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Targeted massively parallel sequencing of a panel of putative breast cancer susceptibility genes in a large cohort of multiple-case breast and ovarian cancer families.
- Source :
-
Journal of medical genetics [J Med Genet] 2016 Jan; Vol. 53 (1), pp. 34-42. Date of Electronic Publication: 2015 Nov 03. - Publication Year :
- 2016
-
Abstract
- Introduction: Gene panel testing for breast cancer susceptibility has become relatively cheap and accessible. However, the breast cancer risks associated with mutations in many genes included in these panels are unknown.<br />Methods: We performed custom-designed targeted sequencing covering the coding exons of 17 known and putative breast cancer susceptibility genes in 660 non-BRCA1/2 women with familial breast cancer. Putative deleterious mutations were genotyped in relevant family members to assess co-segregation of each variant with disease. We used maximum likelihood models to estimate the breast cancer risks associated with mutations in each of the genes.<br />Results: We found 31 putative deleterious mutations in 7 known breast cancer susceptibility genes (TP53, PALB2, ATM, CHEK2, CDH1, PTEN and STK11) in 45 cases, and 22 potential deleterious mutations in 31 cases in 8 other genes (BARD1, BRIP1, MRE11, NBN, RAD50, RAD51C, RAD51D and CDK4). The relevant variants were then genotyped in 558 family members. Assuming a constant relative risk of breast cancer across age groups, only variants in CDH1, CHEK2, PALB2 and TP53 showed evidence of a significantly increased risk of breast cancer, with some supportive evidence that mutations in ATM confer moderate risk.<br />Conclusions: Panel testing for these breast cancer families provided additional relevant clinical information for <2% of families. We demonstrated that segregation analysis has some potential to help estimate the breast cancer risks associated with mutations in breast cancer susceptibility genes, but very large case-control sequencing studies and/or larger family-based studies will be needed to define the risks more accurately.<br /> (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)
- Subjects :
- Computational Biology methods
Exons
Female
Genes, BRCA1
Genes, BRCA2
Genetic Testing
Genotype
Germ-Line Mutation
Hereditary Breast and Ovarian Cancer Syndrome diagnosis
Humans
Male
Mutation
Odds Ratio
Ovarian Neoplasms diagnosis
Pedigree
Biomarkers, Tumor genetics
Genetic Association Studies
Genetic Predisposition to Disease
Hereditary Breast and Ovarian Cancer Syndrome genetics
High-Throughput Nucleotide Sequencing
Ovarian Neoplasms genetics
Subjects
Details
- Language :
- English
- ISSN :
- 1468-6244
- Volume :
- 53
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Journal of medical genetics
- Publication Type :
- Academic Journal
- Accession number :
- 26534844
- Full Text :
- https://doi.org/10.1136/jmedgenet-2015-103452