Investigating the efficacy of immune checkpoint inhibitors in clear cell renal cell carcinoma based on methylation cross talk scoring.

Methylation processes in different molecular contexts (DNA, RNA, and histones) are controlled by different regulatory factors and serve as critical determinants in cancer development. However, the mechanistic links between these epigenetic modifications during malignant transformation, metastasis, disease relapse, and therapeutic resistance remain incompletely understood. In this research, we investigated the transcriptional and genetic alterations of regulators associated with 3 major types of methylation modifications in clear cell renal cell carcinoma. Utilizing ChIP/MeRIP-seq and 450K methylation array data, we identified genes regulated by multiple methylation modifications and constructed a scoring model to quantify the methylation patterns for each patient. Our findings indicate that patients with a low score may be more likely to respond to immunotherapy, whereas patients with a high score may be more sensitive to targeted therapy, such as RITA, Pazopanib, Irlotinib, SU-11274, BRD-K16762525, and FCCP. In conclusion, the score model can serve as a valuable biomarker to guide clinical selection of immunotherapy and targeted drugs and help to improve personalized clear cell renal cell carcinoma treatment.