Cited by 304Cancer Genomics and DiagnosticsChromatin Remodeling and CancerCancer Immunotherapy and Biomarkers

A practical framework and online tool for mutational signature analyses show intertissue variation and driver dependencies

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Degasperi, Andrea, Amarante, Tauanne Dias, Czarnecki, Jan, Shooter, Scott, Zou, Xueqing, Glodzik, Dominik, Morganella, Sandro, Nanda, Arjun S. +9 more·2020·Nature Cancer

Abstract

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. Degasperi et al. introduce a practical framework and Signal, an online tool, to analyze mutational signatures. They find evidence of tissue-specific variability in mutational signatures, which may impact tumor classification and clinical application.

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  • Application of HRDetect in primary tumors revealed that the prevalence of HRD extends beyond BRCA1/2-deficient breast cancer tumors and occurs at varying frequencies in different cancer types.

    “Application of this tool in primary tumors revealed that the prevalence of HRD extends beyond BRCA1/2-deficient breast cancer tumors, and occurs at varying frequencies in different cancer types10.”

    From Pan-cancer landscape of homologous recombination deficiency. (2020) · cites this paper as [10]

  • Predictions of CHORD and HRDetect on the PCAWG dataset were concordant for 1506/1526 (99%) samples.

    “In addition, the predictions of CHORD and HRDetect on the PCAWG dataset10 were concordant for the vast majority of samples (1506/1526; 99%) (Supplementary Fig. 10).”

    From Pan-cancer landscape of homologous recombination deficiency. (2020) · cites this paper as [10]

    The Methods (Datasets; page unavailable) identify the PCAWG cohort, and the Results (Homologous recombination deficiency across 21 organs; page unavailable) discuss HRDetect predictions. Searches for CHORD and for the 1506/1526 concordance figure found no passage comparing CHORD with HRDetect, so our copy does not verify the claimed 99% agreement. (LLM, conf=0.73)

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References 33 · Cited by 304

Research works printed but not linked: 3

  1. [8]Lee DD Seung HS Advances in neural information processing systems 556 562
  2. [32]Wagstaff K Proceedings of the Eighteenth International Conference on Machine Learning Morgan Kaufmann Publishers Inc 2001 577 584
  3. [33]Martello S Toth P North-Holland Mathematics Studies Elsevier 1987 132 259 282

Authors
Degasperi, A., Amarante, T. D., Czarnecki, J., Shooter, S., Zou, X., Glodzik, D., Morganella, S., Nanda, A. S., Badja, C., Koh, G., Momen, S. E., Georgakopoulos-Soares, I., Dias, J. M. L., Young, J., Memari, Y., Davies, H., & Nik-Zainal, S.
Affiliations
  • University of Cambridge (GB)
  • Wellcome Sanger Institute (GB)
  • Addenbrooke's Hospital (GB)
Venue
Nature Cancer
Published
2020-02-17
Volume
1
Issue
2
Pages
249-263
ISSN
2662-1347 (ISSN-L)
OpenAlex
W3006132030
Cited by
304
References
33
Citations by year
2026: 34 · 2025: 37 · 2024: 51 · 2023: 84 · 2022: 46 · 2021: 38 · 2020: 14
FWCI
16.36
Type
journal article
Language
en
Open access
Locations
  • Nature Cancer (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • Lund University Publications (Lund University) (submittedVersion)
Funders
  • Cancer Research UK (C60100/A23433, C60100/A23916, C60100/A25274)
  • Wellcome Trust (WT100126/B/13/Z)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
  • Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
Keywords
mutational signatures, tumor classification, tumor stratification
MeSH terms
Humans, Mutation, Neoplasms, Carcinogenesis

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