Background: Oral squamous cell carcinoma (OSCC) is the most common tumor in the oral cavity and maxillofacial region. Increasing evidence suggests that aerobic glycolysis plays an important role in the occurrence, development, and prognosis of OSCC. Therefore, the identification of biomarkers related to glycolysis in OSCC represents considerable potential for improving its treatment.
Methods: In the present study, a single-sample gene-set enrichment analysis (ssGSEA) algorithm with weighted gene co-expression network analysis (WGCNA) were used to quantify the degree of glycolysis and identify key modules with the greatest correlation with glycolysis.
Results: Glycolytic scores significantly correlated with prognosis. In the key module 5 HUB genes were finally selected, which displayed a robust predictive effect. The expressions of key genes were associated with glycolysis.
Conclusions: The research comprehensively analyzed the glycolysis of OSCC and identified several biomarkers related to glycolysis. These biomarkers may represent potential therapeutic targets for future OSCC therapy.
Keywords: GEO; OSCC; TCGA; WGCNA; glycolysis.
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