BASCULE: Bayesian inference and clustering of mutational signatures leveraging biological priors

Elena Buscaroli, Azad Sadr, Riccardo Bergamin, Salvatore Milite, Edith Natalia Villegas Garcia, Arianna Tasciotti, Alessio Ansuini, Daniele Ramazzotti, Nicola Calonaci, Giulio Caravagna

Abstract: h3>Abstract</h3> <p>Mutational signatures provide key insights into cancer mutational processes, but the availability of signature catalogues generated by different groups using distinct methodologies underscores a need for standardisation. We introduce a Bayesian framework that offers a systematic approach to expanding existing signature catalogues for any type of mutational signature, while grouping patients based on shared signature patterns. We demonstrate that this approach can identify both known and novel molecular subtypes across nearly 8,000 samples spanning six cancer types, and show that stratifications derived from signature yield prognostic groups, further enhancing the translational potential of mutational signatures.</p>

External IDs:doi:10.1101/2024.09.16.613266