Machine Learning-Based Integration Develops a Robust Mitophagy-Related Multigene Model to Predict Patient Prognosis and Immune Microenvironment in Head and Neck Squamous Cell Carcinoma
作者单位：Clinical Oncology School of Fujian Medical UniversityFujian Cancer Hospital
会议名称：《2022CCTB中国肿瘤标志物学术大会暨中国整合肿瘤学大会暨第十六届肿瘤标志物青年科学家论坛暨中国肿瘤标志物产业创新大会》
会议日期：2023年
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
摘 要：Purpose:Head and neck squamous cell carcinoma(HNSCC) treatment is facing clinical *** in cancer cells is related to the tumor high energetic *** tumor immune microenvironment(TME) strongly influences clinical outcomes and treatment ***,the correlation of mitophagy and TME remains unknown in ***:Based on machine learning,a prognostic multigene signature was built with mitophagy-related differentially expressed genes(MPGs),which was associated with TME by gene set enrichment analysis(GSEA),in the TCGA ***,we systematically correlated risk signature with immunological characteristics in TME,which included immune checkpoints,tumor-infiltrating immune cells(TIICs),*** further invalidate CSNK2A2,we employed immunohistochemistry to examine its ***:MPGs-related prognostic model showed good prediction *** who had high-risk scores had significantly shorter progression-free survival(PFS) and overall survival(OS) than those with low-risk scores,according to the results of the survival analysis(p0.0001).The CD8+ T cells infiltrated less in samples with higher risk *** immunological characteristic markers were expressed at higher levels in the low-risk ***,immune therapy might be effective for the low-risk subtype of HNSCC patients(p0.001).Samples with higher risk scores were more sensitive to ***2A2was validated to be higher expressed in HNSCC tissues,according to ***:We have constructed a prognostic signature and provided innovative insights that may improve HNSCC management,which might give a more precise prognostic ***2A2 might be a novel biomarker to predict immune efficacy.