Establishment of a prognostic signature of disulfidptosis-related lncRNAs for predicting survival and immune landscape in clear cell renal cell carcinoma

Abstract

Abstract Objectives A novel cell death pathway, disulfidptosis, marked by intracellular disulfide build-up, is a recently identified form of cell death. This study developed a dependable model using disulfidptosis-associated lncRNAs to predict outcomes and immune interactions in clear cell renal cell carcinoma (ccRCC) patients. Methods Data from ccRCC patients, including genomic and clinicopathological details, were sourced from The Cancer Genome Atlas database. We employed the least absolute shrinkage and selection operator (LASSO) along with regression analyses to construct a prognostic model consisting of 12 disulfidptosis-related lncRNAs (DRLs). The model’s validity was tested using the RECA-EU and GSE29609 datasets. Results The prognostic model, incorporating 12 DRLs – LINC01671, DOCK9-DT, AL078581.2, SPINT1-AS1, ZNF503-AS1, AL391883.1, AC002070.1, AP001372.2, AC068338.3, AC026401.3, AL355835.1, and AL162377.1 – distinguished high-risk ccRCC patients with diminished survival rates in both the training and validation cohorts. Further analyses through Cox regression confirmed this risk model’s independent prognostic capability regarding overall survival (OS). Functional enrichment analysis indicated significant involvement of differentially expressed genes in immune response mediator production. A prognostic nomogram, integrating DRLs with clinical features, showed strong predictive accuracy as confirmed by receiver operating characteristic curves. Additionally, assessments of immune functionality and tumor mutation burden varied across risk categories in the tumor microenvironment, highlighting potential targets for anticancer drugs. Conclusions The findings suggest the DRLs signature is a potent prognostic indicator and may serve to forecast responses to immunotherapy in ccRCC patients.