1. Cancer Biology
  2. Computational and Systems Biology

Pan-cancer association of DNA repair deficiencies with whole-genome mutational patterns

  1. Simon Grund Sørensen
  2. Amruta Shrikhande
  3. Gustav Alexander Poulsgaard
  4. Mikkel Hovden Christensen
  5. Johanna Bertl
  6. Britt Elmedal Laursen
  7. Eva R Hoffmann  Is a corresponding author
  8. Jakob Skou Pedersen  Is a corresponding author
  1. Aarhus University Hospital, Denmark
  2. University of Copenhagen, Denmark
https://doi.org/10.7554/eLife.81224
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  1. Simon Grund Sørensen
  2. Amruta Shrikhande
  3. Gustav Alexander Poulsgaard
  4. Mikkel Hovden Christensen
  5. Johanna Bertl
  6. Britt Elmedal Laursen
  7. Eva R Hoffmann
  8. Jakob Skou Pedersen
(2023)
Pan-cancer association of DNA repair deficiencies with whole-genome mutational patterns
eLife 12:e81224.
https://doi.org/10.7554/eLife.81224
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Abstract

DNA repair deficiencies in cancers may result in characteristic mutational patterns, as exemplified by deficiency of BRCA1/2 and efficacy prediction for PARP-inhibitors. We trained and evaluated predictive models for loss-of-function (LOF) of 145 individual DDR genes based on genome-wide mutational patterns, including structural variants, indels, and base-substitution signatures. We identified 24 genes whose deficiency could be predicted with good accuracy, including expected mutational patterns for BRCA1/2, MSH3/6, TP53, and CDK12 LOF variants. CDK12 is associated with tandem-duplications, and we here demonstrate that this association can accurately predict gene deficiency in prostate cancers (area under the ROC curve=0.97). Our novel associations include mono- or biallelic LOF variants of ATRX, IDH1, HERC2, CDKN2A, PTEN, and SMARCA4, and our systematic approach yielded a catalogue of predictive models, which may provide targets for further research and development of treatment, and potentially help guide therapy.

Data availability

This study is based on analyses of human germline and cancer somatic variant data. The data sets were generated and made available by the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium and from the Hartwig Medical Foundation (HMF). The majority of the data cannot be publicly accessed as it includes protected personal data, including germline variants, which cannot be made publicly available. However, accession to the underlying data sets can be achieved through applications to ICGC/TCGA and HMF as described below.The public parts of the PCAWG data set are available at https://dcc.icgc.org/releases/PCAWG, whereas controlled files may be accessed through applications to gbGaP and DACO, which should include a project proposal, as instructed on this site https://docs.icgc.org/pcawg/data/. The ICGC study ID of the project is EGAS00001001692.The HMF data used in this project may be found by accession code DR-044 and can be obtained by submitting an application with a project proposal to the Hartwig Medical Foundation (https://www.hartwigmedicalfoundation.nl/en).Non-personal summary data have been supplied in supplementary tables S1 to S9:Supplementary Table 1: All included tumours and their primary tumour locationsSupplementary Table 2: 736 DDR genes, hg19 coordinates and the number ofpathogenic events across 6,065 cancer genomesSupplementary Table 3: All SBS signature contributions, indels counts, and1104 SV counts, per sample; zip-compressed; tab-separated values (.tsv), may be opened in Microsoft ExcelSupplementary Table 4: All SBS signature contributions, indels counts, andSV counts, per sample, log-transformed and scaled to z-scores; zip-compressed; tab-separated values (.tsv), may be opened in Microsoft ExcelSupplementary Table 5: Proposed Etiologies of base substitution signaturesSupplementary Table 6: All models (n=535)Supplementary Table 7: Pathogenic events in each of the 535 LOF-setsSupplementary Table 8: Shortlisted models (n=48)Supplementary Table 9: Correlation between features in shortlisted modelsSupplementary Table 10: Survival analysis for the shortlisted modelsThe third-party software used for data analysis includes:Pathogenicity annotation using CADD annotation software, which may be accessed at https://cadd.gs.washington.eduSignature analysis using Signature Tools Lib, which has been installed from the GitHub: https://github.com/Nik-Zainal-Group/signature.tools.libCode that we developed locally for the analysis can be accessed at:https://github.com/SimonGrund/DDR_Predict

Article and author information

Author details

  1. Simon Grund Sørensen

    Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
    Competing interests
    The authors declare that no competing interests exist.

  2. Amruta Shrikhande

    Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
    Competing interests
    The authors declare that no competing interests exist.

  3. Gustav Alexander Poulsgaard

    Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
    Competing interests
    The authors declare that no competing interests exist.

  4. Mikkel Hovden Christensen

    Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
    Competing interests
    The authors declare that no competing interests exist.

  5. Johanna Bertl

    Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
    Competing interests
    The authors declare that no competing interests exist.

  6. Britt Elmedal Laursen

    Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
    Competing interests
    The authors declare that no competing interests exist.

  7. Eva R Hoffmann

    Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
    For correspondence
    eva@sund.ku.dk
    Competing interests
    The authors declare that no competing interests exist.

  8. Jakob Skou Pedersen

    Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
    For correspondence
    jakob.skou@clin.au.dk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7236-4001

Funding

Novo Nordisk Fonden (NNF15OC0016662)

  • Eva R Hoffmann

Cancer Research UK (C23210/A7574)

  • Eva R Hoffmann

Danmarks Frie Forskningsfond (8021-00419B)

  • Jakob Skou Pedersen

Kræftens Bekæmpelse (R307-A17932)

  • Jakob Skou Pedersen

Aarhus Universitets Forskningsfond (AUFF-E-2020-6-14)

  • Jakob Skou Pedersen

Sundhedsvidenskabelige Fakultet, Aarhus Universitet (PhD stipend)

  • Simon Grund Sørensen

Sundhed, Region Midtjylland (A2972)

  • Gustav Alexander Poulsgaard

Danmarks Grundforskningsfond (DNRF115)

  • Eva R Hoffmann

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. W Kimryn Rathmell, Vanderbilt University Medical Center, United States

Ethics

Human subjects: We analysed data generated and made available by the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) as well as the Hartwig Medical Foundation (HMF). The research conforms to the principles of the Helsinki Declaration.

Version history

  1. Preprint posted: February 3, 2022 (view preprint)
  2. Received: June 20, 2022
  3. Accepted: February 26, 2023
  4. Accepted Manuscript published: March 8, 2023 (version 1)
  5. Version of Record published: April 19, 2023 (version 2)

Copyright

© 2023, Sørensen et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Simon Grund Sørensen
  2. Amruta Shrikhande
  3. Gustav Alexander Poulsgaard
  4. Mikkel Hovden Christensen
  5. Johanna Bertl
  6. Britt Elmedal Laursen
  7. Eva R Hoffmann
  8. Jakob Skou Pedersen
(2023)
Pan-cancer association of DNA repair deficiencies with whole-genome mutational patterns
eLife 12:e81224.
https://doi.org/10.7554/eLife.81224

Share this article

https://doi.org/10.7554/eLife.81224

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