DNA methylation-based prediction of response to immune checkpoint inhibition in metastatic melanoma. DNA methylation-based prediction of response to immune checkpoint inhibition in metastatic melanoma

A novel approach of reference-free deconvolution of large-scale DNA methylation data enabled to develop a machine learning classifier based on CpG sites, specific for Latent Methylation Components (LMC), that allowed for patient allocation to prognostic clusters. DNA methylation data was processed using reference-free analyses (MeDeCom) and reference-based computational tumor deconvolution (MethylCIBERSORT, LUMP). These results demonstrate that LMC-based segregation of large-scale DNA methylation data is a promising tool for classifier development and treatment response estimation in cancer patients under targeted immunotherapy. Overall design: 65 specimens of melanoma skin metastasis were analyzed using the Illumina Infinium MethylationEPIC BeadChip all patients belong to AJCC Stage IV