Investigating the prognostic role of lncRNAs associated with disulfidptosis‐related genes in clear cell renal cell carcinoma

Abstract Introduction Renal cell carcinoma (RCC) is a grave malignancy that poses a significant global health burden with over 400,000 new cases annually. Disulfidptosis, a newly discovered programmed cell death process, is linked to the actin cytoskeleton, which plays a vital role in maintaining cell shape and survival. The role of disulfidptosis is poorly depicted in the clear cell histologic variant of RCC (ccRCC). Methods Three sets of ccRCC cohorts, ICGC_RECA‐EU ( n = 91), GSE76207 ( n = 32) and TCGA‐KIRC ( n = 607), were included in our study, the batch effect of which was removed using the “combat” function. Correlation was calculated using the “rcorr” function of the “Hmisc” package for Pearson analysis, which was visualized using the “pheatmap” package. Principal component analysis was performed by the “vegan” package, visualized using the “scatterplot3d” package. Long non‐coding RNAs (lncRNAs) associated with disulfidptosis were screened out using least absolute shrinkage and selection operator (LASSO) and COX analysis. Tumor mutation, immune landscaping and immunotherapy prediction were performed for further characterization of two risk groups. Results A total of 1822 disulfidptosis‐related lncRNAs was selected, among which 308 lncRNAs were found to be significantly associated with the clinical outcome of ccRCC patients. We retained 11 disulfidptosis‐related lncRNAs, namely, AP000439.3, RP11‐417E7.1, RP11‐119D9.1, LINC01510, SNHG3, AC156455.1, RP11‐291B21.2, EMX2OS, AC093850.2, HAGLR and RP11‐389C8.2, through LASSO and COX analysis for prognosis model construction, which displayed satisfactory accuracy (area under the curve, AUC, values all above 0.6 in multiple cohorts) in stratification of ccRCC prognosis. A nomogram model was constructed by integrating clinical factors with risk score, which further enhanced the prediction efficacy (AUC values all above 0.7 in multiple cohorts). We found that patients of male gender, higher clinical stages and advanced pathological T stage were inclined to have higher risk score values. Dactinomycin_1911, Vinblastine_1004, Daporinad_1248 and Vinorelbine_2048 were identified as promising candidate drugs for treating ccRCC patients of higher risk score value. Moreover, patients of higher risk value were prone to be resistant to immunotherapy. Conclusion We developed a prognosis predicting model based on 11 selected disulfidptosis‐related lncRNAs, the efficacy of which was verified in different cohorts. Furthermore, we delineated an intricate portrait of tumor mutation, immune topography and pharmacosensitivity evaluations within disparate risk stratifications.