Simple Summary Genetic variants explaining approximately 40% of familial breast cancer risk have been identified, thus leaving a significant fraction of the heritability of this disease still... Show moreSimple Summary Genetic variants explaining approximately 40% of familial breast cancer risk have been identified, thus leaving a significant fraction of the heritability of this disease still unexplained. The exact nature of this missing fraction is unknown; more extensive sequencing efforts could potentially identify new moderate-penetrance breast cancer risk alleles. The aim of this study was to perform a large-scale whole-exome sequencing study, followed by a targeted validation, in breast cancer patients and healthy women of European descent. We identified 20 novel genes with modest evidence of association (p-value < 0.05) for either overall or subtype-specific breast cancer; however, much larger studies are needed to confirm the exact role of these genes in susceptibility to breast cancer. Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes. Show less
Spurdle, A.B.; Greville-Heygate, S.; Antoniou, A.C.; Brown, M.; Burke, L.; Hoya, M. de la; ... ; Eccles, D.M. 2019
The vocabulary currently used to describe genetic variants and their consequences reflects many years of studying and discovering monogenic disease with high penetrance. With the recent rapid... Show moreThe vocabulary currently used to describe genetic variants and their consequences reflects many years of studying and discovering monogenic disease with high penetrance. With the recent rapid expansion of genetic testing brought about by wide availability of high-throughput massively parallel sequencing platforms, accurate variant interpretation has become a major issue. The vocabulary used to describe single genetic variants in silico, in vitro, in vivo and as a contributor to human disease uses terms in common, but the meaning is not necessarily shared across all these contexts. In the setting of cancer genetic tests, the added dimension of using data from genetic sequencing of tumour DNA to direct treatment is an additional source of confusion to those who are not experienced in cancer genetics. The language used to describe variants identified in cancer susceptibility genetic testing typically still reflects an outdated paradigm of Mendelian inheritance with dichotomous outcomes. Cancer is a common disease with complex genetic architecture; an improved lexicon is required to better communicate among scientists, clinicians and patients, the risks and implications of genetic variants detected. This review arises from a recognition of, and discussion about, inconsistencies in vocabulary usage by members of the ENIGMA international multidisciplinary consortium focused on variant classification in breast-ovarian cancer susceptibility genes. It sets out the vocabulary commonly used in genetic variant interpretation and reporting, and suggests a framework for a common vocabulary that may facilitate understanding and clarity in clinical reporting of germline genetic tests for cancer susceptibility. Show less
The third Human Variome Project (HVP) Meeting "Integration and Implementation" was held under UNESCO Patronage in Paris, France, at the UNESCO Headquarters May 10-14, 2010. The major aims of the... Show moreThe third Human Variome Project (HVP) Meeting "Integration and Implementation" was held under UNESCO Patronage in Paris, France, at the UNESCO Headquarters May 10-14, 2010. The major aims of the HVP are the collection, curation, and distribution of all human genetic variation affecting health. The HVP has drawn together disparate groups, by country, gene of interest, and expertise, who are working for the common good with the shared goal of pushing the boundaries of the human variome and collaborating to avoid unnecessary duplication. The meeting addressed the 12 key areas that form the current framework of HVP activities: Ethics; Nomenclature and Standards; Publication, Credit and Incentives; Data Collection from Clinics; Overall Data Integration and Access-Peripheral Systems/Software; Data Collection from Laboratories; Assessment of Pathogenicity; Country Specific Collection; Translation to Healthcare and Personalized Medicine; Data Transfer, Databasing, and Curation; Overall Data Integration and Access-Central Systems; and Funding Mechanisms and Sustainability. In addition, three societies that support the goals and the mission of HVP also held their own Workshops with the view to advance disease-specific variation data collection and utilization: the International Society for Gastrointestinal Hereditary Tumours, the Micronutrient Genomics Project, and the Neurogenetics Consortium. Show less
![Combined genetic and splicing analysis of BRCA1 c.[594-2A > C; 641A > G] highlights the relevance of naturally occurring in-frame transcripts for developing disease gene variant classification algorithms](/sites/all/modules/custom/islandora_solr_search/images/defaultimg.png?solr_nav%5Bid%5D=7a7ec64615690d0098a7&solr_nav%5Bpage%5D=0&solr_nav%5Boffset%5D=3)
