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A Signature of N6-methyladenosine Regulator-Related Genes Predicts Prognoses and Immune Responses for Head and Neck Squamous Cell Carcinoma
A Signature of N6-methyladenosine Regulator-Related Genes Predicts Prognoses and Immune Responses for Head and Neck Squamous Cell Carcinoma
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A Signature of N6-methyladenosine Regulator-Related Genes Predicts Prognoses and Immune Responses for Head and Neck Squamous Cell Carcinoma
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A Signature of N6-methyladenosine Regulator-Related Genes Predicts Prognoses and Immune Responses for Head and Neck Squamous Cell Carcinoma
A Signature of N6-methyladenosine Regulator-Related Genes Predicts Prognoses and Immune Responses for Head and Neck Squamous Cell Carcinoma

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A Signature of N6-methyladenosine Regulator-Related Genes Predicts Prognoses and Immune Responses for Head and Neck Squamous Cell Carcinoma
A Signature of N6-methyladenosine Regulator-Related Genes Predicts Prognoses and Immune Responses for Head and Neck Squamous Cell Carcinoma
Journal Article

A Signature of N6-methyladenosine Regulator-Related Genes Predicts Prognoses and Immune Responses for Head and Neck Squamous Cell Carcinoma

2022
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Overview
This study aimed to construct a signature of N 6 -methyladenosine (m6A) regulator-related genes that could be used for the prognosis of head and neck squamous cell carcinoma (HNSCC) and to clarify the molecular and immune characteristics and benefits of immune checkpoint inhibitor (ICI) therapy using the prognostic signature to define the subgroups of HNSCC. This study showed that eighteen m6A regulators were abnormally expressed in the Cancer Genome Atlas (TCGA) HNSCC tissues compared with those in normal tissues. We constructed a signature of 12 m6A regulator-related genes using the Cox risk model, combined with the least absolute shrinkage and selection operator (Lasso) variable screening algorithm. Based on the median of the signature risk score, the patients were divided into high- and low-risk groups. The Kaplan–Meier survival analyses showed that patients with high-risk scores demonstrated poorer overall survival (OS) than those with low-risk scores based on TCGA-HNSCC data ( p < 0.001). The OS of high-risk patients was significantly worse than that of low-risk patients in the GSE65858 ( p < 0.001) and International Cancer Genome Consortium (ICGC) oral cancer cohorts ( p = 0.0089). Furthermore, immune infiltration analyses showed that 8 types of immune cell infiltration showed highly significant differences between the two risk groups ( p < 0.001). In the Imvigor210CoreBiologies dataset of patients who received ICIs, the objective response rate (ORR) of the low-risk group (32%) was significantly higher than that of the high-risk group (13%). Additionally, patients in the high-risk group presented with a more significant adverse OS than that of the low-risk group ( p = 0.00032). GSE78220 also showed that the ORR of the low-risk group (64%) was higher than that of the high-risk group (43%) and the OS of low-risk patients was better than that of high-risk patients ( p = 0.0064). The constructed prognostic signature, based on m6A regulator-related genes, could be used to effectively distinguish between prognoses for HNSCC patients. The prognostic signature was found to be related to the immune cell infiltration of HNSCC; it might help predict the responses and prognoses of ICIs during treatment.