Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data.

F.M. is supported by A.I.L. (Associazione Italiana Contro le Leucemie-Linfomi e Mieloma ONLUS), by S.I.E.S. (Società Italiana di Ematologia Sperimentale) and by the Memorial Sloan Kettering Cancer Center NCI Core Grant (P30 CA 008748). N.B. is funded by the University of Milan (project 22597-PSR2017_DIP_032) and by the European Research Council under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 817997). X.S.P. is supported by thr Ministerio de Economía y Competitividad Grant No. SAF2017–87811-R. F.N. is supported by a pre-doctoral fellowship of the MINECO (BES-2016–076372). This work was supported by the Instituto de Salud Carlos III (project PMP15/00007, F.N., E.C.), the “la Caixa” Foundation Grant No HR17-00221 (Health Research 2017 Program, F.N., E.C.), the Ministerio de Economía y Competitividad (MINECO) SAF2013-45836-R (E.C.) from. Plan Nacional de I + D + I, Generalitat de Catalunya Suport Grups de Recerca AGAUR 2017-SGR-1142 (E.C.) and the European Regional Development Fund “Una manera de hacer Europa”. E.C. is supported by ICREA under the ICREA Academia program. A.D. is funded by a CRUK Pioneer Award C60100/A23433. S.N.Z. is funded by a CRUK Advanced Clinician Scientist Award (C60100/A23916) and a CRUK Grand Challenge Award (C60100/A25274). This work was supported by: Department of Veterans Affairs Merit Review Award I01BX001584-01 (N.C.M.), NIH grants P01-155258 (N.C.M., H.A.L., M.F., P.J.C., K.C.A.) and 5P50CA100707-13 (N.C.M., H.A.L., K.C.A). We thank Michael R. Stratton for discussions and help in data interpretation.

Peer Reviewed