Citations

Abstract Background: Guidelines recommend germline mutation testing of breast cancer predisposition genes in triple negative (TN) breast cancer cases with a family history of breast or ovarian cancer or when diagnosed under age 60. However, the prevalence of mutations in these genes among TN cases unselected for family history of breast or ovarian cancer is not known. Methods: To assess the frequency of mutations in 16 predisposition genes in TN cases we screened a large cohort of TN patients (n=1824) unselected for family history of breast or ovarian cancer from 12 centers and 824 study matched unaffected controls for mutations using a panel-based sequencing approach. Results: Deleterious mutations were identified in 15% of TN patients: 8.5% had BRCA1, 2.7% had BRCA2, and 3.6% had mutations in 12 other genes. Mutations in non-BRCA1/2 genes encoding proteins implicated in homologous recombination repair of DNA double strand breaks were detected at the same frequency as in breast cancer families. TN cases with mutations had high-grade tumors and were diagnosed at an earlier age than non-mutated cases. However, 10% of TN cases diagnosed at ≥60 years and 5% with no family history of cancer were also found to carry mutations. Inactivating mutations in non-BRCA1/2 predisposition genes were associated with moderate to high risks of TN breast cancer. Conclusions: National Comprehensive Cancer Network (NCCN) guidelines support clinical genetic testing of breast cancer predisposition genes in 95% of TN breast cancer patients carrying mutations in susceptibility genes. In contrast, National Institute of Health and Care Excellence (NICE) guidelines in the U.K. do not support genetic testing of a substantial proportion of TN patients with predisposing alleles. Frequency tables for inherited mutations in known predisposition genes based on age of diagnosis and family history of cancer will allow for selection of TN patients most likely to carry mutations in the predisposition genes. Citation Format: Fergus J Couch, Steven N Hart, Priyanka Sharma, Amanda Ewart Toland, Penelope Miron, Janet E Olson, Andrew Godwin, Vernon S Pankratz, Curtis Olswold, Seth Slettedahl, Lucia Guidugli, Matthias W Beckmann, Brigitte Rack, Arif B Ekici, Irene Konstantopoulou, Florentia Fostira, George Fountzilas, Liisa M Pelttari, Song Yao, Judy Garber, Angela Cox, Hiltrud Brauch, Christine Ambrosone, Heli Nevanlinna, Drakoulis Yannoukakos, Susan L Slager, Celine M Vachon, Diana M Eccles, Peter A Fasching. Triple-negative breast cancer: Frequency of inherited mutations in breast cancer susceptibility genes [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-12-03.

Abstract Germline mutations of BRCA1 and BRCA2 underlie joint susceptibility to breast and ovarian cancers, but do not account for all cases. Genome wide association studies show little overlap between common variants associated with breast and ovarian cancer susceptibility, whereas rare variants in genes initially identified as breast cancer susceptibility genes also confer susceptibility to ovarian cancer cases, unselected for breast cancer. Ovarian and breast tumors also are observed in Peutz-Jeghers and possibly in Lynch syndrome. To further elucidate rare germline susceptibilities for breast and ovarian cancer, we have ascertained a unique cohort of 90 BRCA1/2-negative probands with a personal history of breast cancer and ovarian/fallopian tube/peritoneal cancer, unselected for family history. Cases are from the clinical genetics services of Memorial Sloan-Kettering Cancer Center and University of Pennsylvania. Analysis is ongoing using both targeted and exome sequencing approaches. Germline DNA of 69 cases will be subjected to whole exome sequencing. A total of 21 additional cases will undergo targeted sequencing for 28 genes (8 cases) and an extended panel of 54 genes (13 cases). The majority of ovarian cancers are high-grade serous epithelial ovarian carcinoma (n=51), in combination with invasive ductal or DCIS (n=36), invasive lobular (n=4), or unspecified (n=11) breast cancers. The remaining ovarian subgroups comprise other epithelial subtypes; endometrioid (n=9), clear cell (n=3), mucinous and low-grade serous (n=3) and non-epithelial (n=4) or unclassified (n=20), in combination with invasive ductal or DCIS (n=21), invasive lobular (n=5) or unspecified (n=13) breast cancers. Preliminary analysis of the targeted set of genes in 69 cases, reveals 43 predicted pathogenic coding or splice site variants; 17 of which are within PALB2, MSH2, MSH6, BARD1, FANCE, CDKN2A, TP53, SETD2, SIRT1, BRIP1, RAD50, and RAD51D and are not seen in dbSNP138, 1000 Genomes or Exome Variant Server ESP6500 and 26 variants with reported frequencies in MUTYH, MSH6, MLH1, FAM175A, RAD50, UIMC1, JARID2, PHF3, SIRT1, MRE11A, ATM, BRCA2, TP53BP1, CDH1, RAD51D, BRCA1, BABAM1 of less than 1% allele frequency in public databases. Analysis of these variants across and within histologic subtypes is being undertaken to look for specific genotype-phenotype correlations. Analysis of novel candidate genes and pathways by co-segregation, functional analysis, as well as external replication is underway to determine whether shared rare variants, mutated genes, or altered pathways confer cancer susceptibility in this cohort. Germline susceptibility to breast and ovarian cancer is heterogenous and remains a critical research and clinical question. Improved understanding of the susceptibility genetics will allow further examination of the utility of targeted cancer prevention strategies in those who are found to be at risk. Citation Format: Kasmintan A. Schrader, Kara N. Maxwell, Joseph Vijai, Steven Hart, Tinu Thomas, Bradley Wubbenhorst, Lucia Guidugli, Robert Klein, Marina Corines, Liying Zhang, Susan Neuhausen, Jeffrey Weitzel, Namrata Gupta, Larry Norton, Clifford Hudis, Gad Getz, Mark Daly, Steven Lipkin, David Altshuler, Fergus Couch, Katherine Nathanson, Kenneth Offit. Determination of cancer susceptibility in probands with breast and ovarian cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3282. doi:10.1158/1538-7445.AM2014-3282

Abstract Recent studies have shown that associations between common genetic variation and gene expression in breast tumors provide insight into the functional mechanisms underlying breast cancer risk loci. However, the relationship between genetic variation, gene expression, and risk of triple negative (TN) breast cancer remains largely unexplored. We performed a genome-wide expression quantitative trait locus (eQTL) analysis of TN breast cancer using 668 formalin-fixed paraffin embedded TN tumors from the Triple Negative Breast Cancer Consortium (TNBCC) to identify novel genes relevant to TN breast cancer risk and to further explore the biology underlying known TN risk loci. Cis-eQTLs were defined as correlations between single nucleotide polymorphisms (SNP) and expression of genes within 1Mb, and trans-eQTLs were defined as the remainder of all SNP-gene correlations. In a genome-wide analysis, we identified 68,012 cis-eQTLs, representing correlations between 42,193 SNPs and 2,092 genes that were significant at a 10% false discovery rate (FDR). We also identified 70 trans-eQTLs across two unique genes at the same FDR threshold. Five cis-eQTLs involved SNPs previously associated with TN breast cancer risk (p<5.0x10-5) in 3,700 TN cases and 4,700 controls from the TNBCC. Three of these, located on chromosomes 5p (cis-eQTL p=4.8x10-34; risk p=1.1x10-7), 7p (cis-eQTL p=6.1x10-10; risk p=1.3x10-7), and 17q (cis-eQTL p=1.8x10-15; risk p=2.9x10-7), have previously been reported in public databases of normal tissue. The remaining two TN breast cancer cis-eQTLs, located on chromosomes 8q (cis-eQTL p=6.3x10-6, risk p=8.3x10-6) and 14q (cis-eQTL p=3.1x10-6, risk p=1.2x10-5), have not been reported as eQTLs in other tissues. In addition, 12 of 25 known TN breast cancer risk loci (PEX14, MDM4, 2q31.1, ESR1, 11q13.1, 11q24.3, 12p13.1, PTHLH, NTN4, 12q24, 19p13.1, MLK1), contained at least one significant cis-eQTL. In summary, we have identified five cis-eQTLs that may identify novel risk loci for TN breast cancer. Citation Format: Kristen S. Purrington, Drakoulis Yannoukakos, Jane Carpenter, Heli Nevanlinna, Angela Cox, Gianluca Severi, Christine Ambrosone, Amanda Ewart Toland, Andrew K. Godwin, Hiltrud Brauch, Peter A. Fasching, Penelope Miron, Jenny Chang-Claude, Nicholas G. Martin, Grant W. Montgomery, Vessela Kristensen, Hoda Anton-Culver, Paul Goodfellow, Janet E. Olson, Hugues Sicotte, Naresh Prodduturi, Daniel W. Visscher, Jeanette E. Eckel-Passow, S. Keith Anderson, Seth Slettedahl, Curtis Olswold, Xianshu Wang, V. Shane Pankratz, Susan Slager, Wei Zheng, Arto Mannermaa, Ute Hamann, Diana M. Eccles, Celine M. Vachon, Fergus J. Couch. Expression quantitative trait locus analysis of triple negative breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3266. doi:10.1158/1538-7445.AM2014-3266

Abstract Massively parallel next generation sequencing data (NGS) has proved to be useful in identification of rare Mendelian disorders. Efforts are on-going to use NGS for discovery of novel rare variants in common disease etiology. Distinguishing rare private mutations from causal variants remains a major challenge in complex disorders. With decreasing cost, investigators are generating NGS data for common cancers. However, power and other considerations suggest that a consortia approach of pooling data is more likely to succeed where individual efforts fail. Combining data within such consortia brings its own level of challenges. We enumerate these challenges and suggest recommendations based on our experience of combining and harmonizing NGS data on 358 breast cancer samples from four centers; (City of Hope n=8, Mayo Clinic n=221, MSKCC n=96 and University of Pennsylvania n=33). Major concerns were ability of individual datasets to discover known and novel variations, depth of coverage across the exome, and quality of variants. Using pre- and post-processed data, we demonstrate an increased power for detecting variants when using a joint-calling method, quality control (QC) and quality assurance pre- and post-merge, as well as the advantages of combined annotations and filtering procedures. To generate a filtered list of high confident calls, we subset the data on Depth per Allele (DP), Genotyping Quality (GQ), Allele balance, Phred likelihood score (PL) as well as using frequency filters on the alternate allele both within the data and comparing against convenience control summaries. We describe general principles and QC measures to be adopted when NGS data is used from diverse sources, specifically applicable to large consortia. Note: This abstract was not presented at the meeting. Citation Format: Joseph Vijai, Steven Hart, Tinu Thomas, Bradley Wubbenhorst, Lucia Guidugli, Kasmintan Schrader, Kara Maxwell, Lauren Jacobs, Danylo Villano, Robert Klein, Steven Lipkin, Susan Neuhausen, Jeffrey Weitzel, David Altshuler, Fergus Couch, Kenneth Offit, Katherine Nathanson. Harmonization of next generation sequencing data within consortia for gene discovery in familial breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2378. doi:10.1158/1538-7445.AM2014-2378

Abstract BRCA1 and BRCA2 (BRCA) testing is uninformative in approximately 80% of families with clinical features of inherited susceptibility to breast cancer. Early identification of the individuals at risk in BRCAx families may lead to enhanced screening and prevention strategies, and potentially improved overall survival as has been seen for carriers of BRCA1/2 mutations. A proportion of these families are likely explained by mutations in other high penetrance and moderate penetrance breast cancer susceptibility genes. Although multi-gene panels are now commercially available for clinical testing, only limited information is available on the spectrum of mutations in breast cancer susceptibility genes in specific subgroups of high-risk breast cancer patients. We performed whole exome sequencing in 278 BRCA1/2 negative individuals with high-risk familial breast cancer, defined as a proband and at least two first or second degree relatives with breast cancer. Samples included 232 individuals from 97 families and 49 unrelated individuals, for a total of 146 independent cases. Data were analyzed for identification of all variants in 18 known high and moderate penetrance breast cancer susceptibility genes, in addition to BRCA1 and BRCA2. Two of the 97 families and one of the 49 singletons (2% of independent cases) were found to have deleterious mutations in high penetrance genes, namely TP53 (2) and CDH1 (1). In addition, nine of 146 independent cases (6%) were found to have deleterious mutations in the other predisposition genes. Mutations in ATM and CHEK2 accounted for seven of the ten moderate penetrance mutations identified; additionally one family had a mutation in BLM, one in MRE11A, and one in PALB2. Furthermore, 15 of 146 independent cases (10%) were found to have variants of unknown significance (VUS) in one of eight genes. There were no deleterious mutations or VUS in eight of the 18 genes. Our data show that significant genetic heterogeneity exists in BRCAx families. Large-scale collaborative efforts will be required to attain sufficient power to understand how to appropriately apply these results clinically in cancer risk evaluation. Citation Format: Kara N. Maxwell, Lucia Guidugli, Kasmintan Schrader, Steven Hart, Vijai Joseph, Tinu Thomas, Xianshu Wang, Bradley Wubbenhorst, Robert Klein, Susan M. Domchek, Csilla Szabo, Susan Neuhausen, Jeffrey Weitzel, Katherine L. Nathanson, Kenneth Offit, Fergus Couch. High and moderate penetrance germline mutations in a number of genes are responsible for a small proportion of familial breast cancer risk in BRCAx families. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1291. doi:10.1158/1538-7445.AM2014-1291

Abstract Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10−5). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk. Cancer Res; 75(12); 2457–67. ©2015 AACR.

Abstract Background: Mammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent mammographic density (PMD) with larger and node-positive tumors across all ages, and estrogen receptor (ER)–negative status among women ages <55 years. To provide insight into these associations, we examined the components of PMD [dense area (DA) and nondense area (NDA)] with breast cancer subtypes. Methods: Data were pooled from six studies including 4,095 breast cancers and 8,558 controls. DA and NDA were assessed from digitized film-screen mammograms and standardized across studies. Breast cancer odds by density phenotypes and age according to histopathologic characteristics and receptor status were calculated using polytomous logistic regression. Results: DA was associated with increased breast cancer risk [OR for quartiles: 0.65, 1.00 (Ref), 1.22, 1.55; Ptrend <0.001] and NDA was associated with decreased risk [ORs for quartiles: 1.39, 1.00 (Ref), 0.88, 0.72; Ptrend <0.001] across all ages and invasive tumor characteristics. There were significant trends in the magnitude of associations of both DA and NDA with breast cancer by increasing tumor size (Ptrend < 0.001) but no differences by nodal status. Among women <55 years, DA was more strongly associated with increased risk of ER+ versus ER− tumors (Phet = 0.02), while NDA was more strongly associated with decreased risk of ER− versus ER+ tumors (Phet = 0.03). Conclusions: DA and NDA have differential associations with ER+ versus ER− tumors that vary by age. Impact: DA and NDA are important to consider when developing age- and subtype-specific risk models. Cancer Epidemiol Biomarkers Prev; 24(5); 798–809. ©2015 AACR.

Background Inactivating germline mutations in the tumour suppressor gene BRCA1 are associated with a significantly increased risk of developing breast and ovarian cancer. A large number (>1500) of unique BRCA1 variants have been identified in the population and can be classified as pathogenic, non-pathogenic or as variants of unknown significance (VUS). Many VUS are rare missense variants leading to single amino acid changes. Their impact on protein function cannot be directly inferred from sequence information, precluding assessment of their pathogenicity. Thus, functional assays are critical to assess the impact of these VUS on protein activity. BRCA1 is a multifunctional protein and different assays have been used to assess the impact of variants on different biochemical activities and biological processes. Methods and results To facilitate VUS analysis, we have developed a visualisation resource that compiles and displays functional data on all documented BRCA1 missense variants. BRCA1 Circos is a web-based visualisation tool based on the freely available Circos software package. The BRCA1 Circos web tool (http://research.nhgri.nih.gov/bic/circos/) aggregates data from all published BRCA1 missense variants for functional studies, harmonises their results and presents various functionalities to search and interpret individual-level functional information for each BRCA1 missense variant. Conclusions This research visualisation tool will serve as a quick one-stop publically available reference for all the BRCA1 missense variants that have been functionally assessed. It will facilitate meta-analysis of functional data and improve assessment of pathogenicity of VUS.