Joint inference of mutational signatures from indels and single-nucleotide substitutions reveals prognostic impact of homologous recombination deficiency in tumors

Abstract Mutational signatures are increasingly used to understand the mechanisms causing cancer, predict prognosis and stratify patients for therapy. However, inference of mutational signatures can be error-prone, particularly in the case of featureless, low-sparsity signatures, which often get confounded. One of them is the homologous recombination deficiency-associated signature SBS3, relevant because of its association with prognosis in ovarian and breast cancer and because of its potential use as a biomarker for synthetic lethality therapies. Here, we present the multimodal method for mutational signature extraction, operating on single-base substitutions (SBS) and indels jointly, and highlight its accuracy signature identification and patient survival prediction. Across four different cohorts of whole-genome sequenced ovarian cancers, the multimodal SBS/indel approach correctly distinguished the commonly confused signatures SBS3, SBS8, SBS39, SBS40 and SBS5. Moreover, we identified two different multimodal m-SBS3 signatures, m-SBS3a and m-SBS3b, with distinct patterns in the indel spectrum. Specifically, the m-SBS3b signature was strongly predictive of better survival in high-grade serous ovarian cancer patients, replicating across the four cohorts, with effect sizes greatly exceeding other genetic markers of survival. m-SBS3 further predicted survival in platinum-treated patients with various cancer types, supporting a general utility of the multimodal mutational signatures for generating biologically and clinically meaningful readouts.