Pan-cancer association of DNA repair deficiencies with whole-genome mutational patterns
- Aarhus University Hospital, Denmark
- University of Copenhagen, Denmark
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
Jakob Skou Pedersen
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
- 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
- Preprint posted: February 3, 2022 (view preprint)
- Received: June 20, 2022
- Accepted: February 26, 2023
- Accepted Manuscript published: March 8, 2023 (version 1)
- 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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Pan-cancer association of DNA repair deficiencies with whole-genome mutational patterns
eLife 12:e81224.
https://doi.org/10.7554/eLife.81224
Further reading
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- Cancer Biology
- Epidemiology and Global Health
Background:
Age is the most important risk factor for cancer, but aging rates are heterogeneous across individuals. We explored a new measure of aging-Phenotypic Age (PhenoAge)-in the risk prediction of site-specific and overall cancer.
Methods:
Using Cox regression models, we examined the association of Phenotypic Age Acceleration (PhenoAgeAccel) with cancer incidence by genetic risk group among 374,463 participants from the UK Biobank. We generated PhenoAge using chronological age and nine biomarkers, PhenoAgeAccel after subtracting the effect of chronological age by regression residual, and an incidence-weighted overall cancer polygenic risk score (CPRS) based on 20 cancer site-specific polygenic risk scores (PRSs).
Results:
Compared with biologically younger participants, those older had a significantly higher risk of overall cancer, with hazard ratios (HRs) of 1.22 (95% confidence interval, 1.18–1.27) in men, and 1.26 (1.22–1.31) in women, respectively. A joint effect of genetic risk and PhenoAgeAccel was observed on overall cancer risk, with HRs of 2.29 (2.10–2.51) for men and 1.94 (1.78–2.11) for women with high genetic risk and older PhenoAge compared with those with low genetic risk and younger PhenoAge. PhenoAgeAccel was negatively associated with the number of healthy lifestyle factors (Beta = –1.01 in men, p<0.001; Beta = –0.98 in women, p<0.001).
Conclusions:
Within and across genetic risk groups, older PhenoAge was consistently related to an increased risk of incident cancer with adjustment for chronological age and the aging process could be retarded by adherence to a healthy lifestyle.
Funding:
This work was supported by the National Natural Science Foundation of China (82230110, 82125033, 82388102 to GJ; 82273714 to MZ); and the Excellent Youth Foundation of Jiangsu Province (BK20220100 to MZ).
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- Cancer Biology
- Chromosomes and Gene Expression
The chromatin-associated protein WD Repeat Domain 5 (WDR5) is a promising target for cancer drug discovery, with most efforts blocking an arginine-binding cavity on the protein called the ‘WIN’ site that tethers WDR5 to chromatin. WIN site inhibitors (WINi) are active against multiple cancer cell types in vitro, the most notable of which are those derived from MLL-rearranged (MLLr) leukemias. Peptidomimetic WINi were originally proposed to inhibit MLLr cells via dysregulation of genes connected to hematopoietic stem cell expansion. Our discovery and interrogation of small-molecule WINi, however, revealed that they act in MLLr cell lines to suppress ribosome protein gene (RPG) transcription, induce nucleolar stress, and activate p53. Because there is no precedent for an anticancer strategy that specifically targets RPG expression, we took an integrated multi-omics approach to further interrogate the mechanism of action of WINi in human MLLr cancer cells. We show that WINi induce depletion of the stock of ribosomes, accompanied by a broad yet modest translational choke and changes in alternative mRNA splicing that inactivate the p53 antagonist MDM4. We also show that WINi are synergistic with agents including venetoclax and BET-bromodomain inhibitors. Together, these studies reinforce the concept that WINi are a novel type of ribosome-directed anticancer therapy and provide a resource to support their clinical implementation in MLLr leukemias and other malignancies.
