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DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer.

ABSTRACT: Germline pathogenic mutations in BRCA1 increase risk of developing breast cancer. Screening for mutations in BRCA1 frequently identifies sequence variants of unknown pathogenicity and recent work has aimed to develop methods for determining pathogenicity. We previously observed that tumor DNA methylation can differentiate BRCA1-mutated from BRCA1-wild type tumors. We hypothesized that we could predict pathogenicity of variants based on DNA methylation profiles of tumors that had arisen in carriers of unclassified variants. We selected 150 FFPE breast tumor DNA samples [47 BRCA1 pathogenic mutation carriers, 65 BRCAx (BRCA1-wild type), 38 BRCA1 test variants] and analyzed a subset (n=54) using the Illumina 450K methylation platform, using the remaining samples for bisulphite pyrosequencing validation. Three validated markers (BACH2, C8orf31, and LOC654342) were combined with sequence bioinformatics in a model to predict pathogenicity of 27 variants (independent test set). Predictions were compared with standard multifactorial likelihood analysis. Prediction was consistent for c.5194-12G>A (IVS 19-12 G>A) (P>0.99); 13 variants were considered not pathogenic or likely not pathogenic using both approaches. We conclude that tumor DNA methylation data alone has potential to be used in prediction of BRCA1 variant pathogenicity but is not independent of estrogen receptor status and grade, which are used in current multifactorial models to predict pathogenicity.

SUBMITTER: Flower KJ

PROVIDER: S-EPMC4844213 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer.

Flower Kirsty J KJ Shenker Natalie S NS El-Bahrawy Mona M Goldgar David E DE Parsons Michael T MT Spurdle Amanda B AB Morris Joanna R JR Brown Robert R Flanagan James M JM

Epigenetics 20150101 12

Germline pathogenic mutations in BRCA1 increase risk of developing breast cancer. Screening for mutations in BRCA1 frequently identifies sequence variants of unknown pathogenicity and recent work has aimed to develop methods for determining pathogenicity. We previously observed that tumor DNA methylation can differentiate BRCA1-mutated from BRCA1-wild type tumors. We hypothesized that we could predict pathogenicity of variants based on DNA methylation profiles of tumors that had arisen in carrie ...[more]

PMID: 26727311

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Project description:BACKGROUND: BRCA1 and BRCA2 germline mutations predispose heterozygous carriers to hereditary breast/ovarian cancer. However, unclassified variants (UVs) (variants with unknown clinical significance) and missense polymorphisms in BRCA1 and BRCA2 genes pose a problem in genetic counseling, as their impact on risk of breast and ovarian cancer is still unclear. The objective of our study was to identify UVs and missense polymorphisms in Algerian breast/ovarian cancer patients and relatives tested previously for BRCA1 and BRCA2 genes germline mutations analysis. METHODS: We analyzed 101 DNA samples from 79 breast/ovarian cancer families. The approach used is based on BRCA1 and BRCA2 sequence variants screening by SSCP or High-Resolution Melting (HRM) curve analysis followed by direct sequencing. In silico analyses have been performed using different bioinformatics programs to individualize genetics variations that can disrupt the BRCA1 and BRCA2 genes function. RESULTS: Among 80 UVs and polymorphisms detected in BRCA1/2 genes (33 BRCA1 and 47 BRCA2), 31 were new UVs (10 BRCA1 and 21 BRCA2), 7 were rare UVs (4 BRCA1 and 3 BRCA2) and 42 were polymorphic variants (19 BRCA1 and 23 BRCA2). Moreover, 8 new missense UVs identified in this study: two BRCA1 (c.4066C>A/p.Gln1356Lys, c.4901G>T/p.Arg1634Met) located respectively in exons 11 and 16, and six BRCA2 (c.1099G>A/p.Asp367Asn, c.2636C>A/p.Ser879Tyr, c.3868T>A/p.Cys1290Ser, c.5428G>T/p.Val1810Phe, c.6346C>G/p.His2116Asp and c.9256G>A/p.Gly3086Arg) located respectively in exons 10, 11 and 24, show a damaging PSIC score yielded by PolyPhen2 program and could be pathogenic. In addition, 5 new BRCA} missense UVs out of six that were found to be damaging by PolyPhen2 program, also were deleterious according to SIFT program. The rare BRCA1 UV c.5332G>A/p.Asp1778Asn was found here for the first time in co-occurrence in trans with the deleterious BRCA1 mutation c.798_799delTT/p.Ser267LysfsX19 in young breast cancer patient. Moreover, 10 new identified intronic variants with unknown clinical significance (3 BRCA1 and 7 BRCA2) in the present study, could be considered as benign, because GeneSplicer, SpliceSiteFinder and MaxEntScan prediction programs show no splice site alteration for these variants. Several missense polymorphisms of BRCA1 c.2612C>T/p.Pro871Leu, c.3548A>G/p.Lys1183Arg, c.4837A>G/p.Ser1613Gly and BRCA2 c.865A>C/p.Asn289His, c.1114A>C/p.Asn372His, c.2971A>G/p.Asn991Asp, c.7150C>A/p.Gly2384Lys have been identified with high frequency in patients who were tested negative for BRCA1 and BRCA2 mutations. These missense polymorphisms could have a role as susceptibility breast cancer markers in Algerian breast/ovarian cancer families where pathological BRCA1 and BRCA2 mutations were not present. CONCLUSIONS: For the first time, UVs and missense polymorphisms in BRCA1 and BRCA2 genes have been identified in Algerian breast/ovarian cancer families. Evaluation of breast/ovarian cancer risk induced by the eight new missense UVs and common polymorphisms detected in our present work is on going in a larger study.

Project description:Background: Detection of variants of uncertain significance (VUSs) in BRCA1 and BRCA2 genes poses relevant challenges for counseling and managing patients. VUS carriers should be managed similarly to probands with no BRCA1/2 variants detected, and predictive genetic testing in relatives is discouraged. However, miscomprehension of VUSs is common and can lead to inaccurate risk perception and biased decisions about prophylactic surgery. Therefore, efforts are needed to improve VUS evaluation and communication at an individual level. Aims: We aimed at investigating whether cosegregation analysis, integrated with a careful review of available functional data and in silico predictions, may improve VUSs interpretation and counseling in individual families. Methods: Patients with Breast Cancer (BC) and/or Ovarian Cancer (OC) fulfilling established criteria were offered genetic counseling and BRCA1/2 testing; VUSs identified in index cases were checked in other relatives affected by BC/OC whenever possible. As an alternative, if BC/OC clustered only in one branch of the family, the parental origin of the VUS was investigated. Public prediction tools and databases were used to collect additional information on the variants analyzed. Results: Out of 1045 patients undergoing BRCA1/2 testing in the period October 2011-April 2018, 66 (6.3%) carried class 3 VUSs. Cosegregation analysis was performed for 13 VUSs in 11 kindreds. Seven VUSs (53.8%) did not cosegregate with breast/ovarian cancer in the family, which provided evidence against their role in cancer clustering in those families. Among the 6 cosegregating VUSs, for two (BRCA1 c.5152+2T>G and BRCA2 c.7975A>G) additional evidence exists from databases and in silico tools supporting their pathogenicity, which reinforces the hypothesis they may have had a predisposing effect in respective families. For the remaining four VUSs (31%), cosegregation analysis failed to provide relevant information. Conclusion: Our findings suggest that cosegregation analysis in a clinical context may be helpful to improve test result interpretation in the specific family and, therefore, should be offered whenever possible. Besides, obtaining and sharing cosegregation data helps gathering evidence that may eventually contribute to VUS classification.

Project description:IntroductionEfforts are ongoing to determine the significance of unclassified variants (UVs) in the breast cancer susceptibility genes BRCA1/BRCA2, but no study has systematically assessed whether women carrying the suspected deleterious UVs have characteristics commonly seen among women carrying known deleterious or disease-causing mutations in BRCA1/BRCA2.MethodsWe sequenced BRCA1/BRCA2 in 1,469 population-based female breast cancer patients diagnosed between the ages of 20 and 49 years. We used existing literature to classify variants into known deleterious mutations, polymorphic variants, and UVs. The UVs were further classified as high risk or low risk based on five methods: allele frequency, Polyphen algorithm, sequence conservation, Grantham matrix scores, and a combination of the Grantham matrix score and sequence conservation. Furthermore, we examined whether patients who carry the variants classified as high risk using these methods have risk characteristics similar to patients with known deleterious BRCA1/BRCA2 mutations (early age at diagnosis, family history of breast cancer or ovarian cancer, and negative estrogen receptor/progesterone receptor).ResultsWe identified 262 distinct BRCA1/BRCA2 variants, including 147 UVs, in our study population. The BRCA1 UV carriers, but not the BRCA2 UV carriers, who were classified as high risk using each classification method were more similar to the deleterious mutation carriers with respect to family history than those carriers classified as low risk. For example, the odds ratio of having a first-degree family history for the high-risk women classified using Polyphen was 3.39 (95% confidence interval = 1.16 to 9.94) compared with normal/polymorphic BRCA1 carriers. The corresponding odds ratio of low-risk women was 1.53 (95% confidence interval = 1.07 to 2.18). The odds ratio for high-risk women defined by allele frequency was 2.00 (95% confidence interval = 1.14 to 3.51), and that of low-risk women was 1.30 (95% confidence interval = 0.87 to 1.93).ConclusionThe results suggest that the five classification methods yielded similar results. Polyphen was particularly better at isolating BRCA1 UV carriers likely to have a family history of breast cancer or ovarian cancer, and may therefore help to classify BRCA1 UVs. Our study suggests that these methods may not be as successful in classifying BRCA2 UVs.

Project description:BackgroundAbnormal DNA methylation is well established for breast cancer and contributes to its progression by silencing tumor suppressor genes. DNA methylation profiling platforms might provide an alternative approach to expression microarrays for accurate breast tumor subtyping. We sought to determine whether the distinction of the inflammatory breast cancer (IBC) phenotype from the non-IBC phenotype by transcriptomics could be sustained by methylomics.Methodology/principal findingsWe performed methylation profiling on a cohort of IBC (N = 19) and non-IBC (N = 43) samples using the Illumina Infinium Methylation Assay. These results were correlated with gene expression profiles. Methylation values allowed separation of breast tumor samples into high and low methylation groups. This separation was significantly related to DNMT3B mRNA levels. The high methylation group was enriched for breast tumor samples from patients with distant metastasis and poor prognosis, as predicted by the 70-gene prognostic signature. Furthermore, this tumor group tended to be enriched for IBC samples (54% vs. 24%) and samples with a high genomic grade index (67% vs. 38%). A set of 16 CpG loci (14 genes) correctly classified 97% of samples into the low or high methylation group. Differentially methylated genes appeared to be mainly related to focal adhesion, cytokine-cytokine receptor interactions, Wnt signaling pathway, chemokine signaling pathways and metabolic processes. Comparison of IBC with non-IBC led to the identification of only four differentially methylated genes (TJP3, MOGAT2, NTSR2 and AGT). A significant correlation between methylation values and gene expression was shown for 4,981 of 6,605 (75%) genes.Conclusions/significanceA subset of clinical samples of breast cancer was characterized by high methylation levels, which coincided with increased DNMT3B expression. Furthermore, an association was observed with molecular signatures indicative of poor patient prognosis. The results of the current study also suggest that aberrant DNA methylation is not the main force driving the molecular biology of IBC.

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DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer.

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DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer.

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