DR-483 Characterization of the evolutionary dynamics of mutational signatures for clinically actionable cancer genomics

We aim to decode how cancers mutate their DNA over time and use that knowledge to improve patient care. Using data from germline and somatic mutations, as well as RNA editing events, derived from WGS and RNA-seq from multiple cancer types, we will identify mutational signatures revealing the processes responsible and at which point they have been active in tumor evolution towards metastasis. We will build AI tools to detect these mutational fingerprints and link them to key driver genes, therapies, and outcomes. The results could enable more accurate risk assessment, prognosis, and therapy selection tailored to each patient.

Marcos Díaz-Gay, Spanish National Cancer Research Center (CNIO), Spain