Joint inference of mutational signatures from indels and single-nucleotide substitutions reveals prognostic impact of DNA repair deficiencies.

Abstract

Background: Mutational signatures are increasingly used to understand the mechanisms causing cancer. However, their important applications in predicting prognosis and stratifying patients for therapy are hampered by inaccurate inference of the various featureless, dense trinucleotide mutational spectra, which are often confounded with one another. One of them is the homologous recombination deficiency (HRd)-associated signature SBS3, relevant because of its association with prognosis in ovarian and breast cancer and because of its potential as a biomarker for synthetic lethality therapies.

Methods: Here, we highlight strong benefits of a multimodal approach for mutational signature extraction, applied on top of standard bioinformatic pipelines. By jointly operating on single-base substitution (SBS) and indel (ID) spectra, this method enables accurate identification of various DNA repair deficiency signatures and patient survival prediction.

Results: Across four different cohorts of whole-genome sequenced high-grade serous ovarian cancers (HGSOC), the multimodal SBS + ID approach correctly distinguished the commonly confused signatures SBS3, SBS5, SBS8, SBS39, and SBS40. Importantly, we robustly identified two different multimodal SBS3 signatures, m-SBS3a and m-SBS3b, with distinct patterns in the indel spectrum. Multimodal SBS3b signature was strongly predictive of longer survival in ovarian cancer patients, replicating across four cohorts, with effect sizes greatly exceeding other genetic markers. Our m-SBS3 also predicted survival in platinum-treated patients with various cancer types, and moreover, the SBS + ID joint inference was successfully applied to mismatch repair-deficient colorectal cancer and immunotherapy response, supporting a general utility of the multimodal mutational signatures approach.

Conclusions: Overall, combining SBS and ID mutations improves detection of HR deficiency-associated signatures and reveals distinct SBS3 subtypes with prognostic value. This multimodal approach outperforms existing markers and is readily applicable to therapy stratification.