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


ABSTRACT: Tumor mutational signatures have the potential to inform cancer diagnosis and treatment. However, their detection in targeted sequenced tumors is hampered by sparse mutations and variability in targeted gene panels. Here we present SATS, a scalable mutational signature analyzer addressing these challenges by leveraging tumor mutational burdens from targeted gene panels. Through analyzing simulated data, pseudo-targeted sequencing data generated by down-sampling whole exome and genome data, and samples with matched whole genome sequencing and targeted sequencing, we showed that SATS can accurately detect common mutational signatures and estimate signature burdens. Applying SATS to 111,711 targeted sequenced tumors from the AACR Project GENIE, we generated a pan-cancer catalogue of mutational signatures tailored to targeted sequencing, enabling estimation of signature burdens within individual tumors. Integrating signatures with clinical data, we demonstrated SATS's clinical utility, including identifying signatures enriched in early-onset hypermutated colorectal cancers and signatures associated with cancer prognosis and immunotherapy response.

SUBMITTER: Lee D 

PROVIDER: S-EPMC10327246 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

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

Lee Donghyuk D   Hua Min M   Wang Difei D   Song Lei L   Zhang Tongwu T   Hua Xing X   Yu Kai K   Yang Xiaohong R XR   Chanock Stephen J SJ   Shi Jianxin J   Landi Maria Teresa MT   Zhu Bin B  

medRxiv : the preprint server for health sciences 20240731


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. V  ...[more]

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