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Breast Cancer Research
Published in: Breast Cancer Research 1/2020

01-12-2020 | Breast Cancer | Research article

Tumor sequencing is useful to refine the analysis of germline variants in unexplained high-risk breast cancer families

Authors: Cédric Van Marcke, Raphaël Helaers, Anne De Leener, Ahmad Merhi, Céline A. Schoonjans, Jérôme Ambroise, Christine Galant, Paul Delrée, Françoise Rothé, Isabelle Bar, Elsa Khoury, Pascal Brouillard, Jean-Luc Canon, Peter Vuylsteke, Jean-Pascal Machiels, Martine Berlière, Nisha Limaye, Miikka Vikkula, François P. Duhoux

Published in: Breast Cancer Research | Issue 1/2020

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Abstract

Background

Multigene panels are routinely used to assess for predisposing germline mutations in families at high breast cancer risk. The number of variants of unknown significance thereby identified increases with the number of sequenced genes. We aimed to determine whether tumor sequencing can help refine the analysis of germline variants based on second somatic genetic events in the same gene.

Methods

Whole-exome sequencing (WES) was performed on whole blood DNA from 70 unrelated breast cancer patients referred for genetic testing and without a BRCA1, BRCA2, TP53, or CHEK2 mutation. Rare variants were retained in a list of 735 genes. WES was performed on matched tumor DNA to identify somatic second hits (copy number alterations (CNAs) or mutations) in the same genes. Distinct methods (among which immunohistochemistry, mutational signatures, homologous recombination deficiency, and tumor mutation burden analyses) were used to further study the role of the variants in tumor development, as appropriate.

Results

Sixty-eight patients (97%) carried at least one germline variant (4.7 ± 2.0 variants per patient). Of the 329 variants, 55 (17%) presented a second hit in paired tumor tissue. Of these, 53 were CNAs, resulting in tumor enrichment (28 variants) or depletion (25 variants) of the germline variant. Eleven patients received variant disclosure, with clinical measures for five of them. Seven variants in breast cancer-predisposing genes were considered not implicated in oncogenesis. One patient presented significant tumor enrichment of a germline variant in the oncogene ERBB2, in vitro expression of which caused downstream signaling pathway activation.

Conclusion

Tumor sequencing is a powerful approach to refine variant interpretation in cancer-predisposing genes in high-risk breast cancer patients. In this series, the strategy provided clinically relevant information for 11 out of 70 patients (16%), adapted to the considered gene and the familial clinical phenotype.
Appendix
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Literature
1.
NCCN. Genetic/Familial high-risk assessment: breast and ovarian (version 3.2019) 2019.
2.
NCCN. Genetic/familial high-risk assessment : colorectal (version 1.2018) 2018.
3.
Lincoln SE, Kobayashi Y, Anderson MJ, Yang S, Desmond AJ, Mills MA, et al. A systematic comparison of traditional and multigene panel testing for hereditary breast and ovarian cancer genes in more than 1000 patients. J Mol Diagn. 2015;17(5):533–44.PubMedCrossRef
4.
Siraj AK, Masoodi T, Bu R, Parvathareddy SK, Al-Badawi IA, Al-Sanea N, et al. Expanding the spectrum of germline variants in cancer. Hum Genet. 2017;136(11–12):1431–44.
5.
6.
van Marcke C, Collard A, Vikkula M, Duhoux FP. Prevalence of pathogenic variants and variants of unknown significance in patients at high risk of breast cancer: a systematic review and meta-analysis of gene-panel data. Crit Rev Oncol Hematol. 2018;132:138–44.PubMedCrossRef
7.
Green RC, Berg JS, Grody WW, Kalia SS, Korf BR, Martin CL, et al. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. 2013;15(7):565–74.PubMedPubMedCentralCrossRef
8.
Lindor NM, Guidugli L, Wang X, Vallee MP, Monteiro AN, Tavtigian S, et al. A review of a multifactorial probability-based model for classification of BRCA1 and BRCA2 variants of uncertain significance (VUS). Hum Mutat. 2012;33(1):8–21.PubMedCrossRef
9.
Moghadasi S, Eccles DM, Devilee P, Vreeswijk MP, van Asperen CJ. Classification and clinical management of variants of uncertain significance in high penetrance cancer predisposition genes. Hum Mutat. 2016;37(4):331–6.PubMedCrossRef
10.
Findlay GM, Daza RM, Martin B, Zhang MD, Leith AP, Gasperini M, et al. Accurate classification of BRCA1 variants with saturation genome editing. Nature. 2018;562(7726):217–22.PubMedPubMedCentralCrossRef
11.
12.
Spurdle AB, Healey S, Devereau A, Hogervorst FB, Monteiro AN, Nathanson KL, et al. ENIGMA--evidence-based network for the interpretation of germline mutant alleles: an international initiative to evaluate risk and clinical significance associated with sequence variation in BRCA1 and BRCA2 genes. Hum Mutat. 2012;33(1):2–7.PubMedCrossRef
13.
14.
Lee AJ, Cunningham AP, Kuchenbaecker KB, Mavaddat N, Easton DF, Antoniou AC, et al. BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface. Br J Cancer. 2014;110(2):535–45.PubMedCrossRef
15.
Zhang J, Walsh MF, Wu G, Edmonson MN, Gruber TA, Easton J, et al. Germline mutations in predisposition genes in pediatric cancer. N Engl J Med. 2015;373(24):2336–46.PubMedPubMedCentralCrossRef
16.
Jian X, Boerwinkle E, Liu X. In silico prediction of splice-altering single nucleotide variants in the human genome. Nucleic Acids Res. 2014;42(22):13534–44.PubMedPubMedCentralCrossRef
17.
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(5):405–24.PubMedPubMedCentralCrossRef
18.
Landrum MJ, Lee JM, Riley GR, Jang W, Rubinstein WS, Church DM, et al. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res. 2014;42(Database issue):D980–5.PubMedCrossRef
19.
Shen R, Seshan VE. FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucleic Acids Res. 2016;44(16):e131.PubMedPubMedCentralCrossRef
20.
Wolff AC, Hammond MEH, Allison KH, Harvey BE, Mangu PB, Bartlett JMS, et al. Human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists Clinical Practice Guideline Focused Update. J Clin Oncol. 2018;36(20):2105–22.PubMedCrossRef
21.
Blokzijl F, Janssen R, van Boxtel R, Cuppen E. MutationalPatterns: comprehensive genome-wide analysis of mutational processes. Genome Med. 2018;10(1):33.PubMedPubMedCentralCrossRef
22.
Maxwell KN, Wubbenhorst B, Wenz BM, De Sloover D, Pluta J, Emery L, et al. BRCA locus-specific loss of heterozygosity in germline BRCA1 and BRCA2 carriers. Nat Commun. 2017;8(1):319.PubMedPubMedCentralCrossRef
23.
Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013;499(7457):214–8.PubMedPubMedCentralCrossRef
24.
Skidmore ZL, Wagner AH, Lesurf R, Campbell KM, Kunisaki J, Griffith OL, et al. GenVisR: genomic visualizations in R. Bioinformatics. 2016;32(19):3012–4.PubMedPubMedCentralCrossRef
25.
Hahne F, Ivanek R. Visualizing genomic data using Gviz and Bioconductor. Methods Mol Biol (Clifton, NJ). 2016;1418:335–51.CrossRef
26.
Zhou X, Edmonson MN, Wilkinson MR, Patel A, Wu G, Liu Y, et al. Exploring genomic alteration in pediatric cancer using ProteinPaint. Nat Genet. 2016;48(1):4–6.PubMedPubMedCentralCrossRef
27.
Vo BT, Li C, Morgan MA, Theurillat I, Finkelstein D, Wright S, et al. Inactivation of Ezh2 Upregulates Gfi1 and drives aggressive Myc-driven group 3 medulloblastoma. Cell Rep. 2017;18(12):2907–17.PubMedPubMedCentralCrossRef
28.
Bose R, Kavuri SM, Searleman AC, Shen W, Shen D, Koboldt DC, et al. Activating HER2 mutations in HER2 gene amplification negative breast cancer. Cancer Discov. 2013;3(2):224–37.PubMedCrossRef
29.
Niu B, Ye K, Zhang Q, Lu C, Xie M, McLellan MD, et al. MSIsensor: microsatellite instability detection using paired tumor-normal sequence data. Bioinformatics. 2014;30(7):1015–6.PubMedCrossRef
30.
Middha S, Zhang L, Nafa K, Jayakumaran G, Wong D, Kim HR, et al. Reliable pan-Cancer microsatellite instability assessment by using targeted next-generation sequencing data. JCO Precis Onco. 2017;1:1–17.
31.
Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature. 2013;500(7463):415–21.PubMedPubMedCentralCrossRef
32.
Angus L, Wilting SM, van Riet J, Smid M, Steenbruggen T, Tjan-Heijnen V, et al. The genomic landscape of 501 metastatic breast cancer patients. San Antonio: San Antonio Breast Cancer Symposium; 2018.
33.
Roberts SA, Lawrence MS, Klimczak LJ, Grimm SA, Fargo D, Stojanov P, et al. An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers. Nat Genet. 2013;45(9):970–6.PubMedPubMedCentralCrossRef
34.
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(7605):47–54.
35.
Plotz G, Casper M, Raedle J, Hinrichsen I, Heckel V, Brieger A, et al. MUTYH gene expression and alternative splicing in controls and polyposis patients. Hum Mutat. 2012;33(7):1067–74.PubMedCrossRef
36.
Viel A, Bruselles A, Meccia E, Fornasarig M, Quaia M, Canzonieri V, et al. A specific mutational signature associated with DNA 8-oxoguanine persistence in MUTYH-defective colorectal cancer. EBioMedicine. 2017;20:39–49.PubMedPubMedCentralCrossRef
37.
38.
de Andrade KC, Frone MN, Wegman-Ostrosky T, Khincha PP, Kim J, Amadou A, et al. Variable population prevalence estimates of germline TP53 variants: a gnomAD-based analysis. Hum Mutat. 2019;40(1):97–105.PubMedCrossRef
39.
Rana HQ, Gelman R, LaDuca H, McFarland R, Dalton E, Thompson J, et al. Differences in TP53 mutation carrier phenotypes emerge from panel-based testing. J Natl Cancer Inst. 2018;110(8):863–70.PubMedCrossRef
40.
41.
Gnarra JR, Tory K, Weng Y, Schmidt L, Wei MH, Li H, et al. Mutations of the VHL tumour suppressor gene in renal carcinoma. Nat Genet. 1994;7(1):85–90.PubMedCrossRef
42.
Lee JEA, Li N, Rowley SM, Cheasley D, Zethoven M, McInerny S, et al. Molecular analysis of PALB2-associated breast cancers. J Pathol. 2018;245(1):53–60.PubMedCrossRef
43.
Renault AL, Mebirouk N, Fuhrmann L, Bataillon G, Cavaciuti E, Le Gal D, et al. Morphology and genomic hallmarks of breast tumours developed by ATM deleterious variant carriers. Breast Cancer Res. 2018;20(1):28.PubMedPubMedCentralCrossRef
44.
Rafnar T, Gudbjartsson DF, Sulem P, Jonasdottir A, Sigurdsson A, Jonasdottir A, et al. Mutations in BRIP1 confer high risk of ovarian cancer. Nat Genet. 2011;43(11):1104–7.PubMedCrossRef
45.
Drost J, van Boxtel R, Blokzijl F, Mizutani T, Sasaki N, Sasselli V, et al. Use of CRISPR-modified human stem cell organoids to study the origin of mutational signatures in cancer. Science. 2017;358(6360):234–8.PubMedPubMedCentralCrossRef
46.
Polak P, Kim J, Braunstein LZ, Karlic R, Haradhavala NJ, Tiao G, et al. A mutational signature reveals alterations underlying deficient homologous recombination repair in breast cancer. Nat Genet. 2017;49(10):1476–86.PubMedCrossRefPubMedCentral
47.
Jonsson P, Bandlamudi C, Cheng ML, Srinivasan P, Chavan SS, Friedman ND, et al. Tumour lineage shapes BRCA-mediated phenotypes. Nature. 2019;571(7766):576–9.PubMedPubMedCentralCrossRef
48.
van Noesel J, van der Ven WH, van Os TA, Kunst PW, Weegenaar J, Reinten RJ, et al. Activating germline R776H mutation in the epidermal growth factor receptor associated with lung cancer with squamous differentiation. J Clin Oncol. 2013;31(10):e161–4.PubMedCrossRef
49.
Ohtsuka K, Ohnishi H, Kurai D, Matsushima S, Morishita Y, Shinonaga M, et al. Familial lung adenocarcinoma caused by the EGFR V843I germ-line mutation. J Clin Oncol. 2011;29(8):e191–2.PubMedCrossRef
50.
Bell DW, Gore I, Okimoto RA, Godin-Heymann N, Sordella R, Mulloy R, et al. Inherited susceptibility to lung cancer may be associated with the T790M drug resistance mutation in EGFR. Nat Genet. 2005;37(12):1315–6.PubMedCrossRef
51.
Pahuja KB, Nguyen TT, Jaiswal BS, Prabhash K, Thaker TM, Senger K, et al. Actionable activating oncogenic ERBB2/HER2 transmembrane and juxtamembrane domain mutations. Cancer Cell. 2018;34(5):792–806 e5.PubMedPubMedCentralCrossRef
52.
Beitsch PD, Whitworth PW, Hughes K, Patel R, Rosen B, Compagnoni G, et al. Underdiagnosis of hereditary breast cancer: are genetic testing guidelines a tool or an obstacle? J Clin Oncol. 2019;37(6):453–60.PubMedCrossRef
53.
Mandelker D, Zhang L, Kemel Y, Stadler ZK, Joseph V, Zehir A, et al. Mutation detection in patients with advanced cancer by universal sequencing of cancer-related genes in tumor and normal DNA vs guideline-based germline testing. JAMA. 2017;318(9):825–35.PubMedPubMedCentralCrossRef
54.
Katki HA, Greene MH, Achatz MI. Testing positive on a multigene panel does not suffice to determine disease risks. J Natl Cancer Inst. 2018;110(8):797–8.PubMedPubMedCentralCrossRef
55.
Lowery MA, Wong W, Jordan EJ, Lee JW, Kemel Y, Vijai J, et al. Prospective evaluation of germline alterations in patients with exocrine pancreatic neoplasms. J Natl Cancer Inst. 2018;110(10):1067–74.PubMedPubMedCentralCrossRef
56.
Metadata
Title
Tumor sequencing is useful to refine the analysis of germline variants in unexplained high-risk breast cancer families
Authors
Cédric Van Marcke
Raphaël Helaers
Anne De Leener
Ahmad Merhi
Céline A. Schoonjans
Jérôme Ambroise
Christine Galant
Paul Delrée
Françoise Rothé
Isabelle Bar
Elsa Khoury
Pascal Brouillard
Jean-Luc Canon
Peter Vuylsteke
Jean-Pascal Machiels
Martine Berlière
Nisha Limaye
Miikka Vikkula
François P. Duhoux
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2020
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-020-01273-y

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