Head and neck squamous cell carcinoma (HNSCC) is among the most common types of cancers that threat the public health worldwide. A growing body of evidence has demonstrated that m⁶A RNA methylation plays a critical role in tumorigenesis. However, the association between m⁶A RNA methylation regulators and prognosis of HNSCC remains poorly known. This study aimed to construct a m⁶A RNA methylation regulators-based biomarker signature that efficiently predicted the prognosis of HNSCC. The gene expression profile of m⁶A RNA methylation regulators and the corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) HNSCC dataset. The differentially expressed m⁶A RNA methylation regulators between tumor samples and normal control samples, as well as the interaction and correlation of m⁶A RNA methylation regulators were evaluated. Consensus clustering analysis was performed to identify the clusters of HNSCC with different clinical outcome. Then a prognostic signature was built on TCGA HNSCC cohort and further validated in an external independent cohort. The expression levels of METTL3, YTHDF1, KIAA1429, ALKBH5, YTHDF2, METTL14, FTO, WTAP, RBM15 and HNRNPC were significantly upregulated in tumor samples, while YTHDC2 was remarkably downregulated in the cancer specimens. WTAP and METTL14 might be the hub genes of the interaction network among m⁶A RNA methylation regulators. Two clusters of HNSCC cases were identified and significant differences were found with respect to overall survival (OS) and tumor grade between the two subgroups of patients. A two-gene prognostic signature including YTHDC2 and HNRNPC was constructed and could predict OS in HNSCC patients from TCGA dataset. In addition, the prognostic signature-based risk score was identified as an independent prognostic indicator for HNSCC. More importantly, these findings were successfully validated in an external independent HNSCC cohort. In conclusion, our study has built up a robust m⁶A RNA methylation regulators-based molecular signature that predicts the prognosis of patients with HNSCC with high accuracy, which might provide important guidance for therapeutic strategies.

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