Dataset Information

Breast cancer risks associated with missense variants in breast cancer susceptibility genes.

ABSTRACT:

Background

Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain.

Methods

We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated.

Results

The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set.

Conclusions

These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.

SUBMITTER: Dorling L

PROVIDER: S-EPMC9116026 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Publications

Breast cancer risks associated with missense variants in breast cancer susceptibility genes.

Dorling Leila L Carvalho Sara S Allen Jamie J Parsons Michael T MT Fortuno Cristina C González-Neira Anna A Heijl Stephan M SM Adank Muriel A MA Ahearn Thomas U TU Andrulis Irene L IL Auvinen Päivi P Becher Heiko H Beckmann Matthias W MW Behrens Sabine S Bermisheva Marina M Bogdanova Natalia V NV Bojesen Stig E SE Bolla Manjeet K MK Bremer Michael M Briceno Ignacio I Camp Nicola J NJ Campbell Archie A Castelao Jose E JE Chang-Claude Jenny J Chanock Stephen J SJ Chenevix-Trench Georgia G Collée J Margriet JM Czene Kamila K Dennis Joe J Dörk Thilo T Eriksson Mikael M Evans D Gareth DG Fasching Peter A PA Figueroa Jonine J Flyger Henrik H Gabrielson Marike M Gago-Dominguez Manuela M García-Closas Montserrat M Giles Graham G GG Glendon Gord G Guénel Pascal P Gündert Melanie M Hadjisavvas Andreas A Hahnen Eric E Hall Per P Hamann Ute U Harkness Elaine F EF Hartman Mikael M Hogervorst Frans B L FBL Hollestelle Antoinette A Hoppe Reiner R Howell Anthony A Jakubowska Anna A Jung Audrey A Khusnutdinova Elza E Kim Sung-Won SW Ko Yon-Dschun YD Kristensen Vessela N VN Lakeman Inge M M IMM Li Jingmei J Lindblom Annika A Loizidou Maria A MA Lophatananon Artitaya A Lubiński Jan J Luccarini Craig C Madsen Michael J MJ Mannermaa Arto A Manoochehri Mehdi M Margolin Sara S Mavroudis Dimitrios D Milne Roger L RL Mohd Taib Nur Aishah NA Muir Kenneth K Nevanlinna Heli H Newman William G WG Oosterwijk Jan C JC Park Sue K SK Peterlongo Paolo P Radice Paolo P Saloustros Emmanouil E Sawyer Elinor J EJ Schmutzler Rita K RK Shah Mitul M Sim Xueling X Southey Melissa C MC Surowy Harald H Suvanto Maija M Tomlinson Ian I Torres Diana D Truong Thérèse T van Asperen Christi J CJ Waltes Regina R Wang Qin Q Yang Xiaohong R XR Pharoah Paul D P PDP Schmidt Marjanka K MK Benitez Javier J Vroling Bas B Dunning Alison M AM Teo Soo Hwang SH Kvist Anders A de la Hoya Miguel M Devilee Peter P Spurdle Amanda B AB Vreeswijk Maaike P G MPG Easton Douglas F DF

Genome medicine 20220518 1

<h4>Background</h4>Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain.<h4>Methods</h4>We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), B ...[more]

PMID: 35585550

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Project description:Understanding the gene-specific risks for development of breast cancer will lead to improved clinical care for those carrying germline mutations in cancer predisposition genes. We sought to detail the spectrum of mutations and refine risk estimates for known and proposed breast cancer susceptibility genes. Targeted massively-parallel sequencing was performed to identify mutations and copy number variants in 26 known or proposed breast cancer susceptibility genes in 2134 BRCA1/2-negative women with familial breast cancer (proband with breast cancer and a family history of breast or ovarian cancer) from a largely European-Caucasian multi-institutional cohort. Case-control analysis was performed comparing the frequency of internally classified mutations identified in familial breast cancer women to Exome Aggregation Consortium controls. Mutations were identified in 8.2% of familial breast cancer women, including mutations in high-risk (odds ratio > 5) (1.4%) and moderate-risk genes (2 < odds ratio < 5) (2.9%). The remaining familial breast cancer women had mutations in proposed breast cancer genes (1.7%), Lynch syndrome genes (0.5%), and six cases had two mutations (0.3%). Case-control analysis demonstrated associations with familial breast cancer for ATM, PALB2, and TP53 mutations (odds ratio > 3.0, p < 10-4), BARD1 mutations (odds ratio = 3.2, p = 0.012), and CHEK2 truncating mutations (odds ratio = 1.6, p = 0.041). Our results demonstrate that approximately 4.7% of BRCA1/2 negative familial breast cancer women have mutations in genes statistically associated with breast cancer. We classified PALB2 and TP53 as high-risk, ATM and BARD1 as moderate risk, and CHEK2 truncating mutations as low risk breast cancer predisposition genes. This study demonstrates that large case-control studies are needed to fully evaluate the breast cancer risks associated with mutations in moderate-risk and proposed susceptibility genes.

Project description:Family history remains one of the strongest risk factors for breast cancer. It is well established that women with a first-degree relative affected by breast cancer are twice as likely to develop the disease themselves. Twins studies indicate that this is most likely due to shared genetics rather than shared epidemiological/lifestyle risk factors. Linkage and targeted sequencing studies have shown that rare high- and moderate-penetrance germline variants in genes involved in the DNA damage response (DDR) including BRCA1, BRCA2, PALB2, ATM, and TP53 are responsible for a proportion of breast cancer cases. However, breast cancer is a heterogeneous disease, and there is now strong evidence that different risk alleles can predispose to different subtypes of breast cancer. Here, we review the associations between the different genes and subtype-specificity of breast cancer based on the most comprehensive genetic studies published. Genome-wide association studies (GWAS) have also been used to identify an additional hereditary component of breast cancer, and have identified hundreds of common, low-penetrance susceptibility alleles. The combination of these low penetrance risk variants, summed as a polygenic risk score (PRS), can identify individuals across the spectrum of disease risk. However, there remains a substantial bottleneck between the discovery of GWAS-risk variants and their contribution to tumorigenesis mainly because the majority of these variants map to the non-protein coding genome. A range of functional genomic approaches are needed to identify the causal risk variants and target susceptibility genes and establish their underlying role in disease biology. We discuss how the application of these multidisciplinary approaches to understand genetic risk for breast cancer can be used to identify individuals in the population that may benefit from clinical interventions including screening for early detection and prevention, and treatment strategies to reduce breast cancer-related mortalities.

Dataset Information

Breast cancer risks associated with missense variants in breast cancer susceptibility genes.

Background

Methods

Results

Conclusions

Publications

Breast cancer risks associated with missense variants in breast cancer susceptibility genes.

Similar Datasets

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