Skip to main content

Advertisement

SpringerLink
Log in

Multigene panel testing in unselected Israeli breast cancer cases: mutational spectrum and use of BRCA1/2 mutation prediction algorithms

  • Clinical trial
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

Background

Studies assessing the contribution of non-BRCA1/2 gene mutations to inherited breast cancer (BC) predisposition consistently reported low (up to 4%) yield. The current study aimed at assessing the spectrum of non-BRCA mutations in unselected Israeli BC cases and the utility of BRCAPRO and Penn II models, as tools for prediction of detecting non-BRCA1/2 mutations in Israeli BC patients who tested negative for the predominant Jewish BRCA1/2 mutations.

Methods

All consecutive Jewish Israeli BC patients at the Sheba Medical center who tested negative for the predominant BRCA1/2 mutations and elected to perform multigene panel testing were included. For each patient probability of BRCA mutation detection was calculated by the Penn II algorithm and the BRCAPRO tool.

Results

Overall, 144 cases were included (median age at diagnosis was 48, range 20–73 years); 48% were Ashkenazim. One patient harbored a non-founder BRCA1 mutation (c.5434C>G; p.P1812A). Pathogenic/likely pathogenic (P/LP) mutations in non-BRCA1/2 genes were detected in additional 14/144 patients, including CHEK2 (n = 5), RAD51D (n = 2), MSH6 (n = 2), and one each in ATM, RET, TP53, NBN, and BAP1. Using a cutoff of 15% probability of BRCA mutation detection, both models accurately predicted the observed carrier rate of non-BRCA mutations.

Conclusions

In unselected Jewish Israeli BC patients, the rate of detecting non-founder BRCA1/2 mutations is low, with CHEK2 mutations detected in 3.4% of cases. BRCA1/2 mutation prediction models may be utilized for selecting patients eligible for further multigene panel testing after exclusion of predominant BRCA1/2 mutations.

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

Similar content being viewed by others

References

  1. Committee on Practice Bulletins–Gynecology, Committee on Genetics, Society of Gynecologic Oncology (2017) Practice Bulletin No 182: Hereditary Breast and Ovarian Cancer Syndrome. Obstet Gynecol 2130(3):e110–e126

    Google Scholar 

  2. NCCN Guidelines for Detection, Prevention, & Risk Reduction. https://www.nccn.org/professionals/physician_gls/#detection. Accessed 1 March 2019

  3. NICE (2013) Familial breast cancer: classification, care and managing breast cancer and related risks in people with a family history of breast cancer. Guidance and Guidelines|NICE. https://www.nice.org.uk/guidance/cg164. Accessed 1 March 2019

  4. Parmigiani G, Berry D, Aguilar O (1998) Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2. Am J Hum Genet 62:145–158

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. The Penn II Risk Model, BRCA 1 and BRCA 2 Mutation Predictor. https://pennmodel2.pmacs.upenn.edu/penn2/index.jsp. Accessed 1 Feb 2019

  6. BRCA Calculator. http://www.myriadpro.com/brca-risk-calculator/calc.html. Accessed 1 Feb 2019

  7. Lee AJ, Cunningham AP, Kuchenbaecker KB, Mavaddat N, Easton DF, Antoniou AC (2014) BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface. Br J Cancer 110:535–545

    Article  CAS  PubMed  Google Scholar 

  8. Tyrer J, Duffy SW, Cuzick J (2004) A breast cancer prediction model incorporating familial and personal risk factors. Stat Med 23:1111–1130

    Article  PubMed  Google Scholar 

  9. Cintolo-Gonzalez JA, Braun D, Blackford AL, Mazzola E, Acar A, Plichta JK et al (2017) Breast cancer risk models: a comprehensive overview of existing models, validation, and clinical applications. Breast Cancer Res Treat 164:263–284

    Article  PubMed  Google Scholar 

  10. Barnes-Kedar I, Bernstein-Molho R, Ginzach N, Hartmajer S, Shapira T, Magal N et al (2018) The yield of full BRCA1/2 genotyping in Israeli high-risk breast/ovarian cancer patients who do not carry the predominant mutations. Breast Cancer Res Treat 172:151–157

    Article  CAS  PubMed  Google Scholar 

  11. Janavičius R (2010) Founder BRCA1/2 mutations in the Europe: implications for hereditary breast-ovarian cancer prevention and control. EPMA J 1:397–412

    Article  PubMed  PubMed Central  Google Scholar 

  12. Bernstein-Molho R, Laitman Y, Schayek H, Reish O, Lotan S, Haim S et al (2018) The yield of targeted genotyping for the recurring mutations in BRCA1/2 in Israel. Breast Cancer Res Treat 167:697–702

    Article  CAS  PubMed  Google Scholar 

  13. Petrucelli N, Mange S, Fulbright JL, Dohany L, Zakalik D, Duquette D (2015) To reflex or not: additional BRCA1/2 testing in Ashkenazi Jewish individuals without founder mutations. J Genet Couns 24:285–293

    Article  PubMed  Google Scholar 

  14. Walsh T, Mandell JB, Norquist BM, Casadei S, Gulsuner S, Lee MK et al (2017) Genetic predisposition to breast cancer due to mutations other than BRCA1 and BRCA2 founder alleles among Ashkenazi Jewish women. JAMA Oncol 3:1647–1653

    Article  PubMed  PubMed Central  Google Scholar 

  15. Tung N, Lin NU, Kidd J, Allen BA, Singh N, Wenstrup RJ et al (2016) Frequency of germline mutations in 25 cancer susceptibility genes in a sequential series of patients with breast cancer. J Clin Oncol 34:1460–1468

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Saam J, Arnell C, Theisen A, Moyes K, Marino I, Roundy KM et al (2015) Patients tested at a laboratory for hereditary cancer syndromes show an overlap for multiple syndromes in their personal and familial cancer histories. Oncology 89:288–293

    Article  CAS  PubMed  Google Scholar 

  17. Espenschied CR, LaDuca H, Li S, McFarland R, Gau C-L, Hampel H (2017) Multigene panel testing provides a new perspective on lynch syndrome. J Clin Oncol 35:2568–2575

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Berry DA, Iversen ES, Gudbjartsson DF, Hiller EH, Garber JE, Peshkin BN et al (2002) BRCAPRO validation, sensitivity of genetic testing of BRCA1/BRCA2, and prevalence of other breast cancer susceptibility genes. J Clin Oncol 20:2701–2712

    Article  CAS  PubMed  Google Scholar 

  19. Foulkes WD, Knoppers BM, Turnbull C (2016) Population genetic testing for cancer susceptibility: founder mutations to genomes. Nat Rev Clin Oncol 13:41–54

    Article  CAS  PubMed  Google Scholar 

  20. Vysotskaia VS, Hogan GJ, Gould GM, Wang X, Robertson AD, Haas KR et al (2017) Development and validation of a 36-gene sequencing assay for hereditary cancer risk assessment. PeerJ 5:e3046

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Lincoln SE, Kobayashi Y, Anderson MJ, Yang S, Desmond AJ, Mills MA et al (2015) A systematic comparison of traditional and multigene panel testing for hereditary breast and ovarian cancer genes in more than 1000 patients. J Mol Diagn 17(5):533–544

    Article  PubMed  Google Scholar 

  22. Woodage T, King SM, Wacholder S, Hartge P, Struewing JP, McAdams M et al (1998) The APC I1307 K allele and cancer risk in a community-based study of Ashkenazi Jews. Nat Genet 20:62–65

    Article  CAS  PubMed  Google Scholar 

  23. Chompret A, Abel A, Stoppa-Lyonnet D, Brugières L, Pagès S, Feunteun J et al (2001) Sensitivity and predictive value of criteria for p53germline mutation screening. J Med Genet 38:43–47

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Yablonski-Peretz T, Paluch-Shimon S, Gutman LS, Kaplan Y, Dvir A, Barnes-Kedar I et al (2016) Screening for germline mutations in breast/ovarian cancer susceptibility genes in high-risk families in Israel. Breast Cancer Res Treat 155:133–138

    Article  CAS  PubMed  Google Scholar 

  25. Daly MB, Pilarski R, Berry M, Buys SS, Farmer M, Friedman S et al (2017) NCCN Guidelines Insights: Genetic/Familial High-Risk Assessment: Breast and Ovarian, Version 2.2017. J Natl Compr Canc Netw 15:9–20

    Article  CAS  PubMed  Google Scholar 

  26. Mateo J, Carreira S, Sandhu S, Miranda S, Mossop H, Perez-Lopez R et al (2015) DNA-repair defects and olaparib in metastatic prostate cancer. N Engl J Med 373(18):1697–1708

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Manchanda R, Patel S, Gordeev VS, Antoniou AC, Smith S, Lee A et al (2018) Cost-effectiveness of population-based BRCA1, BRCA2, RAD51C, RAD51D, BRIP1, PALB2 mutation testing in unselected general population women. JNCI J Natl Cancer Inst 110:714–725

    Article  PubMed  Google Scholar 

  28. Manchanda R, Loggenberg K, Sanderson S, Burnell M, Wardle J, Gessler S et al (2014) Population testing for cancer predisposing BRCA1/BRCA2 mutations in the Ashkenazi-Jewish community: a randomized controlled trial. J Natl Cancer Inst 107(1):379

    PubMed  Google Scholar 

  29. Metcalfe KA, Poll A, Royer R, Llacuachaqui M, Tulman A, Sun P et al (2009) Screening for founder mutations in BRCA1 and BRCA2 in unselected Jewish women. J Clin Oncol 28:387–391

    Article  CAS  PubMed  Google Scholar 

  30. Lieberman S, Tomer A, Ben-Chetrit A, Olsha O, Strano S, Beeri R et al (2017) Population screening for BRCA1/BRCA2 founder mutations in Ashkenazi Jews: proactive recruitment compared with self-referral. Genet Med 19:754–762

    Article  CAS  PubMed  Google Scholar 

  31. Gabai-Kapara E, Lahad A, Kaufman B, Friedman E, Segev S, Renbaum P et al (2014) Population-based screening for breast and ovarian cancer risk due to BRCA1 and BRCA2. Proc Natl Acad Sci USA 111:14205–14210

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Breast Cancer Center, Oncology Institute, Chaim Sheba Medical Center, 52621, Tel-Hashomer, Israel

    Rinat Bernstein-Molho

  2. Community Genetics, Public Health Services, Ministry of Health, Jerusalem, Israel

    Amihood Singer

  3. Susanne Levy Gertner Oncogenetics Unit, The Danek Gertner Institute of Human Genetics, Chaim Sheba Medical Center, 52621, Tel-Hashomer, Israel

    Yael Laitman, Iris Netzer, Shelley Zalmanoviz & Eitan Friedman

  4. Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel

    Rinat Bernstein-Molho & Eitan Friedman

Authors
  1. Rinat Bernstein-Molho
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amihood Singer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yael Laitman
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Iris Netzer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shelley Zalmanoviz
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Eitan Friedman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Eitan Friedman.

Ethics declarations

Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bernstein-Molho, R., Singer, A., Laitman, Y. et al. Multigene panel testing in unselected Israeli breast cancer cases: mutational spectrum and use of BRCA1/2 mutation prediction algorithms. Breast Cancer Res Treat 176, 165–170 (2019). https://doi.org/10.1007/s10549-019-05228-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-019-05228-6

Keywords

Search

Navigation