SATS: A mutational signature analyzer of targeted sequenced tumors

Tumor mutational signatures are important in clinical decision-making and are typically analyzed using whole exome or genome sequencing (WES/WGS). However, targeted sequencing is more commonly used in clinical settings, posing challenges in mutational signature analysis due to sparse mutation data and non-overlapping targeted gene panels. We introduce SATS (Signature Analyzer for Targeted Sequencing), an analytical method that identifies mutational signatures in targeted sequenced tumors by analyzing tumor mutational burdens and accounting for different gene panels. We demonstrate through simulations and pseudo-targeted sequencing data (generated by down-sampling WES/WGS data) that SATS can accurately detect common mutational signatures with distinct profiles. Using SATS, we created a pan-cancer catalog of mutational signatures specifically tailored to targeted sequencing by analyzing 100,477 targeted sequenced tumors from the AACR Project GENIE. The catalog allows SATS to estimate signature activities even within a single sample, providing new opportunities for applying mutational signatures in clinical settings. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This research was conducted with support from Intramural Research Program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics (DCEG). Additionally, Dr. Lee was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT, No. RS-2023-00213625). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study used ONLY openly available human data that were originally located at https://synapse.org/genie, https://cancer.sanger.ac.uk/signatures/, https://gdc.cancer.gov/about-data/publications/mc3-2017, ftp://ftp.sanger.ac.uk/pub/cancer/Nik-ZainalEtAl-560BreastGenomes, https://www.synapse.org/#!Synapse:syn26706790, https://www.synapse.org/#!Synapse:syn11726618, and https://www.synapse.org/#!Synapse:syn11801497. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The AACR Project GENIE dataset could be retrieved from Synapse (https://synapse.org/genie)