Irene L Andrulis

Mount Sinai Hospital, New York, New York, United States

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Publications (249)2009.2 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: We carried out whole genome and transcriptome sequencing on four tumor/normal pairs of epithelioid sarcoma. These index cases were supplemented with whole transcriptome sequencing of three additional tumors and three cell lines. Unlike rhabdoid tumor (the other major group of SMARCB1-negative cancers), epithelioid sarcoma shows a complex genome with a higher mutational rate, comparable to that of ovarian carcinoma. Despite this mutational burden, SMARCB1 mutations remain the most frequently recurring event and are probably critical drivers of tumor formation. Several cases show heterozygous SMARCB1 mutations without inactivation of the second allele, and we explore this further in vitro. Finding CDKN2A deletions in our discovery cohort, we evaluated CDKN2A protein expression in a tissue microarray. Six out of sixteen cases had lost CDKN2A in greater than or equal to 90% of cells, while the remaining cases had retained the protein. Expression analysis of epithelioid sarcoma cell lines by transcriptome sequencing shows a unique profile that does not cluster with any particular tissue type nor with other SWI/SNF-aberrant lines. Evaluation of the levels of members of the SWI/SNF complex other than SMARCB1 revealed that these proteins are expressed as part of a residual complex, similarly to previously studied rhabdoid tumor lines. This residual SWI/SNF is susceptible to synthetic lethality and may therefore indicate a therapeutic opportunity.
    The Journal of Pathology 09/2015; DOI:10.1002/path.4636 · 7.43 Impact Factor
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    ABSTRACT: In breast cancer, constitutive activation of NF-κB has been reported, however, the impact of genetic variation of the pathway on patient prognosis has been little studied. Furthermore, a combination of genetic variants, rather than single polymorphisms, may affect disease prognosis. Here, in an extensive dataset (n = 30,431) from the Breast Cancer Association Consortium, we investigated the association of 917 SNPs in 75 genes in the NF-κB pathway with breast cancer prognosis. We explored SNP-SNP interactions on survival using the likelihood-ratio test comparing multivariate Cox' regression models of SNP pairs without and with an interaction term. We found two interacting pairs associating with prognosis: patients simultaneously homozygous for the rare alleles of rs5996080 and rs7973914 had worse survival (HRinteraction 6.98, 95% CI=3.3-14.4, P=1.42E-07), and patients carrying at least one rare allele for rs17243893 and rs57890595 had better survival (HRinteraction 0.51, 95% CI=0.3-0.6, P = 2.19E-05). Based on in silico functional analyses and literature, we speculate that the rs5996080 and rs7973914 loci may affect the BAFFR and TNFR1/TNFR3 receptors and breast cancer survival, possibly by disturbing both the canonical and non-canonical NF-κB pathways or their dynamics, whereas, rs17243893-rs57890595 interaction on survival may be mediated through TRAF2-TRAIL-R4 interplay. These results warrant further validation and functional analyses.
    Oncotarget 08/2015; DOI:10.18632/oncotarget.4991 · 6.36 Impact Factor
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    ABSTRACT: Background: Epidemiological studies have linked adult height with breast cancer risk in women. However, the magnitude of the association, particularly by subtypes of breast cancer, has not been established. Furthermore, the mechanisms of the association remain unclear. Methods: We performed a meta-analysis to investigate associations between height and breast cancer risk using data from 159 prospective cohorts totaling 5216302 women, including 113178 events. In a consortium with individual-level data from 46325 case patients and 42482 control patients, we conducted a Mendelian randomization analysis using a genetic score that comprised 168 height-associated variants as an instrument. This association was further evaluated in a second consortium using summary statistics data from 16003 case patients and 41335 control patients. Results: The pooled relative risk of breast cancer was 1.17 (95% confidence interval [CI] = 1.15 to 1.19) per 10cm increase in height in the meta-analysis of prospective studies. In Mendelian randomization analysis, the odds ratio of breast cancer per 10cm increase in genetically predicted height was 1.22 (95% CI = 1.13 to 1.32) in the first consortium and 1.21 (95% CI = 1.05 to 1.39) in the second consortium. The association was found in both premenopausal and postmenopausal women but restricted to hormone receptor-positive breast cancer. Analyses of height-associated variants identified eight new loci associated with breast cancer risk after adjusting for multiple comparisons, including three loci at 1q21.2, DNAJC27, and CCDC91 at genome-wide significance level P < 5×10(-8). Conclusions: Our study provides strong evidence that adult height is a risk factor for breast cancer in women and certain genetic factors and biological pathways affecting adult height have an important role in the etiology of breast cancer.
    Journal of the National Cancer Institute 08/2015; 107(11). DOI:10.1093/jnci/djv219 · 12.58 Impact Factor
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    ABSTRACT: Introduction: Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density. Methods: The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density. Results: No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5' of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP×MHT×case-status <0.02). Conclusions: The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the association of MHT use with mammographic density.
    Breast cancer research: BCR 08/2015; 17(1):110. DOI:10.1186/s13058-015-0625-9 · 5.49 Impact Factor
  • Cancer Research 08/2015; 75(15 Supplement):5574-5574. DOI:10.1158/1538-7445.AM2015-5574 · 9.33 Impact Factor
  • International Journal of Epidemiology 07/2015; DOI:10.1093/ije/dyv118 · 9.18 Impact Factor
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    ABSTRACT: Epidemiological studies have reported inconsistent associations between telomere length (TL) and risk for various cancers. These inconsistencies are likely attributable, in part, to biases that arise due to post-diagnostic and post-treatment TL measurement. To avoid such biases, we used a Mendelian randomization approach and estimated associations between nine TL-associated SNPs and risk for five common cancer types (breast, lung, colorectal, ovarian and prostate cancer, including subtypes) using data on 51,725 cases and 62,035 controls. We then used an inverse-variance weighted average of the SNP-specific associations to estimate the association between a genetic score representing long TL and cancer risk. The long TL genetic score was significantly associated with increased risk of lung adenocarcinoma (P=6.3x10(-15)), even after exclusion of a SNP residing in a known lung cancer susceptibility region (TERT-CLPTM1L) P=6.6x10(-6)). Under Mendelian randomization assumptions, the association estimate (odds ratio (OR)=2.78) is interpreted as the OR for lung adenocarcinoma corresponding to a 1000 base pair increase in TL. The weighted TL SNP score was not associated with other cancer types or subtypes. Our finding that genetic determinants of long TL increase lung adenocarcinoma risk avoids issues with reverse causality and residual confounding that arise in observational studies of TL and disease risk. Under Mendelian randomization assumptions, our finding suggests that longer TL increases lung adenocarcinoma risk. However, caution regarding this causal interpretation is warranted in light of the potential issue of pleiotropy, and a more general interpretation is that SNPs influencing telomere biology are also implicated in lung adenocarcinoma risk. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email:
    Human Molecular Genetics 07/2015; 24(18). DOI:10.1093/hmg/ddv252 · 6.39 Impact Factor
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    ABSTRACT: The etiologic contribution of germline genetic variation to sporadic osteosarcoma is not well understood. Osteosarcoma is a sentinel cancer of Li-Fraumeni syndrome (LFS), in which approximately 70% of families meeting the classic criteria have germline TP53 mutations. We sequenced TP53 exons in 765 osteosarcoma cases. Data were analyzed with χ(2) tests, logistic regression, and Cox proportional hazards regression models. We observed a high frequency of young osteosarcoma cases (age <30 years) carrying a known LFS- or likely LFS-associated mutation (3.8%) or rare exonic variant (5.7%) with an overall frequency of 9.5%, compared with none in case patients age 30 years and older (P < .001). This high TP53 mutation prevalence in young osteosarcoma cases is statistically significantly greater than the previously reported prevalence of 3% (P = .0024). We identified a novel association between a TP53 rare variant and metastasis at diagnosis of osteosarcoma (rs1800372, odds ratio = 4.27, 95% confidence interval = 1.2 to 15.5, P = .026). Genetic susceptibility to young onset osteosarcoma is distinct from older adult onset osteosarcoma, with a high frequency of LFS-associated and rare exonic TP53 variants. Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.
    Journal of the National Cancer Institute 07/2015; 107(7). DOI:10.1093/jnci/djv101 · 12.58 Impact Factor
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    ABSTRACT: Mena(calc) is an immunofluorescence-based, quantitative method in which expression of the non-invasive Mena protein isoform (Mena11a) is subtracted from total Mena protein expression. Previous work has found a significant positive association between Mena(calc) and risk of death from breast cancer. Our goal was to determine if Mena(calc) could be used as an independent prognostic marker for axillary node-negative (ANN) breast cancer. Analysis of the association of Mena(calc) with overall survival (death from any cause) was performed for 403 ANN tumors using Kaplan Meier survival curves and the univariate Cox proportional hazards (PH) model with the log-rank or the likelihood ratio test. Cox PH models were used to estimate hazard ratios (HRs) for the association of Mena(calc) with risk of death after adjustment for HER2 status and clinicopathological tumor features. High Mena(calc) was associated with increased risk of death from any cause (P = 0.0199, HR (CI) = 2.18 (1.19, 4.00)). A similarly elevated risk of death was found in the subset of the Mena(calc) cohort which did not receive hormone or chemotherapy (n = 142) (P = 0.0052, HR (CI) = 3.80 (1.58, 9.97)). There was a trend toward increased risk of death with relatively high Mena(calc) in the HER2, basal and luminal molecular subtypes. Mena(calc) may serve as an independent prognostic biomarker for the ANN breast cancer patient population.
    BMC Cancer 06/2015; 15(1):483. DOI:10.1186/s12885-015-1468-6 · 3.36 Impact Factor
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    ABSTRACT: Metastasis is the leading cause of death in osteosarcoma patients, the most common pediatric bone malignancy. We conducted a multi-stage genome-wide association study of osteosarcoma metastasis at diagnosis in 935 osteosarcoma patients to determine whether germline genetic variation contributes to risk of metastasis. We identified a SNP, rs7034162, in NFIB significantly associated with metastasis in European osteosarcoma cases, as well as in cases of African and Brazilian ancestry (meta-analysis of all cases: P=1.2x10(-9), OR 2.43, 95% CI 1.83-3.24). The risk allele was significantly associated with lowered NFIB expression, which led to increased osteosarcoma cell migration, proliferation, and colony formation. Additionally, a transposon screen in mice identified a significant proportion of osteosarcomas harboring inactivating insertions in Nfib, and had lowered Nfib expression. These data suggest that germline genetic variation at rs7034162 is important in osteosarcoma metastasis, and that NFIB is an osteosarcoma metastasis susceptibility gene. Copyright © 2015, American Association for Cancer Research.
    Cancer Discovery 06/2015; 5(9). DOI:10.1158/2159-8290.CD-15-0125 · 19.45 Impact Factor
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    ABSTRACT: Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
    The American Journal of Human Genetics 06/2015; 97(1). DOI:10.1016/j.ajhg.2015.05.002 · 10.93 Impact Factor
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    ABSTRACT: BReast CAncer genes 1 and 2 (BRCA1 and BRCA2) mutation carriers diagnosed with breast cancer are at increased risk of developing a second primary breast cancer. Data from high-risk clinics may be subject to different biases which can cause both over and underestimation of this risk. Using data from a large multi-institutional family registry we estimated the 10-year cumulative risk of second primary breast cancer including more complete testing information on family members. We prospectively followed 800 women diagnosed with breast cancer from the Breast Cancer Family Registry (BCFR) who were carriers of a BRCA1 or BRCA2 pathogenic mutation or a variant of unknown clinical significance. In order to limit survival and ascertainment bias, cases were limited to those diagnosed with a first primary breast cancer from 1994 to 2001 and enrolled in the BCFR within 3 years after their cancer diagnosis. We excluded women enrolled after being diagnosed with a second breast cancer. We calculated 10-year incidence of second primary breast cancers. The 10-year incidence of a second primary breast cancer was highest in BRCA1 mutation carriers (17 %; 95 % CI 11-25 %), with even higher estimates in those first diagnosed under the age of 40 (21 %; 95 % CI 13-34 %). Lower rates were found in BRCA2 mutation carriers (7 %; 95 % CI 3-15 %) and women with a variant of unknown clinical significance (6 %; 95 % CI 4-9 %). Whereas the cumulative 10-year incidence of second primary breast cancer is high in BRCA1 mutation carriers, the estimates in BRCA2 mutation carriers and women with variants of unknown clinical significance are similar to those reported in women with sporadic breast cancer.
    Breast Cancer Research and Treatment 05/2015; 151(3). DOI:10.1007/s10549-015-3419-y · 3.94 Impact Factor
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    ABSTRACT: Objective: Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3' UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370. Methods: Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers). Results: We found no association with risk of ovarian cancer (OR=0.99, 95% CI 0.94-1.04, p=0.74) or breast cancer (OR=0.98, 95% CI 0.94-1.01, p=0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR=1.09, 95% CI 0.97-1.23, p=0.14, breast cancer HR=1.04, 95% CI 0.97-1.12, p=0.27; BRCA2, ovarian cancer HR=0.89, 95% CI 0.71-1.13, p=0.34, breast cancer HR=1.06, 95% CI 0.94-1.19, p=0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR=0.94, 95% CI 0.83-1.07, p=0.38), breast cancer (HR=0.96, 95% CI 0.87-1.06, p=0.38), and all other previously-reported associations. Conclusions: rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.
    Gynecologic Oncology 05/2015; DOI:10.1016/j.ygyno.2015.04.034 · 3.77 Impact Factor
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    ABSTRACT: Individuals carrying pathogenic mutations in BRCA1/2 genes have a high lifetime risk of breast cancer. BRCA1 and BRCA2 are involved in DNA double strand break repair, DNA alterations that can be caused by exposure to reactive oxygen species, a main source of which are mitochondria. Mitochondrial genome variations affect electron transport chain efficiency and reactive oxygen species production. Individuals from different mitochondrial haplogroups differ in their metabolism and sensitivity to oxidative stress. Variability in mitochondrial genetic background can alter reactive oxygen species production, leading to cancer risk. Here we test the hypothesis that mitochondrial haplogroups modify breast cancer risk in BRCA1/2 mutation carriers. We genotyped 22214 (11421 affected, 10793 unaffected) mutation carriers belonging to the Consortium of Investigators of Modifiers of BRCA1/2 for 129 mitochondrial polymorphisms using the iCOGS array. Haplogroup inference and association detection were performed using a phylogenetic approach. ALTree was applied to explore the reference mitochondrial evolutionary tree and detect subclades enriched for affected or unaffected individuals. We discovered that subclade T1a1 was depleted in affected BRCA2 mutation carriers than the rest of clade T, (Hazard Ratio (HR) = 0.55 (95% Confidence Interval (CI) 0.34-0.88, p-value = 0.01). Compared with the most frequent haplogroup in the general population i.e. H and T clade, the T1a1 haplogroup has an HR = 0.62 (95% CI = 0.40-0.95, p-value = 0.03). We also identified three potential susceptibility loci, including G13708A/rs28359178, which has demonstrated an inverse association with familial breast cancer risk. This study illustrates how original approaches like the phylogeny-based method we used can empower classical molecular epidemiological studies aimed at identifying association or risk modification effects.
    Breast cancer research: BCR 04/2015; 17(1):61. DOI:10.1186/s13058-015-0567-2 · 5.49 Impact Factor
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    ABSTRACT: A common and aggressive subtype of soft-tissue sarcoma, undifferentiated pleomorphic sarcoma (UPS) was examined to determine the role of micro-RNAs (miRNAs) in modulating distant metastasis. Following histopathologic review, 110 fresh frozen clinically annotated UPS samples were divided into two independent cohorts for Training (42 patients), and Validation (68 patients) analyses. Global miRNA profiling on the Training Set and functional analysis in vitro suggested that miRNA-138 and its downstream RHO-ROCK cell adhesion pathway was a convergent target of miRNAs associated with the development of metastasis. A six-miRNA signature set prognostic of distant metastasis-free survival (DMFS) was developed from Training Set miRNA expression values. Using the six-miRNA signature, patients were successfully categorized into high- and low-risk groups for DMFS in an independent Validation Set, with a hazard ratio (HR) of 2.25 (p = 0.048). After adjusting for other known prognostic variables such as age, gender, tumor grade, size, depth, and treatment with radiotherapy, the six-miRNA signature retained prognostic value with a HR of 3.46 (p < 0.001). A prognostic miRNA biomarker for clinical validation was thus identified along with a functional pathway that modulates UPS metastatic phenotype.
    Oncotarget 04/2015; DOI:10.18632/oncotarget.3926 · 6.36 Impact Factor
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    ABSTRACT: Introduction: Previous studies have identified common germline variants nominally associated with breast cancer survival. These associations have not been widely replicated in further studies. The purpose of this study was to evaluate the association of previously reported SNPs with breast cancer-specific survival using data from a pooled analysis of eight breast cancer survival genome-wide association studies (GWAS) from the Breast Cancer Association Consortium. Methods: A literature review was conducted of all previously published associations between common germline variants and three survival outcomes: breast cancer-specific survival, overall survival and disease-free survival. All associations that reached the nominal significance level of P value <0.05 were included. Single nucleotide polymorphisms that had been previously reported as nominally associated with at least one survival outcome were evaluated in the pooled analysis of over 37,000 breast cancer cases for association with breast cancer-specific survival. Previous associations were evaluated using a one-sided test based on the reported direction of effect. Results: Fifty-six variants from 45 previous publications were evaluated in the meta-analysis. Fifty-four of these were evaluated in the full set of 37,954 breast cancer cases with 2,900 events and the two additional variants were evaluated in a reduced sample size of 30,000 samples in order to ensure independence from the previously published studies. Five variants reached nominal significance (P <0.05) in the pooled GWAS data compared to 2.8 expected under the null hypothesis. Seven additional variants were associated (P <0.05) with ER-positive disease. Conclusions: Although no variants reached genome-wide significance (P <5 x 10(-8)), these results suggest that there is some evidence of association between candidate common germline variants and breast cancer prognosis. Larger studies from multinational collaborations are necessary to increase the power to detect associations, between common variants and prognosis, at more stringent significance levels.
    Breast Cancer Research 04/2015; 17(1). DOI:10.1186/s13058-015-0570-7 · 5.49 Impact Factor
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    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 non-dense 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 non-dense areas, and between rs17356907 (NTN4) and adjusted absolute non-dense 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 etiological pathways implicated in how mammographic density predicts breast cancer risk. Copyright © 2015, American Association for Cancer Research.
    Cancer Research 04/2015; 75(12). DOI:10.1158/0008-5472.CAN-14-2012 · 9.33 Impact Factor
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    ABSTRACT: We have utilized a two-stage study design to search for SNPs associated with the survival of breast cancer patients treated with adjuvant chemotherapy. Our initial GWS data set consisted of 805 Finnish breast cancer cases (360 treated with adjuvant chemotherapy). The top 39 SNPs from this stage were analyzed in three independent data sets: iCOGS (n=6720 chemotherapy-treated cases), SUCCESS-A (n=3596), and POSH (n=518). Two SNPs were successfully validated: rs6500843 (any chemotherapy; per-allele HR 1.16, 95% C.I. 1.08-1.26, p=0.0001, p(adjusted)=0.0091), and rs11155012 (anthracycline therapy; per-allele HR 1.21, 95% C.I. 1.08-1.35, p=0.0010, p(adjusted)=0.0270). The SNP rs6500843 was found to specifically interact with adjuvant chemotherapy, independently of standard prognostic markers (p(interaction)=0.0009), with the rs6500843-GG genotype corresponding to the highest hazard among chemotherapy-treated cases (HR 1.47, 95% C.I. 1.20-1.80). Upon trans-eQTL analysis of public microarray data, the rs6500843 locus was found to associate with the expression of a group of genes involved in cell cycle control, notably AURKA, the expression of which also exhibited differential prognostic value between chemotherapy-treated and untreated cases in our analysis of microarray data. Based on previously published information, we propose that the eQTL genes may be connected to the rs6500843 locus via a RBFOX1-FOXM1 -mediated regulatory pathway.
    Oncotarget 04/2015; 6(10):7390-7407. DOI:10.18632/oncotarget.3506 · 6.36 Impact Factor
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    ABSTRACT: Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.
    Nature Genetics 03/2015; DOI:10.1038/ng.3242 · 29.35 Impact Factor

Publication Stats

8k Citations
2,009.20 Total Impact Points


  • 2014–2015
    • Mount Sinai Hospital
      New York, New York, United States
    • The Ohio State University
      Columbus, Ohio, United States
  • 1989–2015
    • University of Toronto
      • • Department of Molecular Genetics
      • • Department of Laboratory Medicine and Pathobiology
      • • Department of Surgery
      • • Mount Sinai Hospital
      Toronto, Ontario, Canada
    • Mount Sinai Hospital, Toronto
      • Department of Pathology and Laboratory Medicine
      Toronto, Ontario, Canada
  • 2011–2014
    • Sinai Hospital
      Mount Sinai, New York, United States
  • 1993–2014
    • Samuel Lunenfeld Research Institute
      Toronto, Ontario, Canada
  • 2013
    • German Cancer Research Center
      • Division of Cancer Epidemiology
      Heidelberg, Baden-Wuerttemberg, Germany
    • Herlev Hospital
      • Department of Pathology
      Herlev, Capital Region, Denmark
  • 2012
    • Memorial Sloan-Kettering Cancer Center
      New York City, New York, United States
  • 2005–2012
    • Cancer Care Ontario
      Toronto, Ontario, Canada
  • 2010
    • Albert Einstein College of Medicine
      New York City, New York, United States
  • 2009–2010
    • University of Cambridge
      • • Department of Public Health and Primary Care
      • • Department of Oncology
      Cambridge, ENG, United Kingdom
    • Beijing University of Technology
      Peping, Beijing, China
  • 2007
    • University of Cologne
      Köln, North Rhine-Westphalia, Germany
  • 2006
    • Columbia University
      New York, New York, United States
  • 1984–1986
    • SickKids
      Toronto, Ontario, Canada