Construction of a novel disulfidptosis-related lncRNAs signature for prognosis prediction and anti-tumor immunity in laryngeal squamous cell carcinoma.

ABSTRACT

Disulfidptosis, an innovative type of controlled cellular death linked to metabolic dysfunction, has garnered attention. However, there is limited knowledge regarding the involvement of disulfidptosisrelated lnRNAs (DRlncRNAs) in laryngeal squamous cell carcinoma (LSCC). The objective of our team in this study seeks to establish a DRlncRNAs signature, investigate their prognostic value in LSCC, and explore their associations with immune cell subpopulations, biological signaling pathways, and exploring implications for drug sensitivity. We accessed LSCC patients' RNA-seq data and pertinent clinical data for subsequent further analysis from The Cancer Genome Atlas (TCGA) portal. A literature search was conducted focusing on disulfidptosis-related genes. Pearson correlation coefficients were calculated to identify DRlncRNAs. Differential expression analysis of lncRNAs was performed. Utilizing univariate Cox regression analysis, we identified disulfidptosis-associated prognostic lncRNAs. The LASSO-Cox regression analysis was employed to refine this set of lncRNAs and construct a disulfidptosis-related lncRNAs signature. Various statistical techniques were employed to appraise model predictive performance. Subsequently, risk groups were stratified based on the risk score derived from the DRlncRNAs signature. The superiority of the risk score in prognostication over traditional clinicopathological features in LSCC patients was demonstrated. Evident distinctions emerged between risk groups, particularly in immune cell subpopulations like activated mast cells, eosinophils, and activated NK cells. Finally, the low-risk group demonstrated reduced IC50 values for specific chemotherapeutics like cisplatin and gemcitabine. The in vitro experiments indicated differential behavior of our DRlncRNAs. The DRlncRNAs signature can serve as a robust biomarker with the ability to predict both prognosis and therapeutic responses among patients with LSCC.