mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies
Year: 2021
Type: article
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.
Source: Communications Biology
Institutions: Oslo University Hospital, Memorial Sloan Kettering Cancer Center, Centro de Investigación Biomédica en Red de Cáncer, Consorci Institut D'Investigacions Biomediques August Pi I Sunyer, Cardiff University, University of Miami, Sylvester Comprehensive Cancer Center, University of Turin, University of Milan, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Universidad de Oviedo, Hospital Clínic de Barcelona, Universitat de Barcelona
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,290
Funders: U.S. Department of Health and Human Services, Multiple Myeloma Research Foundation, American Society of Hematology, International Myeloma Foundation, Memorial Sloan-Kettering Cancer Center, Society of Memorial Sloan Kettering, Sylvester Comprehensive Cancer Center, University of Miami Health Systems, European Commission, European Regional Development Fund, National Cancer Institute, Division of Cancer Epidemiology and Genetics, National Cancer Institute, H2020 European Research Council
Awards: G1007166040, spontaneous Evolution and Clonal heterOgeneity in MoNoclonal Gammopathies: from mechanisms of progression to clinical management, G2156476721, G2246262118, G2538737708, G289723095, G305175183, G4102770861, G434337789, Cancer Center Support Grant, The Sylvester Cancer Center Support Grant
OpenAlex ID: W3147379882