Abstract
BACKGROUND: Low-density lipoprotein receptor-related protein (LRP) is integral to protein synthesis and contributes significantly to tumor initiation and growth. However, the role of LRP-related mRNAs (LRPMRs) in KIRC progression remains unclear. Our study investigates the potential use of LRPMRs as prognostic markers in patients with KIRC. METHODS: Clinical and transcriptomic data of KIRC patients were obtained from The Cancer Genome Atlas (TCGA) database for model construction and performance evaluation. A nomogram integrating clinical characteristics and the risk model was then established. To explore the clinical significance and underlying mechanisms, we analyzed the tumor microenvironment (TME), evaluated tumor mutational burden (TMB), performed gene set enrichment analysis, and predicted drug sensitivity. The mRNA expression was assessed using RT-qPCR. RESULTS: A six-LRPMR-based model was developed and provided significant prognostic information. Kaplan-Meier analysis demonstrated worse survival outcomes for high-risk (H-R) patients (p < 0.001). A nomogram incorporating the risk model showed improved predictive accuracy compared with the clinical model alone (AUC = 0.761). GSEA highlighted proximal tubule transport and propanoate metabolism pathways as significantly enriched in the low-risk (L-R) group, while the H-R group displayed enrichment in CD22-mediated BCR regulation and FCGR activation pathways. Higher TMB in the H-R cohort predicted a poor prognosis. TME analysis suggested that H-R patients may respond less favorably to immunotherapy. Drug sensitivity analysis indicated that H-R patients were more sensitive to Staurosporine and Sabutoclax, whereas L-R patients were more sensitive to dihydrorotenone and osimertinib. RT-qPCR validated differential mRNA expression between KIRC and normal cells. CONCLUSION: This six-LRPMR-based prognostic model provides valuable insights for prognosis assessment and personalized treatment selection in KIRC.