Suchergebnisse

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).

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 ; Postprint (author's final draft)

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 ; Postprint (author's final draft)

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.

Multiple myeloma (MM) is consistently preceded by precursor conditions recognized clinically as monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma (SMM). We interrogate the whole genome sequence (WGS) profile of 18 MGUS and compare them with those from 14 SMMs and 80 MMs. We show that cases with a non-progressing, clinically stable myeloma precursor condition (n=15) are characterized by later initiation in the patient's life and by the absence of myeloma defining genomic events including: chromothripsis, templated insertions, mutations in driver genes, aneuploidy, and canonical APOBEC mutational activity. This data provides evidence that WGS can be used to recognize two biologically and clinically distinct myeloma precursor entities that are either progressive or stable. The factors that are associated with myeloma precursor condition progression are not well understood. Here the authors find that monoclonal gammopathies of undetermined significance and smoldering myelomas that did not progress to multiple myelomas have a distinct genomic profile and emerge later in the patient's life. ; We want to thank Dr. Vincent S Rajkumar for important and useful scientific feedback on the final draft. This work was supported by the Society of Memorial Sloan Kettering, by the Sylvester Comprehensive Cancer Center NCI Core Grant (P30 CA 240139), by the Memorial Sloan Kettering Cancer Center NCI Core Grant (P30 CA 008748), by the Multiple Myeloma Research Foundation (MMRF), by the Perelman Family Foundation, and by the Riney Family Multiple Myeloma Research Program Fund. F.M. is supported by the American Society of Hematology, the International Myeloma Foundation and The Society of Memorial Sloan Kettering Cancer Center. N.B. is funded by the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement no. 817997). K.H.M. is supported by the Royal Australasian College of Physicians Dr. Helen Rarity McCreanor Traveling Fellowship. This study is part of the Limburg Clinical Research Center (LCRC) UHasselt-ZOL-Jessa, supported by the foundation Limburg Sterk Merk (LSM), Hasselt University, Ziekenhuis Oost-Limburg and Jessa Hospital. Additionally, this research is supported by Limburgs Kankerfonds, and LiveALife. ; Maura, F (corresponding author), Mem Sloan Kettering Canc Ctr, Dept Med, Myeloma Serv, 1275 York Ave, New York, NY 10021 USA. Landgren, O; Maura, F (corresponding author), Univ Miami, Sylvester Comprehens Canc Ctr, Myeloma Program, Miami, FL 33124 USA. col15@miami.edu; fxm557@med.miami.edu

The multiple myeloma (MM) genome is heterogeneous and evolves through preclinical and post-diagnosis phases. Here we report a catalog and hierarchy of driver lesions using sequences from 67 MM genomes serially collected from 30 patients together with public exome datasets. Bayesian clustering defines at least 7 genomic subgroups with distinct sets of co-operating events. Focusing on whole genome sequencing data, complex structural events emerge as major drivers, including chromothripsis and a novel replication-based mechanism of templated insertions, which typically occur early. Hyperdiploidy also occurs early, with individual trisomies often acquired in different chronological windows during evolution, and with a preferred order of acquisition. Conversely, positively selected point mutations, whole genome duplication and chromoplexy events occur in later disease phases. Thus, initiating driver events, drawn from a limited repertoire of structural and numerical chromosomal changes, shape preferred trajectories of evolution that are biologically relevant but heterogeneous across patients. ; F.M. is supported by AIL (Associazione Italiana Contro le Leucemie-Linfomi e Mieloma ONLUS), by SIES (Società Italiana di Ematologia Sperimentale), and by the Memorial Sloan Kettering Cancer Center NCI Core Grant (P30 CA 008748). N.B. is funded by AIRC (Associazione Italiana per la Ricerca sul Cancro) through a MFAG (no. 17658) and by the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement no. 817997). 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. and K.C.A.) and 5P50CA100707-13 (N.C.M., H.A.L. and K.C.A) ; SI