Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
Breast Cancer Research
Published in: Breast Cancer Research 1/2017

Open Access 01-12-2017 | Research article

A knowledge-based framework for the discovery of cancer-predisposing variants using large-scale sequencing breast cancer data

Authors: Giorgio E. M. Melloni, Luca Mazzarella, Loris Bernard, Margherita Bodini, Anna Russo, Lucilla Luzi, Pier Giuseppe Pelicci, Laura Riva

Published in: Breast Cancer Research | Issue 1/2017

Login to get access

Abstract

Background

The landscape of cancer-predisposing genes has been extensively investigated in the last 30 years with various methodologies ranging from candidate gene to genome-wide association studies. However, sequencing data are still poorly exploited in cancer predisposition studies due to the lack of statistical power when comparing millions of variants at once.

Method

To overcome these power limitations, we propose a knowledge-based framework founded on the characteristics of known cancer-predisposing variants and genes. Under our framework, we took advantage of a combination of previously generated datasets of sequencing experiments to identify novel breast cancer-predisposing variants, comparing the normal genomes of 673 breast cancer patients of European origin against 27,173 controls matched by ethnicity.

Results

We detected several expected variants on known breast cancer-predisposing genes, like BRCA1 and BRCA2, and 11 variants on genes associated with other cancer types, like RET and AKT1. Furthermore, we detected 183 variants that overlap with somatic mutations in cancer and 41 variants associated with 38 possible loss-of-function genes, including PIK3CB and KMT2C. Finally, we found a set of 19 variants that are potentially pathogenic, negatively correlate with age at onset, and have never been associated with breast cancer.

Conclusions

In this study, we demonstrate the usefulness of a genomic-driven approach nested in a classic case-control study to prioritize cancer-predisposing variants. In addition, we provide a resource containing variants that may affect susceptibility to breast cancer.
Appendix
Available only for authorised users
Literature
1.
Koboldt DC, Fulton RS, McLellan MD, Schmidt H, Kalicki-Veizer J, McMichael JF, et al. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490:61–70.CrossRef
2.
Ripperger T, Gadzicki D, Meindl A, Schlegelberger B. Breast cancer susceptibility: current knowledge and implications for genetic counselling. Eur J Hum Genet. 2008;17:722–31.CrossRefPubMedPubMedCentral
3.
Campeau PM, Foulkes WD, Tischkowitz MD. Hereditary breast cancer: new genetic developments, new therapeutic avenues. Hum Genet. 2008;124:31–42.CrossRefPubMed
4.
Fachal L, Dunning AM. From candidate gene studies to GWAS and post-GWAS analyses in breast cancer. Curr Opin Genet Dev. 2015;30:32–41.CrossRefPubMed
5.
6.
Chang CQ, Yesupriya A, Rowell JL, Pimentel CB, Clyne M, Gwinn M, et al. A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes. Eur J Hum Genet. 2014;22:402–8.CrossRefPubMed
7.
Michailidou K, Hall P, Gonzalez-Neira A, Ghoussaini M, Dennis J, Milne RL, et al. Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet. 2013;45:353–61.CrossRefPubMedPubMedCentral
8.
Zheng W, Zhang B, Cai Q, Sung H, Michailidou K, Shi J, et al. Common genetic determinants of breast-cancer risk in East Asian women: a collaborative study of 23 637 breast cancer cases and 25 579 controls. Hum Mol Genet. 2013;22:2539–50.CrossRefPubMedPubMedCentral
9.
Schrader KA, Cheng DT, Joseph V, et al. GErmline variants in targeted tumor sequencing using matched normal dna. JAMA Oncol. 2016;2:104–11.CrossRefPubMed
10.
Cancer Genome Atlas Research Network, Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, Ellrott K, Shmulevich I, Sander C, Stuart JM. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet. 2013;45(10):1113–20. doi:10.​1038/​ng.​2764.
11.
Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536:285–91.CrossRefPubMedPubMedCentral
12.
13.
Liu X, Jian X, Boerwinkle E. dbNSFP v2.0: A database of human non-synonymous SNVs and their functional predictions and annotations. Hum Mutat. 2013;34:E2393–402.CrossRefPubMedPubMedCentral
14.
Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 2014;42:D1001–6.CrossRefPubMed
15.
Griffith M, Spies NC, Krysiak K, McMichael JF, Coffman AC, Danos AM, et al. CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat Genet. 2017;49:170–4.CrossRefPubMedPubMedCentral
16.
Ainscough BJ, Griffith M, Coffman AC, Wagner AH, Kunisaki J, Choudhary MN, et al. DoCM: a database of curated mutations in cancer. Nat Methods. 2016;13:806–7.CrossRefPubMedPubMedCentral
17.
Forbes SA, Bindal N, Bamford S, Cole C, Kok CY, Beare D, et al. COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer. Nucleic Acids Res. 2011;39:D945–50.CrossRefPubMed
18.
Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, et al. The cBio Cancer genomics portal: an open platform for exploring multidimensional cancer genomics Data. Cancer Discov. 2012;2:401–4.CrossRefPubMed
19.
The UniProt Consortium. Activities at the Universal Protein Resource (UniProt). Nucleic Acids Res. 2014;42:D191–8.CrossRef
20.
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:D980–5.CrossRefPubMed
21.
22.
Walsh T, Lee MK, Casadei S, Thornton AM, Stray SM, Pennil C, et al. Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing. Proc Natl Acad Sci. 2010;107:12629–33.CrossRefPubMedPubMedCentral
23.
24.
Stratakis CA, Kirschner LS, Carney JA. Clinical and molecular features of the Carney complex: diagnostic criteria and recommendations for patient evaluation. J Clin Endocrinol Metab. 2001;86:4041–6.CrossRefPubMed
25.
Petrucelli N, Daly MB, Feldman GL. Hereditary breast and ovarian cancer due to mutations in BRCA1 and BRCA2. Genet Med. 2010;12:245–59.CrossRefPubMed
26.
Rahman N, Seal S, Thompson D, Kelly P, Renwick A, Elliott A, et al. PALB2, which encodes a BRCA2-interacting protein, is a breast cancer susceptibility gene. Nat Genet. 2007;39:165–7.CrossRefPubMed
27.
Jones S, Hruban RH, Kamiyama M, Borges M, Zhang X, Parsons DW, et al. Exomic sequencing identifies PALB2 as a pancreatic cancer susceptibility gene. Science. 2009;324:217.CrossRefPubMedPubMedCentral
28.
Martins VL, Vyas JJ, Chen M, Purdie K, Mein CA, South AP, et al. Increased invasive behaviour in cutaneous squamous cell carcinoma with loss of basement-membrane type VII collagen. J Cell Sci. 2009;122:1788–99.CrossRefPubMedPubMedCentral
29.
30.
Morandi A, Plaza-Menacho I, Isacke CM. RET in breast cancer: functional and therapeutic implications. Trends Mol Med. 2011;17:149–57.CrossRefPubMed
31.
32.
33.
34.
Baglietto L, Lindor NM, Dowty JG, White DM, Wagner A, Gomez Garcia EB, et al. Risks of Lynch syndrome cancers for MSH6 mutation carriers. JNCI J Natl Cancer Inst. 2010;102:193–201.CrossRefPubMed
35.
36.
Bleeker FE, Felicioni L, Buttitta F, Lamba S, Cardone L, Rodolfo M, et al. AKT1E17K in human solid tumours. Oncogene. 2008;27:5648–50.CrossRefPubMed
37.
Chang MT, Asthana S, Gao SP, Lee BH, Chapman JS, Kandoth C, et al. Identifying recurrent mutations in cancer reveals widespread lineage diversity and mutational specificity. Nat Biotechnol. 2016;34:155–63.CrossRefPubMed
38.
Jensen LJ, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J, et al. STRING 8--a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res. 2009;37:D412–6.CrossRefPubMed
39.
40.
Piñero J, Bravo À, Queralt-Rosinach N, Gutiérrez-Sacristán A, Deu-Pons J, Centeno E, et al. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res. 2017;45:D833–9.CrossRefPubMed
41.
Boyd NF, Martin LJ, Yaffe MJ, Minkin S. Mammographic density and breast cancer risk: current understanding and future prospects. Breast Cancer Res BCR. 2011;13:223.CrossRefPubMed
42.
Machiela MJ, Ho BM, Fisher VA, Hua X, Chanock SJ. Limited evidence that cancer susceptibility regions are preferential targets for somatic mutation. Genome Biol. 2015;16:193.CrossRefPubMedPubMedCentral
43.
Golmard L, Caux-Moncoutier V, Davy G, Al Ageeli E, Poirot B, Tirapo C, et al. Germline mutation in the RAD51B gene confers predisposition to breast cancer. BMC Cancer. 2013;13:484.CrossRefPubMedPubMedCentral
44.
Yang L, Yu S-J, Hong Q, Yang Y, Shao Z-M. Reduced expression of TET1, TET2, TET3 and TDG mRNAs are associated with poor prognosis of patients with early breast cancer. PLoS One. 2015;10, e0133896.CrossRefPubMedPubMedCentral
45.
46.
Schroeder RD, Angelo LS, Kurzrock R. NF2/Merlin in hereditary neurofibromatosis 2 versus cancer: biologic mechanisms and clinical associations. Oncotarget. 2013;5:67–77.PubMedCentral
47.
Nevanlinna H, Bartek J. The CHEK2 gene and inherited breast cancer susceptibility. Oncogene. 2006;25:5912–9.CrossRefPubMed
48.
Gayther SA, Batley SJ, Linger L, Bannister A, Thorpe K, Chin S-F, et al. Mutations truncating the EP300 acetylase in human cancers. Nat Genet. 2000;24:300–3.CrossRefPubMed
49.
Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol. 1995;57:289–300.
50.
Antoniou AC, Casadei S, Heikkinen T, Barrowdale D, Pylkäs K, Roberts J, et al. Breast-cancer risk in families with mutations in PALB2. N Engl J Med. 2014;371:497–506.CrossRefPubMedPubMedCentral
51.
Utermark T, Rao T, Cheng H, Wang Q, Lee SH, Wang ZC, et al. The p110α and p110β isoforms of PI3K play divergent roles in mammary gland development and tumorigenesis. Genes Dev. 2012;26:1573–86.CrossRefPubMedPubMedCentral
52.
Okamura K, Feuk L, Marquès-Bonet T, Navarro A, Scherer SW. Frequent appearance of novel protein-coding sequences by frameshift translation. Genomics. 2006;88:690–7.CrossRefPubMed
53.
Fadista J, Oskolkov N, Hansson O, Groop L. LoFtool: a gene intolerance score based on loss-of-function variants in 60 706 individuals. Bioinforma Oxf Engl. 2017;33:471–4.
54.
55.
56.
Shivapurkar N, Sood S, Wistuba II, Virmani AK, Maitra A, Milchgrub S, et al. Multiple regions of chromosome 4 demonstrating allelic losses in breast carcinomas. Cancer Res. 1999;59:3576–80.PubMed
57.
Myatt SS, Lam EW-F. The emerging roles of forkhead box (Fox) proteins in cancer. Nat Rev Cancer. 2007;7:847–59.CrossRefPubMed
58.
Valiente M, Obenauf AC, Jin X, Chen Q, Zhang XH-F, Lee DJ, et al. Serpins promote cancer cell survival and vascular cooption in brain metastasis. Cell. 2014;156:1002–16.CrossRefPubMedPubMedCentral
59.
60.
Lawrence MS, Stojanov P, Mermel CH, Robinson JT, Garraway LA, Golub TR, et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature. 2014;505:495–501.CrossRefPubMedPubMedCentral
61.
Timp W, Feinberg AP. Cancer as a dysregulated epigenome allowing cellular growth advantage at the expense of the host. Nat Rev Cancer. 2013;13:497–510.CrossRefPubMedPubMedCentral
62.
Rebouissou S, Vasiliu V, Thomas C, Bellanné-Chantelot C, Bui H, Chrétien Y, et al. Germline hepatocyte nuclear factor 1alpha and 1beta mutations in renal cell carcinomas. Hum Mol Genet. 2005;14:603–14.CrossRefPubMed
63.
Rahman N, Scott RH. Cancer genes associated with phenotypes in monoallelic and biallelic mutation carriers: new lessons from old players. Hum Mol Genet. 2007;16:R60–6.CrossRefPubMed
64.
Berends MJW, Wu Y, Sijmons RH, Mensink RGJ, van der Sluis T, Hordijk-Hos JM, et al. Molecular and clinical characteristics of MSH6 variants: an analysis of 25 index carriers of a germline variant. Am J Hum Genet. 2002;70:26–37.CrossRefPubMed
65.
Foulkes WD, Metcalfe K, Sun P, Hanna WM, Lynch HT, Ghadirian P, et al. Estrogen receptor status in BRCA1- and BRCA2-related breast cancer: the influence of age, grade, and histological type. Clin Cancer Res. 2004;10:2029–34.CrossRefPubMed
66.
Kanchi KL, Johnson KJ, Lu C, McLellan MD, Leiserson MDM, Wendl MC, et al. Integrated analysis of germline and somatic variants in ovarian cancer. Nat Commun. 2014;5:3156.CrossRefPubMedPubMedCentral
67.
Lu C, Xie M, Wendl MC, Wang J, McLellan MD, Leiserson MDM, et al. Patterns and functional implications of rare germline variants across 12 cancer types. Nat Commun. 2015;6:10086.CrossRefPubMedPubMedCentral
Metadata
Title
A knowledge-based framework for the discovery of cancer-predisposing variants using large-scale sequencing breast cancer data
Authors
Giorgio E. M. Melloni
Luca Mazzarella
Loris Bernard
Margherita Bodini
Anna Russo
Lucilla Luzi
Pier Giuseppe Pelicci
Laura Riva
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2017
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-017-0854-1

Other articles of this Issue 1/2017

Breast Cancer Research 1/2017 Go to the issue

Research article

Parity, hormones and breast cancer subtypes - results from a large nested case-control study in a national screening program

Research

Serum concentrations of active tamoxifen metabolites predict long-term survival in adjuvantly treated breast cancer patients

Research article

DCYTB is a predictor of outcome in breast cancer that functions via iron-independent mechanisms

Erratum

Erratum to: Honokiol activates AMP-activated protein kinase in breast cancer cells via LKB1-dependent pathway and inhibits breast carcinogenesis

Research article

A phase-I study of lapatinib in combination with foretinib, a c-MET, AXL and vascular endothelial growth factor receptor inhibitor, in human epidermal growth factor receptor 2 (HER-2)-positive metastatic breast cancer

Erratum

Erratum to: Cyclin D1 cooperates with p21 to regulate TGFβ-mediated breast cancer cell migration and tumor local invasion
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine
Image Credits