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Assessment of rare BRCA1 and BRCA2 variants of unknown significance using hierarchical modeling.

ABSTRACT: Current evidence suggests that the genetic risk of breast cancer may be caused primarily by rare variants. However, while classification of protein-truncating mutations as deleterious is relatively straightforward, distinguishing as deleterious or neutral the large number of rare missense variants is a difficult on-going task. In this article, we present one approach to this problem, hierarchical statistical modeling of data observed in a case-control study of contralateral breast cancer (CBC) in which all the participants were genotyped for variants in BRCA1 and BRCA2. Hierarchical modeling permits leverage of information from observed correlations of characteristics of groups of variants with case-control status to infer with greater precision the risks of individual rare variants. A total of 181 distinct rare missense variants were identified among the 705 cases with CBC and the 1,398 controls with unilateral breast cancer. The model identified three bioinformatic hierarchical covariates, align-GV, align-GD, and SIFT scores, each of which was modestly associated with risk. Collectively, the 11 variants that were classified as adverse on the basis of all the three bioinformatic predictors demonstrated a stronger risk signal. This group included five of six missense variants that were classified as deleterious at the outset by conventional criteria. The remaining six variants can be considered as plausibly deleterious, and deserving of further investigation (BRCA1 R866C; BRCA2 G1529R, D2665G, W2626C, E2663V, and R3052W). Hierarchical modeling is a strategy that has promise for interpreting the evidence from future association studies that involve sequencing of known or suspected cancer genes.

SUBMITTER: Capanu M

PROVIDER: S-EPMC3111904 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Assessment of rare BRCA1 and BRCA2 variants of unknown significance using hierarchical modeling.

Capanu Marinela M Concannon Patrick P Haile Robert W RW Bernstein Leslie L Malone Kathleen E KE Lynch Charles F CF Liang Xiaolin X Teraoka Sharon N SN Diep Anh T AT Thomas Duncan C DC Bernstein Jonine L JL Begg Colin B CB

Genetic epidemiology 20110425 5

Current evidence suggests that the genetic risk of breast cancer may be caused primarily by rare variants. However, while classification of protein-truncating mutations as deleterious is relatively straightforward, distinguishing as deleterious or neutral the large number of rare missense variants is a difficult on-going task. In this article, we present one approach to this problem, hierarchical statistical modeling of data observed in a case-control study of contralateral breast cancer (CBC) i ...[more]

PMID: 21520273

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Project description:Background:The spectrum of BRCA mutations that predispose to development of breast/ovarian cancer in Indian population remains unexplored. We report incidence and various types of pathogenic, likely pathogenic and variants of unknown significance (VUS) mutations in BRCA1 and BRCA2 genes observed at a tertiary cancer center in North India. Materials and methods:A total of 206 unrelated breast and/or ovarian cancer patients, who met the National Comprehensive Cancer Network (NCCN) guidelines for genetic testing, were screened for germline BRCA1/BRCA 2 mutations on high-throughput sequencing platform; large genomic rearrangements were assessed by multiple ligation probe assay. Mutations were mined in mutational databases, PubMed, and discerned into classes. Furthermore, the clinicopathological correlation of BRCA mutation status with prognostic markers in breast cancer and tumor histology in ovarian cancer was performed. Results:In total, 45/206 and 17/206 cases showed positivity for BRCA1 and BRCA2 mutations, respectively, whereas 1/206 was positive for a mutation in both the genes. Altogether, 33 distinct BRCA1 mutations were observed, among which 27 were deleterious (12 frameshifts, 8 nonsense, 1 missense, 3 splice-site variants, 2 big deletions and 1 large duplication) and 6 were VUS. Five novel BRCA1 mutations (c.541G>T, c.1681delT, c.2295delG, c.4915C>T and exon 23 deletion) were identified. Seven mutations (c.2214_2215insT, c.2295delG, c.3607C>T,c.4158_4162delCTCTC, c.4571C>A, splicesite_3 (C>T) and exon 21-23 duplication) occurred more than once, whereas 16 distinct BRCA2 mutations were noted - 9 were lethal (6 frameshifts, 2 nonsense and 1 big deletion) and 7 VUS. One unique pathogenic BRCA2 mutation (c.932_933insT) was recognized. Two mutations (c.9976A>T and c.10089A>G) recurred twice. No significant difference in hormone receptor status was observed among BRCA1 carriers, BRCA2 carriers and noncarriers. Conclusion:We have documented various pathogenic and VUS mutations in BRCA1 and BRCA2 genes observed in the cohort. Six novel mutations were identified. The knowledge shared would assist genetic testing in enabling more focused site-specific screening for mutations in biological relatives.

Project description:BackgroundVariants of unknown significance (VUSs) have been identified in BRCA1 and BRCA2 and account for the majority of all identified sequence alterations. Notably, VUSs occur disproportionately in people of African descent hampering breast cancer (BCa) management and prevention efforts in the population. Our study sought to identify and characterize mutations associated with increased risk of BCa at young age.MethodsIn our study, the spectrum of mutations in BRCA1 and BRCA2 was enumerated in a cohort of 31 African American women of early age at onset breast cancer, with a family history of breast or cancer in general and/or with triple negative breast cancer. To improve the characterization of the BRCA1 and BRCA2 variants, bioinformatics tools were utilized to predict the potential function of each of the variants.ResultsUsing next generation sequencing methods and in silico analysis of variants, a total of 197 BRCA1 and 266 BRCA2 variants comprising 77 unique variants were identified in 31 patients. Of the 77 unique variants, one (1.3%) was a pathogenic frameshift mutation (rs80359304; BRCA2 Met591Ile), 13 (16.9%) were possibly pathogenic, 34 (44.2%) were benign, and 29 (37.7%) were VUSs. Genetic epidemiological approaches were used to determine the association with variant, haplotype, and phenotypes, such as age at diagnosis, family history of cancer and family history of breast cancer. There were 5 BRCA1 SNPs associated with age at diagnosis; rs1799966 (P=.045; Log Additive model), rs16942 (P=.033; Log Additive model), rs1799949 (P=.058; Log Additive model), rs373413425 (P=.040 and .023; Dominant and Log Additive models, respectively) and rs3765640 (P=.033 Log Additive model). Additionally, a haplotype composed of all 5 SNPs was found to be significantly associated with younger age at diagnosis using linear regression modeling (P=.023). Specifically, the haplotype containing all the variant alleles was associated with older age at diagnosis (OR= 5.03 95% CI=.91-9.14).ConclusionsKnowing a patient's BRCA mutation status is important for prevention and treatment decision-making. Improving the characterization of mutations will lead to better management, treatment, and BCa prevention efforts in African Americans who are disproportionately affected with aggressive BCa and may inform future precision medicine genomic-based clinical studies.

Dataset Information

Assessment of rare BRCA1 and BRCA2 variants of unknown significance using hierarchical modeling.

Publications

Assessment of rare BRCA1 and BRCA2 variants of unknown significance using hierarchical modeling.

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