Predictive modeling and functional characterization of the ceRNA regulatory network in cisplatin resistance of...

Non-small cell lung cancer remains the leading cause of cancer-related mortality worldwide. Cisplatin-based chemotherapy is a primary treatment strategy for non-small cell lung cancer, but acquired drug resistance limits its therapeutic efficacy. Emerging evidence suggests that microRNA-mediated competing endogenous RNA networks play a critical role in regulating anticancer drug resistance. In this study, we initially established a cisplatin sensitivity prediction model that enables the evaluation of cisplatin responsiveness based on patients' transcriptomic profiling. Integrative analysis of cisplatin sensitiveness and the transcriptomic data identified GDF15 and ZDHHC9 as essential drivers of cisplatin resistance. We further constructed the competing endogenous RNA regulatory network centered on these resistance-associated genes. Functional validation determined that hsa-miR-873-5p directly represses GDF15 expression, and its overexpression increased cellular sensitivity to cisplatin, as evidenced by a 35% reduction in half-maximal inhibitory concentration in PC9 cells and a 24% reduction in H226 cells. Our study provides a prediction model for cisplatin responsiveness evaluation and suggests the hsa-miR-873-5p/GDF15 axis as a promising therapeutic target for overcoming cisplatin resistance in non-small cell lung cancer. SIGNIFICANCE STATEMENT: This study develops a predictive model for cisplatin sensitivity in lung cancer and identifies key resistance genes via transcriptomic analysis. The study further reveals the critical hsa-miR-873-5p/GDF15 regulatory axis as a potential biomarker for personalized therapy in patients with non-small cell lung cancer.