Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Genotype-first approach to the detection of hereditary breast and ovarian cancer risk, and effects of risk disclosure to biobank participants

Abstract

Genotype-first approach allows to systematically identify carriers of pathogenic variants in BRCA1/2 genes conferring a high risk of familial breast and ovarian cancer. Participants of the Estonian biobank have expressed support for the disclosure of clinically significant findings. With an Estonian biobank cohort, we applied a genotype-first approach, contacted carriers, and offered return of results with genetic counseling. We evaluated participants’ responses to and the clinical utility of the reporting of actionable genetic findings. Twenty-two of 40 contacted carriers of 17 pathogenic BRCA1/2 variants responded and chose to receive results. Eight of these 22 participants qualified for high-risk assessment based on National Comprehensive Cancer Network criteria. Twenty of 21 counseled participants appreciated being contacted. Relatives of 10 participants underwent cascade screening. Five of 16 eligible female BRCA1/2 variant carriers chose to undergo risk-reducing surgery, and 10 adhered to surveillance recommendations over the 30-month follow-up period. We recommend the return of results to population-based biobank participants; this approach could be viewed as a model for population-wide genetic testing. The genotype-first approach permits the identification of individuals at high risk who would not be identified by application of an approach based on personal and family histories only.

This is a preview of subscription content

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Framework for the return of results.
Fig. 2: Added value of the genotype-first approach to the identification of high-risk individuals.

References

  1. 1.

    Rowley SM, Mascarenhas L, Devereux L, Li N, Amarasinghe KC, Zethoven M, et al. Population-based genetic testing of asymptomatic women for breast and ovarian cancer susceptibility. Genet Med. 2018;21:913–22.

    Article  Google Scholar 

  2. 2.

    Alver M, Palover M, Saar A, Läll K, Zekavat SM, Tõnisson N, et al. Recall by genotype and cascade screening for familial hypercholesterolemia in a population-based biobank from Estonia. Genet Med. 2019;21:1173–80.

    CAS  Article  Google Scholar 

  3. 3.

    Haukkala A, Kujala E, Alha P, Salomaa V, Koskinen S, Swan H, et al. The return of unexpected research results in a biobank study and referral to health care for heritable long QT syndrome. Public Health Genomics. 2013;16:241–50.

    CAS  Article  Google Scholar 

  4. 4.

    Manickam K, Buchanan AH, Schwartz MLB, Hallquist MLG, Williams JL, Rahm AK, et al. Exome sequencing-based screening for BRCA1/2 expected pathogenic variants among adult biobank participants. JAMA Netw Open. 2018;1:e182140.

    Article  Google Scholar 

  5. 5.

    Leitsalu L, Alavere H, Jacquemont S, Kolk A, Maillard AM, Reigo A, et al. Reporting incidental findings of genomic disorder-associated copy number variants to unselected biobank participants. Per Med. 2016;13:303–14.

    CAS  Article  Google Scholar 

  6. 6.

    Vornanen M, Aktan-Collan K, Hallowell N, Konttinen H, Haukkala A. Lay perspectives on receiving different types of genomic secondary findings: a qualitative vignette study. J Genet Couns. 2018;28:343–54.

    Article  Google Scholar 

  7. 7.

    Francke U, Dijamco C, Kiefer AK, Eriksson N, Moiseff B, Tung JY, et al. Dealing with the unexpected: consumer responses to direct-access BRCA mutation testing. PeerJ. 2013;1:e8.

    Article  Google Scholar 

  8. 8.

    Budin-ljøsne I, Mascalzoni D, Soini S, Machado H, Kaye J, Bentzen HB. et al. Feedback of individual genetic results to research participants. Biopreserv Biobank. 2016;14:241–8.

    Article  Google Scholar 

  9. 9.

    Riigikogu. Human Genes Research Act. 2000. https://www.riigiteataja.ee/en/eli/508042019001/consolide.

  10. 10.

    Szabo C, King M. Inherited breast and ovarian cancer. Hum Mol Genet. 1995;4:1811–7.

    CAS  Article  Google Scholar 

  11. 11.

    Miki Y, Swensen J, Shattuck-Eidens D, Futreal PA, Harshman K, Tavtigian S, et al. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science. 1994;266:66–71.

    CAS  Article  Google Scholar 

  12. 12.

    Wooster R, Bignell G, Lancaster J, Swift S, Seal S, Mangion J, et al. Identification of the breast cancer susceptibility gene BRCA2. Nature. 1995;378:789–92.

    CAS  Article  Google Scholar 

  13. 13.

    McClain MR, Palomaki GE, Nathanson KL, Haddow JE. Adjusting the estimated proportion of breast cancer cases associated with BRCA1 and BRCA2 mutations: public health implications. Genet Med. 2005;7:28–33.

    CAS  Article  Google Scholar 

  14. 14.

    Hartmann LC, Lindor NM. The role of risk-reducing surgery in hereditary breast and ovarian cancer. Obstet Gynecol Surv. 2016;71:598–9.

    Article  Google Scholar 

  15. 15.

    Kuchenbaecker KB, Hopper JL, Barnes DR, Phillips KA, Mooij TM, Roos-Blom MJ, et al. Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA. 2017;317:2402–16.

    CAS  Article  Google Scholar 

  16. 16.

    Balmaña J, Díez O, Rubio IT, Cardoso F. BRCA in breast cancer: ESMO clinical practice guidelines. Ann Oncol. 2011;22:31–34.

    Article  Google Scholar 

  17. 17.

    National Comprehensive Cancer Network (NCCN). Breast Cancer Risk Reduction. NCCN Guidelines Version 1.2020.

  18. 18.

    Gabai-Kapara E, Lahad A, Kaufman B, Friedman E, Segev S, Renbaum P, et al. Population-based screening for breast and ovarian cancer risk due to BRCA1 and BRCA2. Proc Natl Acad Sci. 2014;111:14205–10.

    CAS  Article  Google Scholar 

  19. 19.

    Leitsalu L, Haller T, Esko T, Tammesoo M-L, Alavere H, Snieder H, et al. Cohort Profile: Estonian Biobank of the Estonian Genome Center, University of Tartu. Int J Epidemiol. 2015;44:1137–47.

    Article  Google Scholar 

  20. 20.

    McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GRS, Thormann A, et al. The ensembl variant effect predictor. Genome Biol. 2016;17:1–14.

    Article  Google Scholar 

  21. 21.

    Yang H, Wang K. Genomic variant annotation and prioritization with ANNOVAR and wANNOVAR. Nat Protoc. 2015;10:1556–66.

    CAS  Article  Google Scholar 

  22. 22.

    Delaneau O, Howie B, Cox AJ, Zagury JF, Marchini J. Haplotype estimation using sequencing reads. Am J Hum Genet. 2013;93:687–96.

    CAS  Article  Google Scholar 

  23. 23.

    Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7.

    Article  Google Scholar 

  24. 24.

    R Core Team. R: A language and environment for statistical computing. 2018. https://www.r-project.org/.

  25. 25.

    Landrum MJ, Lee JM, Benson M, Brown GR, Chao C, Chitipiralla S, et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 2018;46:D1062–67.

    CAS  Article  Google Scholar 

  26. 26.

    Freeman PJ, Hart RK, Gretton LJ, Brookes AJ, Dalgleish R. VariantValidator: accurate validation, mapping, and formatting of sequence variation descriptions. Hum Mutat. 2018;39:61–68.

    Article  Google Scholar 

  27. 27.

    Sherry S, Ward M, Kholodov M, Baker J, Phan L, Smigielski E, et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001;29:308–11.

    CAS  Article  Google Scholar 

  28. 28.

    Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: A joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–24.

    Article  Google Scholar 

  29. 29.

    Gray SW, Martins Y, Feuerman LZ, Bernhardt BA, Biesecker BB, Christensen KD, et al. Social and behavioral research in genomic sequencing: approaches from the Clinical Sequencing Exploratory Research Consortium and Measures Working Group. Genet Med. 2014;16:727–35.

    Article  Google Scholar 

  30. 30.

    Marteau TM, Bekker H. The development of a six-item short-form of the state scale of the Spielberger State—Trait Anxiety Inventory (STAI). Br J Clin Psychol. 1992;31:301–6.

    CAS  Article  Google Scholar 

  31. 31.

    Brehaut JC, O’Connor AM, Wood TJ, Hack TF, Siminoff L, Gordon E, et al. Validation of a decision regret scale. Med Decis Mak. 2003;23:281–92.

    Article  Google Scholar 

  32. 32.

    Berkenstadt M, Shiloh S, Barkai G, Katznelson MBM, Goldman B. Perceived personal control (PPC): a new concept in measuring outcome of genetic counseling. Am J Med Genet. 1999;82:53–59.

    CAS  Article  Google Scholar 

  33. 33.

    Szabo C, Masiello A, Ryan JF, Brody LC. The breast cancer information core: database design, structure, and scope. Hum Mutat. 2000;16:123–31.

    CAS  Article  Google Scholar 

  34. 34.

    Tamboom K, Kaasik K, Aršavskaja J, Tekkel M, Lilleorg A, Padrik P, et al. BRCA1 mutations in women with familial or early-onset breast cancer and BRCA2 mutations in familial cancer in Estonia. Hered Cancer Clin Pr. 2010;8:4.

    Article  Google Scholar 

  35. 35.

    Hamel N, Feng BJ, Foretova L, Stoppa-Lyonnet D, Narod SA, Imyanitov E, et al. On the origin and diffusion of BRCA1 c.5266dupC (5382insC) in European populations. Eur J Hum Genet. 2011;19:300–6.

    Article  Google Scholar 

  36. 36.

    Borg Å, Haile RW, Malone KE, Capanu M, Diep A, Törngren T, et al. Characterization of BRCA1 and BRCA2 deleterious mutations and variants of unknown clinical significance in unilateral and bilateral breast cancer: The WECARE study. Hum Mutat 2010;31. https://doi.org/10.1002/humu.21202.

  37. 37.

    Tung NM, Garber JE. BRCA1/2 testing: therapeutic implications for breast cancer management. Br J Cancer. 2018;119:141–52.

    CAS  Article  Google Scholar 

  38. 38.

    Rauscher EA, Dean M, Campbell-Salome G, Barbour JB. “How do we rally around the one who was positive?” Familial uncertainty management in the context of men managing BRCA-related cancer risks. Soc Sci Med. 2019;242:112592.

    Article  Google Scholar 

  39. 39.

    Menko FH, Jeanson KN, Bleiker EMA, Van Tiggelen CWM, Hogervorst FBL, Jacqueline A, et al. The uptake of predictive DNA testing in 40 families with a pathogenic BRCA1/BRCA2 variant. An evaluation of the proband-mediated procedure. Eur J Hum Genet. 2020. https://doi.org/10.1038/s41431-020-0618-8.

  40. 40.

    Menko FH, ter Stege JA, van der Kolk LE, Jeanson KN, Schats W, Moha DA, et al. The uptake of presymptomatic genetic testing in hereditary breast-ovarian cancer and Lynch syndrome: a systematic review of the literature and implications for clinical practice. Fam Cancer. 2019;18:127–35.

    CAS  Article  Google Scholar 

  41. 41.

    Hampel H, Bennett RL, Buchanan A, Pearlman R, Wiesner GL. A practice guideline from the American College of Medical Genetics and Genomics and the National Society of Genetic Counselors: referral indications for cancer predisposition assessment. Genet Med. 2015;17:70–87.

    Article  Google Scholar 

  42. 42.

    Läll K, Lepamets M, Palover M, Esko T, Metspalu A, Tõnisson N, et al. Polygenic prediction of breast cancer: comparison of genetic predictors and implications for risk stratification. BMC Cancer. 2019;19:557.

    Article  Google Scholar 

Download references

Acknowledgements

We express our sincere thanks to the biobank participants and their relatives for participating in the study.

Funding

This research was supported by the European Union through the European Regional Development Fund (project no. 2014-2020.4.01.15-0012 GENTRANSMED), European Union Horizon 2020 (grant no. 810645, no. 654248), Estonian Research Council (PUT736 to NT, PUT PRG555 to NT, IUT20-60, PUT1660 to TE, PUTJD817 to MK, MOBERA15, RITA1/01-42-03).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Neeme Tõnisson.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

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

Verify currency and authenticity via CrossMark

Cite this article

Leitsalu, L., Palover, M., Sikka, T.T. et al. Genotype-first approach to the detection of hereditary breast and ovarian cancer risk, and effects of risk disclosure to biobank participants. Eur J Hum Genet 29, 471–481 (2021). https://doi.org/10.1038/s41431-020-00760-2

Download citation

Search

Quick links