Abstract
BACKGROUND/PURPOSE: Oral squamous cell carcinoma (OSCC) is a highly malignant tumor, and the overall survival (OS) time of patients with OSCC varies considerably. This study aimed to identify reliable biomarkers for OSCC and construct a new prognostic signature, which may guide personalized precision treatment. MATERIALS AND METHODS: Transcriptome array data of 317 patients with OSCC from The Cancer Genome Atlas Project (TCGA) cohort were retrospectively analyzed. Single-sample gene set enrichment analysis (ssGSEA) and univariate Cox regression were performed to identify the prognostic significance of the hallmarks of each tumor in OSCC. Subsequently, lncRNAs related to glycolysis were identified through co-expression analysis. A glycolysis-related prognostic signature was constructed by combining univariate Cox regression, least absolute shrinkage and selection operator (Lasso) regression, and multivariate Cox regression analyses. Additionally, the infiltration of immune cells in OSCC was evaluated based on data from ssGSEA and TIMER databases. RESULTS: Glycolysis was identified as the main risk factor for OS in a variety of cancer hallmarks. The 4-lncRNA glycolysis prognostic signature could distinguish high and low-risk patients. This risk signature was found to be an independent prognostic risk factor for OSCC, showing good predictive power compared with other clinicopathological indicators. Immune correlation analysis showed that patients in the low-risk group exhibited higher levels of immune cell infiltration. CONCLUSION: The novel 4-lncRNA prognostic signature can predict the clinical outcome of patients with OSCC well, and it is expected to become a promising prognostic biomarker as well as a potential therapeutic target in the future.