DNA Methylation Modification Patterns Identify Distinct Prognosis and Responses to Immunotherapy and Targeted Therapy in Renal Cell Carcinoma.

Background: Considering the remarkable heterogeneity of biological features of renal cell carcinoma (RCC), the current clinical classification that only relies on classic clinicopathological features is in urgent need of improvement. Herein, we aimed to conduct DNA methylation modification patterns in RCC.

Methods: We retrospectively curated multiple RCC cohorts, comprising TCGA-KIRC, TCGA-KICH, TCGA-KIRP, and E-MTAB-1980. DNA methylation modification patterns were proposed with an unsupervised clustering algorithm based on 20 DNA methylation regulators. Immunological features were characterized using tumor-infiltrating immune cells and immunomodulators. Sensitivity to immuno- or targeted therapy was estimated with submap and Genomics of Drug Sensitivity in Cancer (GDSC). DNA methylation score (DMS) was developed with principal component analysis.

Results: Three DNA methylation modification patterns were conducted across RCC patients, namely C1, C2 and C3. Among them, C3 displayed the most remarkable survival advantage. The three patterns presented in agreement with immune phenotypes: immune-desert, immune-excluded, and immune-inflamed, respectively. These patterns displayed distinct responses to anti-PD-1 and targeted drugs. DMS enabled the quantification of DNA methylation status individually as an alternative tool for prognostic estimation.

Conclusions: The DNA methylation molecular patterns we proposed are an innovative complement to the traditional classification of RCC, which might contribute to precision medicine.