Abstract
Mutational signatures of single-base substitutions (SBSs) characterize somatic mutation processes which contribute to cancer development and progression. However, current mutational signatures do not distinguish the two independent steps that generate SBSs: the initial DNA damage followed by erroneous repair. To address this modelling gap we developed DAMUTA, a hierarchical Bayesian probabilistic model that infers separate signatures for each process, and captures their sample-specific interaction. We applied DAMUTA to 18,974 pan-cancer whole genome sequencing mutation catalogues from 23 cancer types and show that tissue-specificity in mutation patterns is driven largely by variability in damage processes. We also show that misrepair processes are predictive of DNA damage response deficiencies. Unlike existing approaches, DAMUTA distinguishes damage from misrepair contributions, and we demonstrate significant improvements over a mutational-burden baseline or signatures from the COSMIC database. Our analysis reveals a shared pan-cancer pattern of early clonal transition-mutations which shifts to a more uniform substitution pattern consistent with increased reliance on translesion synthesis for damage tolerance. DAMUTA thus generates a compact set of signatures which resolves redundancies of current signature models, disentangles the effects of DNA damage and misrepair processes, and facilitates improved stratification of tumours, while providing a framework towards a unified pan-cancer model of the cellular response to DNA damage.