TY - JOUR
T1 - A practical framework and online tool for mutational signature analyses show intertissue variation and driver dependencies
AU - Degasperi, Andrea
AU - Amarante, Tauanne Dias
AU - Czarnecki, Jan
AU - Shooter, Scott
AU - Zou, Xueqing
AU - Glodzik, Dominik
AU - Morganella, Sandro
AU - Nanda, Arjun S.
AU - Badja, Cherif
AU - Koh, Gene
AU - Momen, Sophie E.
AU - Georgakopoulos-Soares, Ilias
AU - Dias, João M.L.
AU - Young, Jamie
AU - Memari, Yasin
AU - Davies, Helen
AU - Nik-Zainal, Serena
N1 - Publisher Copyright:
© 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.
PY - 2020/2/1
Y1 - 2020/2/1
N2 - Mutational signatures are patterns of mutations that arise during tumorigenesis. We present an enhanced, practical framework for mutational signature analyses. Applying these methods to 3,107 whole-genome-sequenced (WGS) primary cancers of 21 organs reveals known signatures and nine previously undescribed rearrangement signatures. We highlight interorgan variability of signatures and present a way of visualizing that diversity, reinforcing our findings in an independent analysis of 3,096 WGS metastatic cancers. Signatures with a high level of genomic instability are dependent on TP53 dysregulation. We illustrate how uncertainty in mutational signature identification and assignment to samples affects tumor classification, reinforcing that using multiple orthogonal mutational signature data is not only beneficial, but is also essential for accurate tumor stratification. Finally, we present a reference web-based tool for cancer and experimentally generated mutational signatures, called Signal (https://signal.mutationalsignatures.com), that also supports performing mutational signature analyses.
AB - Mutational signatures are patterns of mutations that arise during tumorigenesis. We present an enhanced, practical framework for mutational signature analyses. Applying these methods to 3,107 whole-genome-sequenced (WGS) primary cancers of 21 organs reveals known signatures and nine previously undescribed rearrangement signatures. We highlight interorgan variability of signatures and present a way of visualizing that diversity, reinforcing our findings in an independent analysis of 3,096 WGS metastatic cancers. Signatures with a high level of genomic instability are dependent on TP53 dysregulation. We illustrate how uncertainty in mutational signature identification and assignment to samples affects tumor classification, reinforcing that using multiple orthogonal mutational signature data is not only beneficial, but is also essential for accurate tumor stratification. Finally, we present a reference web-based tool for cancer and experimentally generated mutational signatures, called Signal (https://signal.mutationalsignatures.com), that also supports performing mutational signature analyses.
UR - http://www.scopus.com/inward/record.url?scp=85083741435&partnerID=8YFLogxK
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U2 - 10.1038/s43018-020-0027-5
DO - 10.1038/s43018-020-0027-5
M3 - Article
C2 - 32118208
AN - SCOPUS:85083741435
SN - 2662-1347
VL - 1
SP - 249
EP - 263
JO - Nature Cancer
JF - Nature Cancer
IS - 2
ER -