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mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies

Rustad, Even H., Nadeu, Ferran, Angelopoulos, Nicos, Ziccheddu, Bachisio, Bolli, Niccolò, Puente, Xose S., Campo, Elias, Landgren, Ola and Maura, Francesco 2021. mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies. Communications Biology 4 (1) , 424. 10.1038/s42003-021-01938-0

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Abstract

Mutational signatures have emerged as powerful biomarkers in cancer patients, with prognostic and therapeutic implications. Wider clinical utility requires access to reproducible algorithms, which allow characterization of mutational signatures in a given tumor sample. Here, we show how mutational signature fitting can be applied to hematological cancer genomes to identify biologically and clinically important mutational processes, highlighting the importance of careful interpretation in light of biological knowledge. Our newly released R package mmsig comes with a dynamic error-suppression procedure that improves specificity in important clinical and biological settings. In particular, mmsig allows accurate detection of mutational signatures with low abundance, such as those introduced by APOBEC cytidine deaminases. This is particularly important in the most recent mutational signature reference (COSMIC v3.1) where each signature is more clearly defined. Our mutational signature fitting algorithm mmsig is a robust tool that can be implemented immediately in the clinic.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
Additional Information: This article is licensed under a Creative Commons Attribution 4.0 International License
Publisher: Nature Research
ISSN: 2399-3642
Funders: European Regional Development Fund and Welsh Government (Ser Cymru programme)
Date of First Compliant Deposit: 12 April 2021
Date of Acceptance: 3 March 2021
Last Modified: 12 Apr 2021 10:00
URI: http://orca.cf.ac.uk/id/eprint/140422

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