BackgroundA growing body of research has revealed the connection of metabolism reprogramming and tumor progression, yet how metabolism reprogramming affects inter-patient heterogeneity and prognosis in head and neck squamous cell carcinoma (HNSCC) still requires further explorations.MethodsA cellular hierarchy framework based on metabolic properties discrepancy, METArisk, was introduced to re-analyze the cellular composition from bulk transcriptomes of 486 patients through deconvolution utilizing single-cell reference profiles from 25 primary and 8 metastatic HNSCC sample integration of previous studies. Machine learning methods were used to identify the correlations between metabolism-related biomarkers and prognosis. The functions of the genes screened out in tumor progression, metastasis and chemotherapy resistance were validated in vitro by cellular functional experiments and in vivo by xenograft tumor mouse model.ResultsIncorporating the cellular hierarchy composition and clinical properties, the METArisk phenotype divided multi-patient cohort into two classes, wherein poor prognosis of METArisk-high subgroup was associated with a particular cluster of malignant cells with significant activity of metabolism reprogramming enriched in metastatic single-cell samples. Subsequent analysis targeted for phenotype differences between the METArisk subgroups identifiedPYGLas a key metabolism-related biomarker that enhances malignancy and chemotherapy resistance by GSH/ROS/p53 pathway, leading to poor prognosis of HNSCC.ConclusionPYGLwas identified as a metabolism-related oncogenic biomarker that promotes HNSCC progression, metastasis and chemotherapy resistance though GSH/ROS/p53 pathway. Our study revealed the cellular hierarchy composition of HNSCC from the cell metabolism reprogramming perspective and may provide new inspirations and therapeutic targets for HNSCC in the future.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13046-023-02734-w.