Novel cuproptosis-related lncRNAs risk model to predicting prognosis and guiding immunotherapy for OSCC patients - Lingbo Kong; Chenfei Wang; Xiaohui Lu; Qianqi Zhu; Yihua Song; Xingmei Feng (Discover Oncology)
Abstract Background A significant role in many cancers is played by cuproptosis, a new term for the copper-dependent regulatory cell death pattern. However, as a new research hotspot, the cuproptosis-related lncRNAs (CRLs) associated with regulation in oral squamous cell carcinoma (OSCC) patients are currently not well understood. Methods Long noncoding RNA (lncRNA) data were downloaded from the Cancer Genome Atlas database (TCGA). The ‘LIMMA’ package in R software was used to screen for differential expression of CRLs. LASSO regression and COX regression models were used to construct prognostic signature based on 4 prognostic CRLs. Finally, the relationship of risk characteristics with immune correlation analysis, somatic mutations, PCA, biological molecular pathways and drug sensitivity was investigated. Results A cuproptosis-related lncRNAs prognostic signature was developed by us. Based on the risk scores, the OSCC samples were split into high- and low-risk groups using this signature. The two risk groups differed significantly in immune functions, drug sensitivity, and overall survival. The risk model showed better prognostic predictive power compared to the traditional clinicopathological signature. By qPCR trial, we also verified the expression of STARD4-AS1 in OSCC cell lines and tissues was in line with our results from this experimental screen. Through cell experiments, we have confirmed that knocking down STARD4-AS1 promotes the proliferation and migration ability of OSCC cells. Conclusion The CRLs signature contributes to new understandings of the treatment of OSCC and is a rubost biomarker for predicting the prognosis of patients with OSCC.