Construction of a five-disulfidptosis-related-lncRNA signature for predicting prognosis and immune activity in kidney renal clear cell carcinoma

Abstract

Abstract Background: Kidney renal clear cell carcinoma (KIRC) is a highly aggressive cancer. Disulfidptosis is a novel mechanism of programmed cell death. However, the role of disulfidptosis-related lncRNAs (DRlncRNAs) in KIRC remains unknown. This study aimed to develop a prognostic model based on DRlncRNAs and examine their prognostic value in KIRC. Methods: RNA sequencing and relevant clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses and the lasso algorithm were used to identify prognostic DRlncRNAs and establish a prognostic model. Multiple methods were used to assess the reliability of the model. Gene set enrichment analysis (GSEA), immune infiltration analysis and somatic mutation analysis were performed to evaluate the predictive performance of the model, and anticancer drugs were predicted. Results: The prognostic model was established based on five DRlncRNAs and was identified as a good predictor of the survival and prognosis of patients with KIRC. GSEA revealed that DRlncRNAs were associated with apoptosis and immune-related pathways. Immune analysis suggested that low-risk patients had better immunotherapeutic outcomes. Somatic mutation analysis revealed that low-risk patients had a lower somatic mutation rate and TMB score and a better prognosis. In addition, axitinib, ibrutinib, osimertinib and ruxolitinib were found to be more effective in low-risk patients, whereas crizotinib, lapatinib, linsitinib and nilotinib were found to be more effective in high-risk patients. Finally, qRT-PCR was performed to determine the expression of DRlncRNAs in normal kidney cells and KIRC cell lines. Conclusion: We constructed a risk model and proposed a novel strategy for diagnosing and treating KIRC.