Advertisement

Clinical interpretation of pathogenic ATM and CHEK2 variants on multigene panel tests: navigating moderate risk

  • Allison H. West
  • Kathleen R. Blazer
  • Jessica Stoll
  • Matthew Jones
  • Caroline M. Weipert
  • Sarah M. Nielsen
  • Sonia S. Kupfer
  • Jeffrey N. Weitzel
  • Olufunmilayo I. Olopade
Original Article
  • 408 Downloads

Abstract

Comprehensive genomic cancer risk assessment (GCRA) helps patients, family members, and providers make informed choices about cancer screening, surgical and chemotherapeutic risk reduction, and genetically targeted cancer therapies. The increasing availability of multigene panel tests for clinical applications allows testing of well-defined high-risk genes, as well as moderate-risk genes, for which the penetrance and spectrum of cancer risk are less well characterized. Moderate-risk genes are defined as genes that, when altered by a pathogenic variant, confer a 2 to fivefold relative risk of cancer. Two such genes included on many comprehensive cancer panels are the DNA repair genes ATM and CHEK2, best known for moderately increased risk of breast cancer development. However, the impact of screening and preventative interventions and spectrum of cancer risk beyond breast cancer associated with ATM and/or CHEK2 variants remain less well characterized. We convened a large, multidisciplinary, cross-sectional panel of GCRA clinicians to review challenging, peer-submitted cases of patients identified with ATM or CHEK2 variants. This paper summarizes the inter-professional case discussion and recommendations generated during the session, the level of concordance with respect to recommendations between the academic and community clinician participants for each case, and potential barriers to implementing recommended care in various practice settings.

Keywords

Cancer genetics ATM CHEK2 Moderate-risk gene Panel test Genomic cancer risk assessment (GCRA) 

Notes

Acknowledgements

Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R13CA206594-01 (PI: O. Olopade) and R25CA171998 (PIs: K. Blazer and J. Weitzel). A. West is supported by the National Cancer Institute of the National Institutes of Health under a Basic Medical Research Training in Oncology Award Number T32CA009566 (PI: O. Olopade). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Compliance with ethical standards

Conflict of interest

Dr. Olufunmilayo Olopade is co-founder of CancerIQ. All co-authors declare that they have no conflict of interest.

Supplementary material

10689_2018_70_MOESM1_ESM.pdf (417 kb)
Cancer Genetics and Genomics Conference syllabus. (PDF 417 KB)
10689_2018_70_MOESM2_ESM.pdf (48 kb)
Participant survey. (PDF 47 KB)

References

  1. 1.
    Hodgson SV (2007) A practical guide to human cancer genetics, 3rd edn. Cambridge University Press, New YorkGoogle Scholar
  2. 2.
    Lindor NM, McMaster ML, Lindor CJ, Greene MH (2008) Concise handbook of familial cancer susceptibility syndromes, 2nd edn. J Natl Cancer Inst Monogr 38:1–93.  https://doi.org/10.1093/jncimonographs/lgn001 Google Scholar
  3. 3.
    Offit K (1998) Clinical cancer genetics: risk counseling and management New York. Wiley Liss, New YorkGoogle Scholar
  4. 4.
    Weitzel JN, Blazer KR, MacDonald DJ, Culver JO, Offit K (2011) Genetics, genomics, and cancer risk assessment: state of the art and future directions in the era of personalized medicine. CA Cancer J Clin 61(5):327–359.  https://doi.org/10.3322/caac.20128 PubMedPubMedCentralGoogle Scholar
  5. 5.
    DeMarco TA, Smith KL, Nusbaum RH, Peshkin BN, Schwartz MD, Isaacs C (2007) Practical aspects of delivering hereditary cancer risk counseling. Semin Oncol 34(5): 369–378.  https://doi.org/10.1053/j.seminoncol.2007.07.003 CrossRefPubMedGoogle Scholar
  6. 6.
    Hampel H, Sweet K, Westman JA, Offit K, Eng C (2004) Referral for cancer genetics consultation: a review and compilation of risk assessment criteria. J Med Genet 41(2):81–91CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    National Comprehensive Cancer Network (NCCN) (2016). Genetic/familial high-risk assessment: breast and ovarian version 2Google Scholar
  8. 8.
    Lee JH, Paull TT (2007) Activation and regulation of ATM kinase activity in response to DNA double-strand breaks. Oncogene 26(56):7741–7748.  https://doi.org/10.1038/sj.onc.1210872 CrossRefPubMedGoogle Scholar
  9. 9.
    Cavaciuti E, Lauge A, Janin N et al (2005) Cancer risk according to type and location of ATM mutation in ataxia-telangiectasia families. Genes Chromosomes Cancer 42(1):1–9.  https://doi.org/10.1002/gcc.20101 CrossRefPubMedGoogle Scholar
  10. 10.
    Renwick A, Thompson D, Seal S et al (2006) ATM mutations that cause ataxia-telangiectasia are breast cancer susceptibility alleles. Nat Genet 38(8):873–875.  https://doi.org/10.1038/ng1837 CrossRefPubMedGoogle Scholar
  11. 11.
    Thompson D, Duedal S, Kirner J et al. (2005) Cancer risks and mortality in heterozygous ATM mutation carriers. J Natl Cancer Inst 97(11):813–822.  https://doi.org/10.1093/jnci/dji141 CrossRefPubMedGoogle Scholar
  12. 12.
    Easton DF, Pharoah PD, Antoniou AC et al (2015) Gene-panel sequencing and the prediction of breast-cancer risk. New Engl J Med 372(23):2243–2257.  https://doi.org/10.1056/NEJMsr1501341 CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Tung N, Lin NU, Kidd J 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(13):1460–1468.  https://doi.org/10.1200/jco.2015.65.0747 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    National Comprehensive Cancer Network (NCCN) (2015). Genetic/familial high-risk assessment: colorectal. Version 2Google Scholar
  15. 15.
    Meijers-Heijboer H, van den Ouweland A, Klijn J et al. (2002) Low-penetrance susceptibility to breast cancer due to CHEK2(*)1100delC in noncarriers of BRCA1 or BRCA2 mutations. Nat Genet 31(1):55–59.  https://doi.org/10.1038/ng879 CrossRefPubMedGoogle Scholar
  16. 16.
    Lee SB, Kim SH, Bell DW et al (2001) Destabilization of CHK2 by a missense mutation associated with Li-Fraumeni syndrome. Cancer Res 61(22):8062–8067PubMedGoogle Scholar
  17. 17.
    Vahteristo P, Bartkova J, Eerola H et al (2002) A CHEK2 genetic variant contributing to a substantial fraction of familial breast cancer. Am J Hum Genet 71(2):432–438.  https://doi.org/10.1086/341943 CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Suchy J, Cybulski C, Wokolorczyk D et al (2010) CHEK2 mutations and HNPCC-related colorectal cancer. Int J Cancer 126(12):3005–3009.  https://doi.org/10.1002/ijc.25003 PubMedGoogle Scholar
  19. 19.
    Cybulski C, Gorski B, Huzarski T et al (2004) CHEK2 is a multiorgan cancer susceptibility gene. Am J Hum Genet 75(6):1131–1135.  https://doi.org/10.1086/426403 CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Gronwald J, Cybulski C, Piesiak W et al (2009) Cancer risks in first-degree relatives of CHEK2 mutation carriers: effects of mutation type and cancer site in proband. Br J Cancer 100(9):1508–1512.  https://doi.org/10.1038/sj.bjc.6605038 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Tung N, Domchek SM, Stadler Z et al (2016) Counselling framework for moderate-penetrance cancer-susceptibility mutations. Nat Rev Clin Oncol 13(9):581–588.  https://doi.org/10.1038/nrclinonc.2016.90 CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Bell DW, Kim SH, Godwin AK et al (2007) Genetic and functional analysis of CHEK2 (CHK2) variants in multiethnic cohorts. Int J Cancer 121(12):2661–2667.  https://doi.org/10.1002/ijc.23026 CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Couch FJ, Shimelis H, Hu C et al (2017) Associations between cancer predisposition testing panel genes and breast cancer. JAMA Oncol.  https://doi.org/10.1001/jamaoncol.2017.0424 PubMedGoogle Scholar
  24. 24.
    Kapoor NS, Curcio LD, Blakemore CA et al (2015) Multigene panel testing detects equal rates of pathogenic BRCA1/2 mutations and has a higher diagnostic yield compared to limited BRCA1/2 analysis alone in patients at risk for hereditary breast cancer. Ann Surg Oncol 22(10):3282–3288.  https://doi.org/10.1245/s10434-015-4754-2 CrossRefPubMedGoogle Scholar
  25. 25.
    Blazer KR, MacDonald DJ, Ricker C, Sand S, Uman GC, Weitzel JN (2005) Outcomes from intensive training in genetic cancer risk counseling for clinicians. Genet Med 7(1):40–47CrossRefPubMedGoogle Scholar
  26. 26.
    Blazer KR, Macdonald DJ, Culver JO et al. (2011) Personalized cancer genetics training for personalized medicine: improving community-based healthcare through a genetically literate workforce. Genet Med 13(9):832–840CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Microsoft Excel (2013) Microsoft, RedmondGoogle Scholar
  28. 28.
    Creswell JW (2003) Mixed Methods procedures. Research design qualitative, quantitative, and mixed method approaches, 2nd edn. Sage, Thousand Oaks, pp 208–225Google Scholar
  29. 29.
    Claus EB, Risch N, Thompson WD (1994) Autosomal dominant inheritance of early-onset breast cancer. Implications for risk prediction. Cancer 73(3):643–651CrossRefPubMedGoogle Scholar
  30. 30.
    Fisher B, Costantino JP, Wickerham DL et al (1998) Tamoxifen for prevention of breast cancer: report of the National Surgical Adjuvant Breast and Bowel Project P-1 Study. J Natl Cancer Inst 90(18):1371–1388CrossRefPubMedGoogle Scholar
  31. 31.
    National Comprehensive Cancer Network (NCCN) (2017) Breast Cancer Screening and Diagnosis. Version 1Google Scholar
  32. 32.
    Roberts NJ, Jiao Y, Yu J et al. (2012) ATM mutations in patients with hereditary pancreatic cancer. Cancer Discov 2(1):41–46.  https://doi.org/10.1158/2159-8290.cd-11-0194 CrossRefPubMedGoogle Scholar
  33. 33.
    Petersen GM (2016) Familial pancreatic cancer. Semin Oncol 43(5):548–553.  https://doi.org/10.1053/j.seminoncol.2016.09.002 CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Canto MI, Harinck F, Hruban RH et al. (2013) International Cancer of the Pancreas Screening (CAPS) Consortium summit on the management of patients with increased risk for familial pancreatic cancer. Gut 62(3):339–347.  https://doi.org/10.1136/gutjnl-2012-303108 CrossRefPubMedGoogle Scholar
  35. 35.
    Bartsch DK, Slater EP, Carrato A et al (2016) Refinement of screening for familial pancreatic cancer. Gut 65(8):1314–1321.  https://doi.org/10.1136/gutjnl-2015-311098 CrossRefPubMedGoogle Scholar
  36. 36.
    Fletcher O, Johnson N, dos Santos Silva I et al (2010) Missense variants in ATM in 26,101 breast cancer cases and 29,842 controls. Cancer Epidemiol Biomarkers Prev 19(9):2143–2151.  https://doi.org/10.1158/1055-9965.epi-10-0374 CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Bretsky P, Haiman CA, Gilad S et al (2003) The relationship between twenty missense ATM variants and breast cancer risk: the Multiethnic Cohort. Cancer Epidemiol Biomarkers Prev 12(8):733–738PubMedGoogle Scholar
  38. 38.
    Bernstein JL, Haile RW, Stovall M et al. (2010) Radiation exposure, the ATM Gene, and contralateral breast cancer in the women’s environmental cancer and radiation epidemiology study. J Natl Cancer Inst 102(7):475–483.  https://doi.org/10.1093/jnci/djq055 CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    National Comprehensive Cancer Network (NCCN) (2018). Genetic/familial high-risk assessment: breast and ovarian Version 1Google Scholar
  40. 40.
    Landrum MJ, Lee JM, Benson M, Brown G, Chao C, Chitipiralla S, Gu B, Hart J, Hoffman D, Hoover J, Jang W, Katz K, Ovetsky M, Riley G, Sethi A, Tully R, Villamarin-Salomon R, Rubinstein W, Maglott DR (2015) ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res 44(D1):D862–D868CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    National Comprehensive Cancer Network (NCCN) (2017) Genetic/familial high-risk assessment: colorectal Version 3Google Scholar
  42. 42.
    Boughey JC, Attai DJ, Chen SL et al (2016) contralateral prophylactic mastectomy (CPM) consensus statement from the American Society of Breast Surgeons: data on CPM outcomes and risks. Ann Surg Oncol 23(10):3100–3105.  https://doi.org/10.1245/s10434-016-5443-5 CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Hunt KK, Euhus DM, Boughey JC et al. (2017) Society of Surgical Oncology Breast Disease Working Group statement on prophylactic (risk-reducing) mastectomy. Ann Surg Oncol 24(2):375–397.  https://doi.org/10.1245/s10434-016-5688-z CrossRefPubMedGoogle Scholar
  44. 44.
    Giuliano AE, Boolbol S, Degnim A, Kuerer H, Leitch AM, Morrow M (2007) Society of Surgical Oncology: position statement on prophylactic mastectomy. Approved by the Society of Surgical Oncology Executive Council, March 2007. Ann Surg Oncol 14(9):2425–2427.  https://doi.org/10.1245/s10434-007-9447-z CrossRefPubMedGoogle Scholar
  45. 45.
    Mai PL, Lagos VI, Palomares MR, Weitzel JN (2008) Contralateral risk-reducing mastectomy in young breast cancer patients with and without genetic cancer risk assessment. Ann Surg Oncol 15(12):3415–3421.  https://doi.org/10.1245/s10434-008-0160-3 CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Rebbeck TR, Friebel T, Lynch HT et al (2004) Bilateral prophylactic mastectomy reduces breast cancer risk in BRCA1 and BRCA2 mutation carriers: the PROSE Study Group. J Clin Oncol 22(6):1055–1062.  https://doi.org/10.1200/jco.2004.04.188 CrossRefPubMedGoogle Scholar
  47. 47.
    Brandberg Y, Sandelin K, Erikson S et al (2008) Psychological reactions, quality of life, and body image after bilateral prophylactic mastectomy in women at high risk for breast cancer: a prospective 1-year follow-up study. J Clin Oncol 26(24):3943–3949.  https://doi.org/10.1200/jco.2007.13.9568 CrossRefPubMedGoogle Scholar
  48. 48.
    Hartmann LC, Schaid DJ, Woods JE et al (1999) Efficacy of bilateral prophylactic mastectomy in women with a family history of breast cancer. New Engl J Med 340(2):77–84.  https://doi.org/10.1056/nejm199901143400201 CrossRefPubMedGoogle Scholar
  49. 49.
    den Heijer M, Seynaeve C, Timman R et al (2012) Body image and psychological distress after prophylactic mastectomy and breast reconstruction in genetically predisposed women: a prospective long-term follow-up study. Eur J Cancer 48(9):1263-8.  https://doi.org/10.1016/j.ejca.2011.10.020 Google Scholar
  50. 50.
    National Institutes of Health (2018) All of Us Research ProgramGoogle Scholar
  51. 51.
    Tyrer J, Duffy SW, Cuzick J (2004) A breast cancer prediction model incorporating familial and personal risk factors. Stat Med 23(7):1111–1130.  https://doi.org/10.1002/sim.1668 CrossRefPubMedGoogle Scholar
  52. 52.
    Gail MH, Brinton LA, Byar DP et al (1989) Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst 81(24):1879–1886CrossRefPubMedGoogle Scholar
  53. 53.
    Chowdhury S, Dent T, Pashayan N et al. (2013) Incorporating genomics into breast and prostate cancer screening: assessing the implications. Genet Med 15(6):423–432.  https://doi.org/10.1038/gim.2012.167 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  • Allison H. West
    • 1
  • Kathleen R. Blazer
    • 2
  • Jessica Stoll
    • 3
    • 4
  • Matthew Jones
    • 5
  • Caroline M. Weipert
    • 3
  • Sarah M. Nielsen
    • 3
  • Sonia S. Kupfer
    • 3
    • 5
  • Jeffrey N. Weitzel
    • 2
  • Olufunmilayo I. Olopade
    • 1
    • 3
  1. 1.Section of Hematology/OncologyThe University of Chicago Comprehensive Cancer CenterChicagoUSA
  2. 2.Division of Clinical Cancer GenomicsCity of Hope Comprehensive Cancer Center and Beckman Research InstituteDuarteUSA
  3. 3.Department of Medicine, Center for Clinical Cancer GeneticsThe University of ChicagoChicagoUSA
  4. 4.Department of Medicine, Section of Gastroenterology, Hepatology and NutritionUniversity of ChicagoChicagoUSA
  5. 5.Pritzker School of MedicineUniversity of ChicagoChicagoUSA

Personalised recommendations