Skip to main content

Advertisement

SpringerLink
Log in

A survey of cancer genome signatures identifies genes connected to distinct chromosomal instability phenotypes

  • Article
  • Published:
The Pharmacogenomics Journal Submit manuscript

Abstract

Certain breast and ovarian cancers are characterised by high levels of chromosomal instability. We established a suite of eleven SNP array-based signatures of various forms of chromosomal instability. To understand what biological mechanisms might underpin these signatures, we generated and assembled genetic-feature data including allele-specific expression, fusion genes, gene expression, methylation, somatic coding mutations and protein expression. For each signature, we extracted a compendium of significantly associated genetic features using machine learning. We established an association between subchromosomal allelic imbalance-based measures and DNA repair genes. Numerical chromosomal instability and chromothripsis were found to have distinct genetic associations but shared a relationship to mitotic processes, while whole-genome doubling was characterised by TP53 mutation, and high AURKA and GINS1 expression. Furthermore, we identified two genetically distinct forms of tandem duplicator phenotypes. These findings identify potentially novel genomic targets for validation and drug development for specific subsets of breast and ovarian cancer.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1: A signature of numerical chromosomal instability.
Fig. 2: Correlation between genomic signatures across tumour cohorts.
Fig. 3: Data types and data subsets used as regressors in three elastic net models.
Fig. 4: Multi-omic genetic signatures associated with SAi.

Similar content being viewed by others

Code availability

R code (version 3.0.2) for the estimation of numerical CN and the generation of the SNCNA score is available upon request.

References

  1. Wu S, Powers S, Zhu W, Hannun YA. Substantial contribution of extrinsic risk factors to cancer development. Nature. 2015;529:43–47.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Roy R, Chun J, Powell SN. BRCA1 and BRCA2: different roles in a common pathway of genome protection. Nat Rev Cancer. 2012;12:68–78.

    Article  CAS  Google Scholar 

  3. Coschi CH, Ishak CA, Gallo D, Marshall A, Talluri S, Wang J, et al. Haploinsufficiency of an RB-E2F1-condensin II complex leads to aberrant replication and aneuploidy. Cancer Discov. 2014;4:840–53.

    Article  CAS  PubMed  Google Scholar 

  4. Silk AD, Zasadil LM, Holland AJ, Vitre B, Cleveland DW, Weaver BA. Chromosome missegregation rate predicts whether aneuploidy will promote or suppress tumors. Proc Natl Acad Sci USA. 2013;110:E4134–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Carter SL, Cibulskis K, Helman E, McKenna A, Shen H, Zack T, et al. Absolute quantification of somatic DNA alterations in human cancer. Nat Biotechnol. 2012;30:413–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Burrell RA, McClelland SE, Endesfelder D, Groth P, Weller M-C, Shaikh N, et al. Replication stress links structural and numerical cancer chromosomal instability. Nature. 2013;494:492–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Watkins JA, Irshad S, Grigoriadis A, Tutt AN. Genomic scars as biomarkers of homologous recombination deficiency and drug response in breast and ovarian cancers. Breast Cancer Res. 2014;16:211.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Scheerens H, Malong A, Bassett K, Boyd Z, Gupta V, Harris J, et al. Current status of companion and complementary diagnostics: strategic considerations for development and launch. Clin Transl Sci. 2017;10:84–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Zack TI, Schumacher SE, Carter SL, Cherniack AD, Saksena G, Tabak B, et al. Pan-cancer patterns of somatic copy number alteration. Nat Genet. 2013;45:1134–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Cai H, Kumar N, Bagheri HC, von Mering C, Robinson MD, Baudis M. Chromothripsis-like patterns are recurring but heterogeneously distributed features in a survey of 22,347 cancer genome screens. BMC Genom. 2014;15:82.

    Article  Google Scholar 

  11. Stephens PJ, Greenman CD, Fu B, Yang F, Bignell GR, Mudie LJ, et al. Massive genomic rearrangement acquired in a single catastrophic event during cancer development. Cell. 2011;144:27–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Schouten PC, Grigoriadis A, Kuilman T, Mirza H, Watkins JA, Cooke SA, et al. Robust BRCA1-like classification of copy number profiles of samples repeated across different datasets and platforms. Mol Oncol. 2015;9:1274–86.

  13. Birkbak NJ, Wang ZC, Kim J-Y, Eklund AC, Li Q, Tian R, et al. Telomeric allelic imbalance indicates defective DNA repair and sensitivity to DNA-damaging agents. Cancer Discov. 2012;2:366–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Watkins J, Weekes D, Shah V, Gazinska P, Joshi S, Sidhu B, et al. Genomic complexity profiling reveals that HORMAD1 overexpression contributes to homologous recombination deficiency in triple-negative breast cancers. Cancer Discov. 2015;5:488–505.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Popova T, Manié E, Rieunier G, Caux-Moncoutier V, Tirapo C, Dubois T, et al. Ploidy and large-scale genomic instability consistently identify basal-like breast carcinomas with BRCA1/2 Inactivation. Cancer Res. 2012;72:5454–62.

    Article  CAS  PubMed  Google Scholar 

  16. Abkevich V, Timms KM, Hennessy BT, Potter J, Carey MS, Meyer LA, et al. Patterns of genomic loss of heterozygosity predict homologous recombination repair defects in epithelial ovarian cancer. Br J Cancer. 2012;107:1776–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Menghi F, Inaki K, Woo X, Kumar PA, Grzeda KR, Malhotra A, et al. The tandem duplicator phenotype as a distinct genomic configuration in cancer. Proc Natl Acad Sci USA. 2016;113:E2373–E2382.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Watkins J, Tutt A, Grigoriadis A. Tandem duplications contribute to not one but two distinct phenotypes. Proc Natl Acad Sci USA. 2016;113:E5257–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Ng CKY, Cooke SL, Howe K, Newman S, Xian J, Temple J, et al. The role of tandem duplicator phenotype in tumour evolution in high-grade serous ovarian cancer. J Pathol. 2012;226:703–12.

    Article  CAS  PubMed  Google Scholar 

  20. Nik-Zainal S, Davies H, Staaf J, Ramakrishna M, Glodzik D, Zou X, et al. Landscape of somatic mutations in 560 breast cancer whole-genome sequences. Nature. 2016;534:47–54.

  21. Morganella S, Alexandrov LB, Glodzik D, Zou X, Davies H, Staaf J, et al. The topography of mutational processes in breast cancer genomes. Nat Commun. 2016;7:11383.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Lord CJ, Ashworth A. BRCAness revisited. Nat Rev Cancer. 2016;16:110–20.

  23. Garnett MJ, Edelman EJ, Heidorn SJ, Greenman CD, Dastur A, Lau KW, et al. Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature. 2012;483:570–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin AA, Kim S, et al. The cancer cell line encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012;483:603–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Wang W, Carvalho B, Miller ND, Pevsner J, Chakravarti A, Irizarry RA. Estimating genome-wide copy number using allele-specific mixture models. J Comput Biol. 2008;15:857–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Knutsen T, Padilla-Nash HM, Wangsa D, Barenboim-Stapleton L, Camps J, McNeil N, et al. Definitive molecular cytogenetic characterization of 15 colorectal cancer cell lines. Genes Chromosomes Cancer. 2010;49:204–23.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. SKY Karyotypes and Molecular Cytogenetics of Common Epithelial Cancers. 2012. http://www.path.cam.ac.uk/~pawefish. Accessed 21 November 2019.

  28. Heinze G, Schemper M. A solution to the problem of separation in logistic regression. Stat Med. 2002;21:2409–19.

    Article  PubMed  Google Scholar 

  29. The Cancer Genome Atlas Research Network. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490:61–70.

    Article  Google Scholar 

  30. Yoshihara K, Wang Q, Torres-Garcia W, Zheng S, Vegesna R, Kim H, et al. The landscape and therapeutic relevance of cancer-associated transcript fusions. Oncogene. 2015;34:4845–54.

    Article  CAS  PubMed  Google Scholar 

  31. McBride DJ, Etemadmoghadam D, Cooke SL, Alsop K, George J, Butler A, et al. Tandem duplication of chromosomal segments is common in ovarian and breast cancer genomes. J Pathol. 2012;227:446–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Menghi F, Barthel FP, Yadav V, Tang M, Ji B, Tang Z, et al. The tandem duplicator phenotype is a prevalent genome-wide cancer configuration driven by distinct gene mutations. Cancer Cell. 2018;34:197–210.e5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Manié E, Popova T, Battistella A, Tarabeux J, Caux-Moncoutier V, Golmard L, et al. Genomic hallmarks of homologous recombination deficiency in invasive breast carcinomas. Int J Cancer. 2015;138:891–900.

    Article  PubMed  Google Scholar 

  34. Schouten PC, van Dyk E, Braaf LM, Mulder L, Lips EH, de Ronde JJ, et al. Platform comparisons for identification of breast cancers with a BRCA-like copy number profile. Breast Cancer Res Treat. 2013;139:317–27.

    Article  CAS  PubMed  Google Scholar 

  35. Turner N, Lambros MB, Horlings HM, Pearson A, Sharpe R, Natrajan R, et al. Integrative molecular profiling of triple negative breast cancers identifies amplicon drivers and potential therapeutic targets. Oncogene. 2010;29:2013–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Telli ML, Timms KM, Reid JE, Hennessy B, Mills GB, Jensen KC, et al. Homologous recombination deficiency (HRD) score predicts response to platinum-containing neoadjuvant chemotherapy in patients with triple negative breast cancer. Clin Cancer Res. 2016;22:3764–73.

  37. Grigorova M, Staines JM, Ozdag H, Caldas C, Edwards PAW. Possible causes of chromosome instability: comparison of chromosomal abnormalities in cancer cell lines with mutations in BRCA1, BRCA2, CHK2 and BUB1. Cytogenet Genome Res. 2004;104:333–40.

    Article  CAS  PubMed  Google Scholar 

  38. Hanks S, Coleman K, Reid S, Plaja A, Firth H, Fitzpatrick D, et al. Constitutional aneuploidy and cancer predisposition caused by biallelic mutations in BUB1B. Nat Genet. 2004;36:1159–61.

    Article  CAS  PubMed  Google Scholar 

  39. Zhang C-Z, Spektor A, Cornils H, Francis JM, Jackson EK, Liu S, et al. Chromothripsis from DNA damage in micronuclei. Nature. 2015;522:179–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Thompson L, Jeusset L, Lepage C, McManus K. Evolving therapeutic strategies to exploit chromosome instability in cancer. Cancers (Basel). 2017;9:151.

    Article  Google Scholar 

  41. Willis NA, Frock RL, Menghi F, Duffey EE, Panday A, Camacho V, et al. Mechanism of tandem duplication formation in BRCA1-mutant cells. Nature. 2017;551:590–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Costantino L, Sotiriou SK, Rantala JK, Magin S, Mladenov E, Helleday T, et al. Break-induced replication repair of damaged forks induces genomic duplications in human cells. Science. 2014;343:88–91.

    Article  CAS  PubMed  Google Scholar 

  43. Neelsen KJ, Zanini IMY, Mijic S, Herrador R, Zellweger R, Ray Chaudhuri A, et al. Deregulated origin licensing leads to chromosomal breaks by rereplication of a gapped DNA template. Genes Dev. 2013;27:2537–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Curtis C, Shah SP, Chin S-F, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012;486:346–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Telli ML, Jensen KC, Vinayak S, Kurian AW, Lipson JA, Flaherty PJ, et al. Phase II study of gemcitabine, carboplatin, and iniparib as neoadjuvant therapy for triple-negative and BRCA1/2 mutation-associated breast cancer with assessment of a tumor-based measure of genomic instability: PrECOG 0105. J Clin Oncol. 2015;33:1895–901.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012;2:401–4.

    Article  PubMed  Google Scholar 

  47. Mayba O, Gilbert HN, Liu J, Haverty PM, Jhunjhunwala S, Jiang Z, et al. MBASED: allele-specific expression detection in cancer tissues and cell lines. Genome Biol. 2014;15:405.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Lex A, Gehlenborg N, Strobelt H, Vuillemot R, Pfister H. UpSet: visualization of intersecting sets. IEEE Trans Vis Comput Graph. 2014;20:1983–92.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Research Department of Haematology, UCL Cancer Institute, University College London, London, UK

    Manar S. Shafat

  2. PILAR Research Network, London, UK

    Manar S. Shafat, Eamaan S. Rufaie & Johnathan Watkins

  3. Department of Natural Sciences, School of Science and Technology, Middlesex University, London, UK

    Eamaan S. Rufaie

Authors
  1. Manar S. Shafat
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eamaan S. Rufaie
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Johnathan Watkins
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

JW conceived and designed the study. JW collected and managed ‘omic and clinical data. JW performed copy-number analysis. JW generated ASE data. JW, MS and ER performed platinum treatment response prediction analysis. JW and MS performed elastic net regression. JW and MS wrote the paper.

Corresponding author

Correspondence to Johnathan Watkins.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shafat, M.S., Rufaie, E.S. & Watkins, J. A survey of cancer genome signatures identifies genes connected to distinct chromosomal instability phenotypes. Pharmacogenomics J 21, 390–401 (2021). https://doi.org/10.1038/s41397-021-00217-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41397-021-00217-9

  • Springer Nature Limited

This article is cited by

Search

Navigation