Skip to main content

Advertisement

Log in

Potentially pathogenic germline CHEK2 c.319+2T>A among multiple early-onset cancer families

  • Original Article
  • Published:
Familial Cancer Aims and scope Submit manuscript

Abstract

To study the potential contribution of genes other than BRCA1/2, PTEN, and TP53 to the biological and clinical characteristics of multiple early-onset cancers in Norwegian families, including early-onset breast cancer, Cowden-like and Li-Fraumeni-like syndromes (BC, CSL and LFL, respectively). The Hereditary Cancer Biobank from the Norwegian Radium Hospital was used to identify early-onset BC, CSL or LFL for whom no pathogenic variants in BRCA1/2, PTEN, or TP53 had been found in routine diagnostic DNA sequencing. Forty-four cancer susceptibility genes were selected and analyzed by our in-house designed TruSeq amplicon-based assay for targeted sequencing. Protein- and RNA splicing-dedicated in silico analyses were performed for all variants of unknown significance (VUS). Variants predicted as the more likely to affect splicing were experimentally analyzed by minigene assay. We identified a CSL individual carrying a variant in CHEK2 (c.319+2T>A, IVS2), here considered as likely pathogenic. Out of the five VUS (BRCA2, CDH1, CHEK2, MAP3K1, NOTCH3) tested in the minigene splicing assay, only NOTCH3 c.14090C>T (p.Ser497Leu) showed a significant effect on RNA splicing, notably by inducing partial skipping of exon 9. Among 13 early-onset BC, CSL and LFL patients, gene panel sequencing identified a potentially pathogenic variant in CHEK2 that affects a canonical RNA splicing signal. Our study provides new information on genetic loci that may affect the risk of developing cancer in these patients and their families, demonstrating that genes presently not routinely tested in molecular diagnostic settings may be important for capturing cancer predisposition in these families.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Abbreviations

ACMG:

American College of Medical Genetics and Genomics

BC:

Breast cancer

CS:

Cowden syndrome

CRC:

Colorectal cancer

CSL:

Cowden syndrome like

LF:

Li-Fraumeni syndrome

LFL:

Li-Fraumeni like syndrome

MMR:

Mismatch repair genes

NGS:

Next generation sequencing

SNP:

Single nucleotide polymorphism

SNVs:

Single-nucleotide variants

VUS:

Variants of unclassified significance

WT:

Wild type

References

  1. Kurian AW, Hare EE, Mills MA et al (2014) Clinical evaluation of a multiple-gene sequencing panel for hereditary cancer risk assessment. J Clin Oncol 32(19):2001–2009. doi:10.1200/JCO.2013.53.6607

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Hegde M, Ferber M, Mao R et al (2014) ACMG technical standards and guidelines for genetic testing for inherited colorectal cancer (lynch syndrome, familial adenomatous polyposis, and MYH-associated polyposis). Genet Med 16(1):101–116. doi:10.1038/gim.2013.166

    Article  CAS  PubMed  Google Scholar 

  3. Richards S, Aziz N, Bale S et al (2015) 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 17(5):405–424. doi:10.1038/gim.2015.30

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kleinberger J, Maloney KA, Pollin TI, Jeng LJ (2016) An openly available online tool for implementing the ACMG/AMP standards and guidelines for the interpretation of sequence variants. Genet Med 18(11):1165. doi:10.1038/gim.2016.13

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Amendola LM, Jarvik GP, Leo MC et al (2016) Performance of ACMG-AMP variant-interpretation guidelines among nine laboratories in the clinical sequencing exploratory research consortium (vol 98, pg 1067, 2016). Am J Hum Genet 99(1):247. doi:10.1016/j.ajhg.2016.06.001

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Maxwell KN, Hart SN, Vijai J et al (2016) Evaluation of ACMG-guideline-based variant classification of cancer susceptibility and non-cancer-associated genes in families affected by breast cancer. Am J Hum Genet 98(5):801–817. doi:10.1016/j.ajhg.2016.02.024

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Park KS, Cho EY, Nam SJ, Ki CS, Kim JW (2016) Comparative analysis of BRCA1 and BRCA2 variants of uncertain significance in patients with breast cancer: a multifactorial probability-based model versus ACMG standards and guidelines for interpreting sequence variants. Genet Med 18(12):1250–1257. doi:10.1038/gim.2016.39

    Article  CAS  PubMed  Google Scholar 

  8. Cybulski C, Nazarali S, Narod SA (2014) Multiple primary cancers as a guide to heritability. Int J Cancer 135(8):1756–1763. doi:10.1002/ijc.28988

    Article  CAS  PubMed  Google Scholar 

  9. Malone KE, Daling JR, Thompson JD, O’Brien CA, Francisco LV, Ostrander EA (1998) BRCA1 mutations and breast cancer in the general population - Analyses in women before age 35 years and in women before age 45 years with first-degree family history. Jama 279(12):922–929 doi:10.1001/jama.279.12.922

    Article  CAS  PubMed  Google Scholar 

  10. Peto J, Collins N, Barfoot R et al (1999) Prevalence of BRCA1 and BRCA2 gene mutations in patients with early-onset breast cancer. J Natl Cancer Inst 91(11):943–949

    Article  CAS  PubMed  Google Scholar 

  11. Loizidou M, Marcou Y, Anastasiadou V, Newbold R, Hadjisavvas A, Kyriacou K (2007) Contribution of BRCA1 and BRCA2 germline mutations to the incidence of early-onset breast cancer in Cyprus. Clin Genet 71(2):165–170. doi:10.1111/j.1399-0004.2007.00747.x

    Article  CAS  PubMed  Google Scholar 

  12. Moller P, Hagen AI, Apold J et al (2007) Genetic epidemiology of BRCA mutations—family history detects less than 50% of the mutation carriers. Eur J Cancer 43(11):1713–1717. doi:10.1016/j.ejca.2007.04.023

    Article  PubMed  Google Scholar 

  13. Pradella LM, Evangelisti C, Ligorio C et al (2014) A novel deleterious PTEN mutation in a patient with early-onset bilateral breast cancer. Bmc. Cancer 14:70. doi:10.1186/1471-2407-14-70

    PubMed  PubMed Central  Google Scholar 

  14. Moller P, Stormorken A, Holmen MM, Hagen AI, Vabo A, Maehle L (2014) The clinical utility of genetic testing in breast cancer kindreds: a prospective study in families without a demonstrable BRCA mutation. Breast Cancer Res Treat 144(3):607–614. doi:10.1007/s10549-014-2902-1

    Article  PubMed  PubMed Central  Google Scholar 

  15. Mavaddat N, Peock S, Frost D et al (2013) Cancer risks for BRCA1 and BRCA2 mutation carriers: results from prospective analysis of EMBRACE. J Natl Cancer Inst 105(11):812–822. doi:10.1093/jnci/djt095

    Article  CAS  PubMed  Google Scholar 

  16. Wu CC, Shete S, Amos CI, Strong LC (2006) Joint effects of germ-line p53 mutation and sex on cancer risk in Li-Fraumeni syndrome. Cancer Res 66(16):8287–8292. doi:10.1158/0008-5472.Can-05-4247

    Article  CAS  PubMed  Google Scholar 

  17. Pharoah PDP, Guilford P, Caldas C, Consortiu IGCL (2001) Incidence of gastric cancer and breast cancer in CDH1 (E-cadherin) mutation carriers from hereditary diffuse gastric cancer families. Gastroenterology 121(6):1348–1353. doi:10.1053/gast.2001.29611

    Article  CAS  PubMed  Google Scholar 

  18. Hearle N, Schumacher V, Menko FH et al (2006) Frequency and spectrum of cancers in the Peutz-Jeghers syndrome. Clin Cancer Res 12(10):3209–3215. doi:10.1158/1078-0432.Ccr-06-0083

    Article  CAS  PubMed  Google Scholar 

  19. Bubien V, Bonnet F, Brouste V et al (2013) High cumulative risks of cancer in patients with PTEN hamartoma tumour syndrome. J Med Genet 50(4):255–263. doi:10.1136/jmedgenet-2012-101339

    Article  CAS  PubMed  Google Scholar 

  20. Rustad CF, Bjornslett M, Heimdal KR, Maehle L, Apold J, Moller P (2006) Germline PTEN mutations are rare and highly penetrant. Hered Cancer Clin Pract 4(4):177–185. doi:10.1186/1897-4287-4-4-177

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Aloraifi F, McCartan D, McDevitt T, Green AJ, Bracken A, Geraghty J (2015) Protein-truncating variants in moderate-risk breast cancer susceptibility genes: a meta-analysis of high-risk case-control screening studies. Cancer Genet 208(9):455–463. doi:10.1016/j.cancergen.2015.06.001

    Article  CAS  PubMed  Google Scholar 

  22. Antoniou AC, Casadei S, Heikkinen T et al (2014) Breast-cancer risk in families with mutations in PALB2. N Engl J Med 371(6):497–506. doi:10.1056/NEJMoa1400382

    Article  PubMed  PubMed Central  Google Scholar 

  23. Hobert JA, Eng C (2009) PTEN hamartoma tumor syndrome: an overview. Genet Med 11(10):687–694. doi:10.1097/GIM.0b013e3181ac9aea

    Article  CAS  PubMed  Google Scholar 

  24. Daly MB, Axilbund JE, Buys S et al (2010) Genetic/familial high-risk assessment: breast and ovarian. J Natl Compr Canc Netw 8(5):562–594

    Article  CAS  PubMed  Google Scholar 

  25. Tan MH, Mester J, Peterson C et al (2011) A clinical scoring system for selection of patients for PTEN mutation testing is proposed on the basis of a prospective study of 3042 probands. Am J Hum Genet 88(1):42–56. doi:10.1016/j.ajhg.2010.11.013

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Ngeow J, Sesock K, Eng C (2015) Breast cancer risk and clinical implications for germline PTEN mutation carriers. Breast Cancer Res Treat. doi:10.1007/s10549-015-3665-z

    PubMed  Google Scholar 

  27. Mester J, Eng C (2015) Cowden syndrome: recognizing and managing a not-so-rare hereditary cancer syndrome. J Surg Oncol 111(1):125–130. doi:10.1002/jso.23735

    Article  PubMed  Google Scholar 

  28. Birch JM, Hartley AL, Tricker KJ et al (1994) Prevalence and diversity of constitutional mutations in the P53 Gene among 21 Li-Fraumeni families. Cancer Res 54(5):1298–1304

    CAS  PubMed  Google Scholar 

  29. Malkin D, Li FP, Strong LC et al (1990) Germ line p53 mutations in a familial syndrome of breast cancer, sarcomas, and other neoplasms. Science 250(4985):1233–1238

    Article  CAS  PubMed  Google Scholar 

  30. Srivastava S, Zou ZQ, Pirollo K, Blattner W, Chang EH (1990) Germ-line transmission of a mutated p53 gene in a cancer-prone family with Li-Fraumeni syndrome. Nature 348(6303):747–749. doi:10.1038/348747a0

    Article  CAS  PubMed  Google Scholar 

  31. Varley JM (2003) Germline TP53 mutations and Li-Fraumeni syndrome. Hum Mutat 21(3):313–320. doi:10.1002/humu.10185

    Article  CAS  PubMed  Google Scholar 

  32. Olivier M, Eeles R, Hollstein M, Khan MA, Harris CC, Hainaut P (2002) The IARC TP53 database: new online mutation analysis and recommendations to users. Hum Mutat 19(6):607–614. doi:10.1002/humu.10081

    Article  CAS  PubMed  Google Scholar 

  33. Li L, Chen HC, Liu LX (2009) Sequence alignment algorithm in similarity measurement. Int Forum Info Technol Appl Proc 2009 1:453–456 doi:10.1109/Ifita.2009.119

    Google Scholar 

  34. McKenna A, Hanna M, Banks E et al (2010) The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20(9):1297–1303. doi:10.1101/gr.107524.110

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Wang K, Li M, Hakonarson H (2010) ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucl Acids Res 38(16):e164. doi:10.1093/nar/gkq603

    Article  PubMed  PubMed Central  Google Scholar 

  36. Sherry ST, Ward MH, Kholodov M et al (2001) dbSNP: the NCBI database of genetic variation. Nucl Acids Res 29(1):308–311

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Genomes Project C, Auton A, Brooks LD et al (2015) A global reference for human genetic variation. Nature 526(7571):68–74. doi:10.1038/nature15393

    Article  Google Scholar 

  38. Lek M, Karczewski KJ, Minikel EV et al (2016) Analysis of protein-coding genetic variation in 60,706 humans. Nature 536(7616):285–291. doi:10.1038/nature19057

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Landrum MJ, Lee JM, Riley GR et al (2014) ClinVar: public archive of relationships among sequence variation and human phenotype. Nucl Acids Res 42(D1):D980–D985. doi:10.1093/nar/gkt1113

    Article  CAS  PubMed  Google Scholar 

  40. Apweiler R, Bairoch A, Wu CH et al (2004) UniProt: the Universal Protein knowledgebase. Nucl Acids Res 32:D115–D119. doi:10.1093/nar/gkh131

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Finn RD, Bateman A, Clements J et al (2014) Pfam: the protein families database. Nucl Acids Res 42(D1):D222–D230. doi:10.1093/nar/gkt1223

    Article  CAS  PubMed  Google Scholar 

  42. den Dunnen JT, Antonarakis SE (2000) Mutation nomenclature extensions and suggestions to describe complex mutations: A discussion. Hum Mutat 15(1):7–12

    Article  CAS  PubMed  Google Scholar 

  43. Thompson BA, Spurdle AB, Plazzer JP et al (2014) Application of a 5-tiered scheme for standardized classification of 2,360 unique mismatch repair gene variants in the InSiGHT locus-specific database. Nat Genet 46(2):107–115. doi:10.1038/ng.2854

    Article  CAS  PubMed  Google Scholar 

  44. Houdayer C, Caux-Moncoutier V, Krieger S et al (2012) Guidelines for splicing analysis in molecular diagnosis derived from a set of 327 combined in silico/in vitro studies on BRCA1 and BRCA2 variants. Hum Mutat 33(8):1228–1238. doi:10.1002/humu.22101

    Article  CAS  PubMed  Google Scholar 

  45. Di Giacomo D, Gaildrat P, Abuli A et al (2013) Functional analysis of a large set of BRCA2 exon 7 variants highlights the predictive value of hexamer scores in detecting alterations of exonic splicing regulatory elements. Hum Mutat 34(11):1547–1557. doi:10.1002/humu.22428

    Article  CAS  PubMed  Google Scholar 

  46. Erkelenz S, Hillebrand F, Widera M et al (2015) Balanced splicing at the Tat-specific HIV-1 3’ss A3 is critical for HIV-1 replication. Retrovirology 12:29. doi:10.1186/s12977-015-0154-8

    Article  PubMed  PubMed Central  Google Scholar 

  47. Xiong HY, Alipanahi B, Lee LJ et al (2015) The human splicing code reveals new insights into the genetic determinants of disease. Science 347(6218):1254806. doi:10.1126/science.1254806

    Article  PubMed  Google Scholar 

  48. Soukarieh O, Gaildrat P, Hamieh M et al (2016) Exonic splicing mutations are more prevalent than currently estimated and can be predicted by using in silico tools. PLoS Genet 12(1):e1005756. doi:10.1371/journal.pgen.1005756

    Article  PubMed  PubMed Central  Google Scholar 

  49. Tavtigian SV, Deffenbaugh AM, Yin L et al (2006) Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eight recurrent substitutions as neutral. J Med Genet 43(4):295–305. doi:10.1136/jmg.2005.033878

    Article  CAS  PubMed  Google Scholar 

  50. Kumar P, Henikoff S, Ng PC (2009) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 4(7):1073–1082. doi:10.1038/nprot.2009.86

    Article  CAS  PubMed  Google Scholar 

  51. Stone EA, Sidow A (2005) Physicochemical constraint violation by missense substitutions mediates impairment of protein function and disease severity. Genome Res 15(7):978–986. doi:10.1101/gr.3804205

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Adzhubei IA, Schmidt S, Peshkin L et al (2010) A method and server for predicting damaging missense mutations. Nat Methods 7(4):248–249. doi:10.1038/nmeth0410-248

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Schwarz JM, Cooper DN, Schuelke M, Seelow D (2014) MutationTaster2: mutation prediction for the deep-sequencing age. Nat Methods 11(4):361–362. doi:10.1038/nmeth.2890

    Article  CAS  PubMed  Google Scholar 

  54. Gaildrat P, Killian A, Martins A, Tournier I, Frebourg T, Tosi M (2010) Use of splicing reporter minigene assay to evaluate the effect on splicing of unclassified genetic variants. Methods Mol Biol 653:249–257. doi:10.1007/978-1-60761-759-4$415

    Article  CAS  PubMed  Google Scholar 

  55. Landrum MJ, Lee JM, Benson M et al (2016) ClinVar: public archive of interpretations of clinically relevant variants. Nucl Acids Res 44(D1):D862–D868. doi:10.1093/nar/gkv1222

    Article  CAS  PubMed  Google Scholar 

  56. Kalia SS, Adelman K, Bale SJ et al (2017) Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med 19(2):249–255. doi:10.1038/gim.2016.190

    Article  PubMed  Google Scholar 

  57. Eng C (2000) Will the real Cowden syndrome please stand up: revised diagnostic criteria. J Med Genet 37(11):828–830

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Ngeow J, Liu C, Zhou K, Frick KD, Matchar DB, Eng C (2015) Detecting germline PTEN mutations among at-risk patients with cancer: an age- and sex-specific cost-effectiveness analysis. J Clin Oncol 33(23):2537–2581. doi:10.1200/Jco.2014.60.3456

    Article  PubMed  PubMed Central  Google Scholar 

  59. Hamblin A, Wordsworth S, Fermont JM et al (2017) Clinical applicability and cost of a 46-gene panel for genomic analysis of solid tumours: retrospective validation and prospective audit in the UK National Health Service. PLoS Med 14(2):e1002230. doi:10.1371/journal.pmed.1002230

    Article  PubMed  PubMed Central  Google Scholar 

  60. Pinto P, Paulo P, Santos C et al (2016) Implementation of next-generation sequencing for molecular diagnosis of hereditary breast and ovarian cancer highlights its genetic heterogeneity. Breast Cancer Res Treat 159(2):245–256. doi:10.1007/s10549-016-3948-z

    Article  CAS  PubMed  Google Scholar 

  61. Yadav S, Fulbright J, Dreyfuss H et al (2015) Outcomes of retesting BRCA-negative patients using multigene panels. J Clin Oncol 33(Suppl 28):23

  62. Yurgelun MB, Kulke MH, Fuchs CS et al (2017) Cancer susceptibility gene mutations in individuals with colorectal cancer. J Clin Oncol. doi:10.1200/JCO.2016.71.0012

    Google Scholar 

  63. Lincoln SE, Kobayashi Y, Anderson MJ 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. doi:10.1016/j.jmoldx.2015.04.009

    Article  PubMed  Google Scholar 

  64. Antoniou AC, Foulkes WD, Tischkowitz M (2014) Breast-cancer risk in families with mutations in PALB2 reply. New Engl J Med 371(17):1651–1652

    PubMed  Google Scholar 

  65. Krepischi AC, Pearson PL, Rosenberg C (2012) Germline copy number variations and cancer predisposition. Future Oncol 8(4):441–450. doi:10.2217/fon.12.34

    Article  CAS  PubMed  Google Scholar 

  66. Villacis RA, Basso TR, Canto LM et al (2017) Rare germline alterations in cancer-related genes associated with the risk of multiple primary tumor development. J Mol Med. doi:10.1007/s00109-017-1507-7

    PubMed  Google Scholar 

  67. Villacis RA, Miranda PM, Gomy I et al (2016) Contribution of rare germline copy number variations and common susceptibility loci in Lynch syndrome patients negative for mutations in the mismatch repair genes. Int J Cancer 138(8):1928–1935. doi:10.1002/ijc.29948

    Article  CAS  PubMed  Google Scholar 

  68. O’Keefe C, McDevitt MA, Maciejewski JP (2010) Copy neutral loss of heterozygosity: a novel chromosomal lesion in myeloid malignancies. Blood 115(14):2731–2739. doi:10.1182/blood-2009-10-201848

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank the included families for their participation and contribution to this study.

Funding

This work was supported by the Radium Hospital Foundation (Oslo, Norway), Helse Sør-Øst (Norway), the French Association Recherche contre le Cancer (ARC), the Groupement des Entreprises Françaises dans la Lutte contre le Cancer (Gefluc), the Association Nationale de la Recherche et de la Technologie (ANRT, CIFRE PhD fellowship to H.T.) and by the OpenHealth Institute.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mev Dominguez-Valentin.

Ethics declarations

Conflict of interests

The authors declare that they have no competing interests.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 226 KB)

Supplementary material 2 (DOCX 16 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dominguez-Valentin, M., Nakken, S., Tubeuf, H. et al. Potentially pathogenic germline CHEK2 c.319+2T>A among multiple early-onset cancer families. Familial Cancer 17, 141–153 (2018). https://doi.org/10.1007/s10689-017-0011-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10689-017-0011-0

Keywords

Navigation