSCC); however, to date, no relevant gene signature has been identified. Therefore, we aimed to construct a novel gene signature based on the mTORC1 pathway for predicting the outcomes of patients with HNSCC and their response to treatment. Methods: Gene expression and clinical data were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Key prognostic genes associated with the mTORC1 pathway were screened by univariate Cox regression analyses. A prognostic signature was then established based on significant factors identified in the multivariate Cox regression analysis. The performance of the multi-gene signature was evaluated by Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) analysis. Based on the median risk score, patients were categorized into high- and low-risk groups. Subsequently, a hybrid prognostic nomogram was constructed and estimated by calibration plot and decision curve analysis. Furthermore, immune cell infiltration and therapeutic responses were compared between the two risk groups. Finally, we measured the expression levels of seven genes by quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). Results: The mTORC1 pathway-based signature was constructed using the seven identified genes (SEC11A, CYB5B, HPRT1, SLC2A3, SC5D, CORO1A, and PIK3R3). Patients in the high-risk group exhibited a lower overall survival (OS) rate than those in the low-risk group in both datasets. Through univariate and multivariate Cox regression analyses, this gene signature was confirmed to be an independent prognostic risk factor for HNSCC. The constructed nomogram based on age, American Joint Committee on Cancer (AJCC) stage, and the risk score exhibited satisfactory performance in predicting OS. Additionally, immune cell infiltration and chemotherapeutic and immunotherapeutic responses differed significantly between the two risk groups. The expression levels of SEC11A and CYB5B were higher in HNSCC tissues than in normal tissues. Conclusion: Our study established and verified a mTORC1 signaling pathway-related gene signature that could be used as a novel prognostic factor for HNSCC.