mmsig: A fitting approach to accurately identify somatic mutational signatures in hematological malignancies Journal Article


Authors: Rustad, E. H.; Nadeu, F.; Angelopoulos, N.; Ziccheddu, B.; Bolli, N.; Puente, X. S.; Campo, E.; Landgren, O.; Maura, F.
Article Title: mmsig: A fitting approach to accurately identify somatic mutational signatures in hematological malignancies
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. © 2021, The Author(s).
Journal Title: Communications Biology
Volume: 4
Issue: 1
ISSN: 2399-3642
Publisher: Springer Nature  
Date Published: 2021-03-29
Start Page: 424
Language: English
DOI: 10.1038/s42003-021-01938-0
PUBMED: 33782531
PROVIDER: scopus
PMCID: PMC8007623
DOI/URL:
Notes: Article -- Export Date: 3 May 2021 -- Source: Scopus
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  1. Carl Ola Landgren
    336 Landgren
  2. Even Holth Rustad
    43 Rustad
  3. Francesco Maura
    56 Maura