Cuproptosis, a recently characterized programmed cell death mechanism, has emerged as a potential contributor to tumorigenesis, metastasis, and immune modulation. Long non-coding RNAs (lncRNAs) have demonstrated diverse regulatory roles in cancer and hold promise as biomarkers. However, the involvement and prognostic significance of cuproptosis-related lncRNAs (CRLs) in oral squamous cell carcinoma (OSCC) remain poorly understood. Based on TCGA-OSCC data, we integrated single-sample gene set enrichment analysis (ssGSEA), the LASSO algorithm, and the tumor immune dysfunction and exclusion (TIDE) algorithm. We identified 11 CRLs through differential expression, Spearman correlation, and univariate Cox regression analyses. Two distinct CRL-related subtypes were unveiled, delineating divergent survival patterns, tumor microenvironments (TME), and mutation profiles. A robust CRL-based signature (including AC107027.3, AC008011.2, MYOSLID, AC005785.1, AC019080.5, AC020558.2, AC025265.1, FAM27E3, and LINC02367) prognosticated OSCC outcomes, immunotherapy responses, and anti-tumor strategies. Superior predictive power compared to other lncRNA models was demonstrated. Functional assessments confirmed the influence of FAM27E3, LINC02367, and MYOSLID knockdown on OSCC cell behaviors. Remarkably, the CRLs-based signature maintained stability across OSCC patient subgroups, underscoring its clinical potential for survival prediction. This study elucidates CRLs' roles in TME of OSCC and establishes a potential signature for precision therapy.
Keywords: Cuproptosis; Immunotherapy; Oral squamous cell carcinoma; Prognosis; Tumor microenvironment; lncRNA.
Copyright © 2024. Published by Elsevier Ltd.