Pan-cancer mutational signature analysis of 111,711 targeted sequenced tumors using SATS.

Abstract

Tumor mutational signatures are informative for cancer diagnosis and treatment. However, targeted sequencing, commonly used in clinical settings, lacks specialized analytical tools and a dedicated catalogue of mutational signatures. Here, we introduce SATS, a scalable mutational signature analyzer for targeted sequencing data. SATS leverages tumor mutational burdens to identify and quantify signatures in individual tumors, overcoming the challenges of sparse mutations and variable gene panels. Validations across simulated data, pseudo-targeted sequencing data, and matched whole-genome and targeted sequencing samples show that SATS can accurately detect common mutational signatures and estimate their burdens. Applying SATS to 111,711 tumors from the AACR Project GENIE, we created a pan-cancer mutational signature catalogue specific to targeted sequencing. We further validated signatures in lung, breast and colorectal cancers using an additional 16,774 independent samples. This signature catalogue is a valuable resource for estimating signature burdens in individual targeted sequenced tumors, facilitating the integration of mutational signatures with clinical data.