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2.  Mammographic Breast Density Response to Aromatase Inhibition 
Purpose
Mammographic breast density (MBD) is decreased by tamoxifen, but the effect of aromatase inhibitors (AI) is less clear.
Experimental Design
We enrolled early stage postmenopausal breast cancer patients initiating adjuvant AI therapy and ascertained mammograms before and at an average 10 months of AI therapy. We matched cases to healthy postmenopausal women (controls) from a large mammography screening cohort on age, baseline body mass index, baseline MBD and interval between mammograms. We estimated change in MBD using a computer-assisted thresholding program (Cumulus) and compared differences between cases and matched controls.
Results
In predominantly white women (96%), we found 14% of the 387 eligible cases had a MBD reduction of at least 5% after an average of 10 months of AI therapy. MBD reductions were associated with higher baseline MBD, AI use for more than 12 months and prior postmenopausal hormone use. Comparing each case to her matched control, there was no evidence of an association of change in MBD with AI therapy (median case-control difference among 369 pairs was −0.1% (10th and 90th percentile: −5.9%, 5.2%) p=0.51). Case-control differences were similar by type of AI (p’s 0.41 and 0.56); prior use of postmenopausal hormones (p=0.85); baseline MBD (p=0.55); or length of AI therapy (p=0.08).
Conclusions
In postmenopausal women treated with AIs, 14% of cases had a MBD reduction of >5%, but these decreases did not differ from matched controls. These data suggest that MBD is not a clinically useful biomarker for predicting the value of AI therapy in white postmenopausal women.
doi:10.1158/1078-0432.CCR-12-2789
PMCID: PMC3630282  PMID: 23468058
aromatase inhibitors; mammographic density; breast density; biomarker
3.  Mammographic texture resemblance generalizes as an independent risk factor for breast cancer 
Introduction
Breast density has been established as a major risk factor for breast cancer. We have previously demonstrated that mammographic texture resemblance (MTR), recognizing the local texture patterns of the mammogram, is also a risk factor for breast cancer, independent of percent breast density. We examine if these findings generalize to another population.
Methods
Texture patterns were recorded in digitalized pre-diagnosis (3.7 years) film mammograms of a nested case–control study within the Dutch screening program (S1) comprising of 245 breast cancers and 250 matched controls. The patterns were recognized in the same study using cross-validation to form resemblance scores associated with breast cancer. Texture patterns from S1 were examined in an independent nested case–control study within the Mayo Mammography Health Study cohort (S2) of 226 cases and 442 matched controls: mammograms on average 8.5 years prior to diagnosis, risk factor information and percent mammographic density (PD) estimated using Cumulus were available. MTR scores estimated from S1, S2 and S1 + S2 (the latter two as cross-validations) were evaluated in S2. MTR scores were analyzed as both quartiles and continuously for association with breast cancer using odds ratios (OR) and adjusting for known risk factors including age, body mass index (BMI), and hormone usage.
Results
The mean ages of S1 and S2 were 58.0 ± 5.7 years and 55.2 ± 10.5 years, respectively. The MTR scores on S1 showed significant capability to discriminate cancers from controls (area under the operator characteristics curve (AUC) = 0.63 ± 0.02, P <0.001), which persisted after adjustment for PD. S2 showed an AUC of 0.63, 0.61, and 0.60 based on PD, MTR scores trained on S2, and MTR scores trained on S1, respectively. When adjusted for PD, MTR scores of S2 trained on S1 showed an association with breast cancer for the highest quartile alone: OR in quartiles of controls as reference; 1.04 (0.59 to 1.81); 0.95 (0.52 to 1.74); 1.84 (1.10 to 3.07) respectively. The combined continuous model with both PD and MTR scores based on S1 had an AUC of 0.66 ± 0.03.
Conclusions
The local texture patterns associated with breast cancer risk in S1 were also an independent risk factor in S2. Additional textures identified in S2 did not significantly improve risk segregation. Hence, the textural patterns that indicated elevated risk persisted under differences in X-ray technology, population demographics, follow-up time and geography.
doi:10.1186/bcr3641
PMCID: PMC4053089  PMID: 24713478
4.  Genetic Susceptibility to Triple Negative Breast Cancer 
Cancer research  2013;73(7):2025-2030.
Triple negative breast cancers (TNBC), defined by the absence of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 expression, account for 12-24% of all breast cancers. TNBC is associated with early recurrence of disease and poor outcome. Germline mutations in the BRCA1 and BRCA2 breast cancer susceptibility genes have been associated with up to 15% of TNBC, and TNBC accounts for 70% of breast tumors arising in BRCA1 mutation carriers and 16-23% of breast tumors in BRCA2 carriers. Whether germline mutations in other breast cancer susceptibility genes also predispose to TNBC remains to be determined. Common variation in a subset of the 72 known breast cancer susceptibility loci identified through genome wide association studies and other large-scale genotyping efforts have also been associated with risk of TNBC (TOX3, ESR1, RAD51L1, TERT, 19p13.1, 20q11, MDM4, 2p24.1, and FTO). Furthermore, variation in the 19p13.1 locus and the MDM4 locus has been associated with TNBC but not other forms of breast cancer suggesting that these are TNBC-specific loci. Thus, TNBC can be distinguished from other breast cancer subtypes by a unique pattern of common and rare germline predisposition alleles. Additional efforts to combine genetic and epidemiological data are needed to better understand the etiology of this aggressive form of breast cancer, to identify prevention and therapeutic targets, and to impact clinical practice through development of risk prediction models.
doi:10.1158/0008-5472.CAN-12-1699
PMCID: PMC3654815  PMID: 23536562
5.  Differences in the distribution of cytogenetic subtypes between multiple myeloma patients with and without a family history of monoclonal gammopathy and multiple myeloma 
European journal of haematology  2013;91(3):193-195.
We previously reported an increased risk of monoclonal gammopathy of undetermined significance (MGUS) in first-degree relatives of MGUS and multiple myeloma patients. Here, we examine whether primary cytogenetic categories of myeloma differ between patients with and without a family history of MGUS or myeloma. We studied 201 myeloma patients with available data on family history and molecular cytogenetic classification. Myeloma with trisomies was more common in probands who had an affected first-degree relative with MGUS or myeloma compared to those without a family history (46.9% vs. 33.5%, p=0.125); however, the difference was not statistically significant. Additional studies on the cytogenetic types of myeloma associated with familial tendency are needed.
doi:10.1111/ejh.12133
PMCID: PMC3762589  PMID: 23647020
Multiple myeloma; MGUS; family history; cytogenetics
6.  An Automated Approach for Estimation of Breast Density 
Breast density is a strong risk factor for breast cancer; however, no standard assessment method exists. An automated breast density method (ABDM) was modified and compared with a semi-automated user-assisted display method (CM) and the Breast Imaging Reporting and Data System (BI-RADS) four-category tissue composition measure for their ability to predict future breast cancer risk. The three estimation methods were evaluated in a matched breast cancer case (n=372) control (n=713) study at the Mayo Clinic using digitized film mammograms. Mammograms from the craniocaudal (CC) view of the noncancerous breast were acquired on average seven years before diagnosis. Two controls with no prior history of breast cancer from the screening practice were matched to each case on age, number of prior screening mammograms, final screening exam date, menopausal status at this date, interval between earliest and latest available mammograms, and residence. Both Pearson linear correlation (R) and Spearman rank correlation ( r ) coefficients were used for comparing the three methods where appropriate. Conditional logistic regression was used to estimate the risk of breast cancer (odds ratios [ORs] and 95% confidence intervals [CIs]) associated with the quartiles of percent density (ABDM, CM) or BI-RADS category. The area under the receiver operator characteristic curve (AUC) was estimated and used to compare the discriminatory capabilities of each approach. The continuous measures ABDM and CM were highly correlated with each other (R=0.70) but less with BI-RADS (r=0.49 for ABDM and r=0.57 for CM). Risk estimates associated with the lowest to highest quartiles of ABDM were greater in magnitude (ORs: 1.0[ref], 2.3, 3.0, 5.2, p-trend<0.001) than the corresponding quartiles for CM (ORs: 1.0[ref], 1.7, 2.1 and 3.8; p-trend<0.001) and BI-RADS (ORs: 1.0[ref], 1.6, 1.5, 2.6; p-trend<0.001) methods. However, all methods similarly discriminated between case and control status: AUCs were 0.64, 0.63 and 0.61 for ABDM, CM and BI-RADS, respectively. The ABDM is a viable option for quantitatively assessing breast density from digitized film mammograms.
doi:10.1158/1055-9965.EPI-08-0170
PMCID: PMC2705972  PMID: 18990749
Automated density; breast density; methodology
7.  Association of Mammographic Density with Pathology of Subsequent Breast Cancer among Postmenopausal Women 
Background
Limited studies have examined the associations between mammographic density and subsequent breast tumor characteristics.
Methods
Eligible women were part of a case-control study of postmenopausal breast cancer, 40 years and older, who had a routine mammogram four years or more before their diagnosis. Mammographic density (percent density [PD], dense area and nondense area) was estimated using a computer-assisted thresholding program. At the time of cancer diagnosis cases were classified as asymptomatic or symptomatic based on medical record review and breast imaging workup. Pathologic review was performed blinded to the density status. Linear regression models and tests for trend examined the association between pathologic characteristics of the breast tumor (except histology) and the components of density for all participants, and stratified by symptom status at diagnosis.
Results
Of the 286 eligible cases, 77% were 60 years or older and mean PD was 29.5% (SD=14.6%). Density was not significantly associated with tumor size (p=0.22), histologic type (p=0.77), estrogen receptor (ER) (p=0.11) or progesterone receptor (PR) (p=0.37) status, mitotic activity (p=0.12) or nuclear pleomorphism (p=0.09) [p-values for PD]. An inverse association was suggested between tumor grade and PD (31.95%, 30.29%, 26.73% for grade I-III; p for trend= 0.06). The inverse association with tumor grade and its components (nuclear pleomorphism and tubular differentiation) was only evident among the 97 symptomatic women; positive associations of ER (p=0.009) and PR (p=0.04) were also seen with PD only in this subgroup.
Conclusions
The inverse association between tumor grade and PD in the symptomatic population could inform the biology of the association between mammographic density and breast cancer risk.
doi:10.1158/1055-9965.EPI-07-0559
PMCID: PMC2705947  PMID: 18398028
mammographic density; pathology; breast cancer
8.  Higher alcohol intake may modify the association between mammographic density and breast cancer: An analysis of three case-control studies 
Cancer epidemiology  2012;36(5):458-460.
Alcohol consumption and mammographic density are established risk factors for breast cancer. This study examined whether the association of mammographic density with breast cancer varies by alcohol intake. Mammographic density was assessed in digitized images for 1,207 cases and 1,663 controls from three populations (Japan, Hawaii, California) using a computer-assisted method. Associations were estimated by logistic regression. When comparing ever to never drinking, mean density was similar and consumption was not associated with breast cancer risk. However, within the Hawaii/Japan subset, women consuming >1 drink/day had a non-significantly elevated relative risk compared to never drinkers. Also in the Hawaii/Japan population, alcohol intake only modified the association between mammographic density and breast cancer in women consuming >1 drink/day (pinteraction=0.05) with significant risk estimates of 3.65 and 6.58 for the 2nd and 3rd density tertiles as compared to 1.57 and 1.61 for never drinkers in Hawaii/Japan. Although these findings suggest a stronger association between mammographic density and breast cancer risk for alcohol consumers, the small number of cases requires caution in interpreting the results.
doi:10.1016/j.canep.2012.06.007
PMCID: PMC3438372  PMID: 22785031
breast cancer; alcohol; mammographic density; case-control study; pooling
9.  Single nucleotide polymorphism rs1052501 associated with monoclonal gammopathy of undetermined significance and multiple myeloma 
Leukemia  2012;27(2):515-516.
Summary
Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant precursor to multiple myeloma (MM). Though several genetic variants have been identified for MM, none have been identified for MGUS. Recently, Broderick et al. conducted a GWAS of MM and identified three novel loci at 3p22.1 (rs1052501), 7p15.3 (rs4487645) and 2p23.3 (rs6746082) associated with MM risk. We examined the association of these variants with MGUS in a clinic-based case-control study of 391 MGUS cases and 365 controls. We also attempted to replicate the reported association with MM (243 MM cases, 365 controls). We found rs1052501 associated with increased risk of both MGUS (OR=1.32; 95% CI, 1.02 to 1.72; p=0.04) and MM (OR=1.39; 95% CI, 1.04, 1.86; p=0.03). However, there were no associations with the other two loci, rs6746082 and rs4487645, for either MGUS or MM. We identified one genetic variant that may exert its influence on MM through its association with MGUS.
doi:10.1038/leu.2012.232
PMCID: PMC3707297  PMID: 22945773
genetic variation; MGUS; MM; single nucleotide polymorphism
10.  A Novel Automated Mammographic Density Measure and Breast 
Cancer Risk 
Background Mammographic breast density is a strong breast cancer risk factor but is not used in the clinical setting, partly because of a lack of standardization and automation. We developed an automated and objective measurement of the grayscale value variation within a mammogram, evaluated its association with breast cancer, and compared its performance with that of percent density (PD).
Methods Three clinic-based studies were included: a case–cohort study of 217 breast cancer case subjects and 2094 non-case subjects and two case–control studies comprising 928 case subjects and 1039 control subjects and 246 case subjects and 516 control subjects, respectively. Percent density was estimated from digitized mammograms using the computer-assisted Cumulus thresholding program, and variation was estimated from an automated algorithm. We estimated hazards ratios (HRs), odds ratios (ORs), the area under the receiver operating characteristic curve (AUC), and 95% confidence intervals (CIs) using Cox proportional hazards models for the cohort and logistic regression for case–control studies, with adjustment for age and body mass index. We performed a meta-analysis using random study effects to obtain pooled estimates of the associations between the two mammographic measures and breast cancer. All statistical tests were two-sided.
Results The variation measure was statistically significantly associated with the risk of breast cancer in all three studies (highest vs lowest quartile: HR = 7.0 [95% CI = 4.6 to 10.4]; OR = 10.7 [95% CI = 7.5 to 15.3]; OR = 2.6 [95% CI = 1.6 to 4.2]; all P trend < .001). In two studies, the risk estimates and AUCs for the variation measure were greater than those for percent density (AUCs for variation = 0.71 and 0.76; AUCs for percent density = 0.65 and 0.65), whereas in the third study, these estimates were similar (AUC for variation = 0.60 and AUC for percent density = 0.61). A meta-analysis of the three studies demonstrated a stronger association between variation and breast cancer (highest vs lowest quartile: RR = 3.6, 95% CI = 1.9 to 7.0) than between percent density and breast cancer (highest vs lowest quartile: RR = 2.3, 95% CI = 1.9 to 2.9).
Conclusion The association between the automated variation measure and the risk of breast cancer is at least as strong as that for percent density. Efforts to further evaluate and translate the variation measure to the clinical setting are warranted.
doi:10.1093/jnci/djs254
PMCID: PMC3634551  PMID: 22761274
11.  Healthy Women’s Motivators and Barriers to Participation in a Breast Cancer Cohort Study: A Qualitative Study 
Annals of epidemiology  2009;19(7):484-493.
Background
This focus group study describes motivators and barriers to participation in the Mayo Mammography Health Study (MMHS), a large-scale longitudinal study examining the causal association of breast density with breast cancer, involving completion of a survey, providing access to a residual blood sample for genetic analyses, and sharing their results from a screening mammogram. These women would then be followed long-term for breast cancer incidence and mortality.
Methods
48 Women participated in six focus groups, four with MMHS non-respondents (N=27), and two with MMHS respondents (N=21). Major themes were summarized using content analysis. Social Cognitive Theory (SCT) was used as a framework for interpretation of the findings.
Results
Barriers to participation among MMHS non-respondents were: 1) lack of confidence in their ability to fill out the survey accurately (self-efficacy); 2) lack of perceived personal connection to the study or value of participation (expectancies); and 3) fear related to some questions about perceived cancer risk and worry/concern (emotional coping responses). Among MMHS respondents, personal experience with cancer was reported as a primary motivator for participation (expectancies).
Conclusions
Application of a theoretical model such as SCT to the development of a study recruitment plan could be used to improve rates of study participation and provide a reproducible and evolvable strategy.
doi:10.1016/j.annepidem.2009.01.002
PMCID: PMC3682676  PMID: 19269854
Focus groups; participation; epidemiology; recruitment; social cognitive theory; breast cancer; mammography; qualitative
12.  Increased prevalence of light chain monoclonal gammopathy of undetermined significance (LC-MGUS) in first-degree relatives of individuals with multiple myeloma 
British Journal of Haematology  2012;157(4):472-475.
Previously, we reported increased risk of heavy-chain (HC) monoclonal gammopathy of undetermined significance (MGUS) among first-degree (1°) relatives of multiple myeloma (MM) or HC-MGUS probands. This study investigated whether there was comparable risk for light-chain (LC) MGUS among 911 relatives of the same HC-MGUS/MM probands versus a reference population of 21,463. Seventeen 1° relatives had LC-MGUS (adjusted prevalence =1.7%, 95% CI=0.9%–2.6%). There was increased risk of LC-MGUS in relatives of MM probands (RR=3.4, 95% CI=2.0–5.5). We saw no increased risk in relatives of HC-MGUS probands. We conclude that the prevalence of LC-MGUS is significantly higher among 1° relatives of MM probands.
PMCID: PMC3375594  PMID: 22629552
MGUS; myeloma; epidemiology
13.  Mammographic density and risk of breast cancer by adiposity: An analysis of four case-control studies 
The association of mammographic breast density with breast cancer risk may vary by adiposity. To examine effect modification by body mass index (BMI), the authors standardized mammographic density data from four case-control studies (1994–2002) conducted in California, Hawaii, and Minnesota, and Gifu, Japan. The 1,699 cases and 2,422 controls included 45% Caucasians, 40% Asians, and 9% African-Americans. Using ethnic-specific BMI cut points, 34% were classified as overweight and 19% as obese. A single reader assessed density from mammographic images using a computer-assisted method. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) while adjusting for potential confounders. Modest heterogeneity in the relation between percent density and breast cancer risk across studies was observed (pheterogeneity = 0.08). Cases had a greater age-adjusted mean percent density than controls: 31.7% versus 28.5%, respectively (p <0.001). Relative to <20 percent density, the ORs for >35 were similar across BMI groups whereas the OR for 20–35 was slightly higher in overweight (OR = 1.69, 95% CI: 1.28, 2.24) and obese (OR = 1.62, 95% CI: 1.12, 2.33) than in normal weight women (OR = 1.49, 95% CI: 1.11, 2.01). Furthermore, limited evidence of effect modification by BMI of the OR per 10% increase in percent density (pinteraction = 0.06) was observed, including subgroup analyses by menopausal status and in analyses that excluded women at the extremes of the BMI scale. Our findings indicate little, if any, modification by BMI of the effects of breast density on breast cancer risk.
doi:10.1002/ijc.26205
PMCID: PMC3254813  PMID: 21630258
Adiposity; breast cancer incidence; body mass index; ethnicity; mammographic density; risk factor
14.  Mammographic density, parity and age at first birth, and risk of breast cancer: an analysis of four case-control studies 
Breast Cancer Research and Treatment  2012;132(3):1163-1171.
Mammographic density is strongly and consistently associated with breast cancer risk. To determine if this association was modified by reproductive factors (parity and age at first birth), data were combined from four case-control studies conducted in the United States and Japan. To overcome the issue of variation in mammographic density assessment among the studies, a single observer re-read all the mammograms using one type of interactive thresholding software. Logistic regression was used to estimate odds ratios (OR) while adjusting for other known breast cancer risk factors. Included were 1699 breast cancer cases and 2422 controls, 74% of whom were postmenopausal. A positive association between mammographic density and breast cancer risk was evident in every group defined by parity and age at first birth (OR per doubling of percent mammographic density ranged between 1.20 and 1.39). Nonetheless, the association appeared to be stronger among nulliparous than parous women (OR per doubling of percent mammographic density = 1.39 vs 1.24; P-interaction = 0.054). However, when examined by study location, the effect modification by parity was apparent only in women from Hawaii and when examined by menopausal status, it was apparent in postmenopausal, but not premenopausal, women. Effect modification by parity was not significant in subgroups defined by body mass index or ethnicity. Adjusting for mammographic density did not attenuate the OR for the association between parity and breast cancer risk by more than 16.4% suggesting that mammographic density explains only a small proportion of the reduction in breast cancer risk associated with parity. In conclusion, this study did not support the hypothesis that parity modifies the breast cancer risk attributed to mammographic density. Even though an effect modification was found in Hawaiian women, none was found in women from the other three locations.
doi:10.1007/s10549-011-1929-9
PMCID: PMC3336030  PMID: 22222356
Breast neoplasms; mammographic density; reproductive factors; epidemiology; risk factor; effect modification
15.  Common Breast Cancer Susceptibility Variants in LSP1 and RAD51L1 Are Associated with Mammographic Density Measures that Predict Breast Cancer Risk 
Vachon, Celine M. | Scott, Christopher G. | Fasching, Peter A. | Hall, Per | Tamimi, Rulla M. | Li, Jingmei | Stone, Jennifer | Apicella, Carmel | Odefrey, Fabrice | Gierach, Gretchen L. | Jud, Sebastian M. | Heusinger, Katharina | Beckmann, Matthias W. | Pollan, Marina | Fernández-Navarro, Pablo | González-Neira, Anna | Benítez, Javier | van Gils, Carla H. | Lokate, Mariëtte | Onland-Moret, N. Charlotte | Peeters, Petra H.M. | Brown, Judith | Leyland, Jean | Varghese, Jajini S. | Easton, Douglas F. | Thompson, Deborah J. | Luben, Robert N. | Warren, Ruth ML | Wareham, Nicholas J. | Loos, Ruth JF | Khaw, Kay-Tee | Ursin, Giske | Lee, Eunjung | Gayther, Simon A. | Ramus, Susan J. | Eeles, Rosalind A. | Leach, Martin O. | Kwan-Lim, Gek | Couch, Fergus J. | Giles, Graham G. | Baglietto, Laura | Krishnan, Kavitha | Southey, Melissa C. | Le Marchand, Loic | Kolonel, Laurence N. | Woolcott, Christy | Maskarinec, Gertraud | Haiman, Christopher A | Walker, Kate | Johnson, Nichola | McCormack, Valerie A. | Biong, Margarethe | Alnæs, Grethe I.G. | Gram, Inger Torhild | Kristensen, Vessela N. | Børresen-Dale, Anne-Lise | Lindström, Sara | Hankinson, Susan E. | Hunter, David J. | Andrulis, Irene L. | Knight, Julia A. | Boyd, Norman F. | Figueroa, Jonine D. | Lissowska, Jolanta | Wesolowska, Ewa | Peplonska, Beata | Bukowska, Agnieszka | Reszka, Edyta | Liu, JianJun | Eriksson, Louise | Czene, Kamila | Audley, Tina | Wu, Anna H. | Pankratz, V. Shane | Hopper, John L. | dos-Santos-Silva, Isabel
Background
Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biological mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to inter-individual differences in mammographic density measures.
Methods
We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and non-dense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, body mass index (BMI) and menopausal status.
Results
Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (p=0.00005) and adjusted percent density (p=0.001) whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (p=0.003), but not with adjusted dense area (p=0.07).
Conclusion
We identified two common breast cancer susceptibility variants associated with mammographic measures of radio-dense tissue in the breast gland.
Impact
We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.
doi:10.1158/1055-9965.EPI-12-0066
PMCID: PMC3569092  PMID: 22454379
breast density; breast cancer; genetics; biomarkers; mammography
16.  Adult daughters’ reports of breast cancer risk reduction and early detection advice received from their mothers: an exploratory study (formerly entitled: Family communication about breast cancer prevention as reported by adult daughters in the Minnesota Breast Cancer Family Study) 
Psycho-oncology  2009;18(2):169-178.
Objective
Awareness of cancer family history is dependent upon communication between family members. Communication of this information and related decision-making could be important factors influencing breast cancer risk reduction and early detection behaviors. Using survey data from 2,328 women (mean age 62.5 years) from 372 families enrolled in the Minnesota breast cancer family study, we explored adult daughter’s reports of breast cancer risk reduction advice received from their mothers.
Methods and Results
Approximately 212 (9%) of respondents reported receiving breast cancer risk reduction advice from their mothers and 130 (89%) reported acting upon such advice. Having a mother or first degree relative (FDR) with a history of breast cancer was significantly correlated with following advice to a higher degree as compared to those not having such family history (p=0.003).
Most frequently reported types of advice were to have mammograms (36%) and to have clinical breast exams (35%). Using multivariable logistic regression and after accounting for non-independence of the sample, significant independent correlates of receiving advice included younger age, having an affected mother, and having a higher perceived breast cancer risk. Receiving advice was also correlated with engaging in a higher number of health promoting behaviors and ever having received a mammogram.
Conclusions
Our preliminary findings are consistent with social influence theory and suggest that mother-daughter communication about reducing risk, especially among those having a FDR with breast cancer, could be a potential pathway through which BC family history is associated with the adoption of breast cancer screening and risk reduction behaviors.
doi:10.1002/pon.1393
PMCID: PMC3562088  PMID: 18636437
breast cancer; communication; family; social influence; mammography; psychosocial
17.  Comparison of percent density from raw and processed full-field digital mammography data 
Introduction
Mammographic density has been established as a strong risk factor for breast cancer, primarily using digitized film mammograms. Full-field digital mammography (FFDM) is replacing film mammography, has different properties than film, and provides both raw and processed clinical display representation images. We evaluated and compared FFDM raw and processed breast density measures and their associations with breast cancer.
Methods
A case-control study of 180 cases and 180 controls matched by age, postmenopausal hormone use, and screening history was conducted. Mammograms were acquired from a General Electric Senographe 2000D FFDM unit. Percent density (PD) was assessed for each FFDM representation using the operator-assisted Cumulus method. Reproducibility within image type (n = 80) was assessed using Lin's concordance correlation coefficient (rc). Correlation of PD between image representations (n = 360) was evaluated using Pearson's correlation coefficient (r) on the continuous measures and the weighted kappa statistic (κ) for quartiles. Conditional logistic regression was used to estimate odds ratios (ORs) for the PD and breast cancer associations for both image representations with 95% confidence intervals. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminatory accuracy.
Results
Percent density from the two representations provided similar intra-reader reproducibility (rc= 0.92 for raw and rc= 0.87 for processed images) and was correlated (r = 0.82 and κ = 0.64). When controlling for body mass index, the associations of quartiles of PD with breast cancer and discriminatory accuracy were similar for the raw (OR: 1.0 (ref.), 2.6 (1.2 to 5.4), 3.1 (1.4 to 6.8), 4.7 (2.1 to 10.6); AUC = 0.63) and processed representations (OR: 1.0 (ref.), 2.2 (1.1 to 4.1), 2.2 (1.1 to 4.4), 3.1 (1.5 to 6.6); AUC = 0.64).
Conclusions
Percent density measured with an operator-assisted method from raw and processed FFDM images is reproducible and correlated. Both percent density measures provide similar associations with breast cancer.
doi:10.1186/bcr3372
PMCID: PMC3672765  PMID: 23289950
18.  A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor–negative breast cancer 
Haiman, Christopher A | Chen, Gary K | Vachon, Celine M | Canzian, Federico | Dunning, Alison | Millikan, Robert C | Wang, Xianshu | Ademuyiwa, Foluso | Ahmed, Shahana | Ambrosone, Christine B | Baglietto, Laura | Balleine, Rosemary | Bandera, Elisa V | Beckmann, Matthias W | Berg, Christine D | Bernstein, Leslie | Blomqvist, Carl | Blot, William J | Brauch, Hiltrud | Buring, Julie E | Carey, Lisa A | Carpenter, Jane E | Chang-Claude, Jenny | Chanock, Stephen J | Chasman, Daniel I | Clarke, Christine L | Cox, Angela | Cross, Simon S | Deming, Sandra L | Diasio, Robert B | Dimopoulos, Athanasios M | Driver, W Ryan | Dünnebier, Thomas | Durcan, Lorraine | Eccles, Diana | Edlund, Christopher K | Ekici, Arif B | Fasching, Peter A | Feigelson, Heather S | Flesch-Janys, Dieter | Fostira, Florentia | Försti, Asta | Fountzilas, George | Gerty, Susan M | Giles, Graham G | Godwin, Andrew K | Goodfellow, Paul | Graham, Nikki | Greco, Dario | Hamann, Ute | Hankinson, Susan E | Hartmann, Arndt | Hein, Rebecca | Heinz, Judith | Holbrook, Andrea | Hoover, Robert N | Hu, Jennifer J | Hunter, David J | Ingles, Sue A | Irwanto, Astrid | Ivanovich, Jennifer | John, Esther M | Johnson, Nicola | Jukkola-Vuorinen, Arja | Kaaks, Rudolf | Ko, Yon-Dschun | Kolonel, Laurence N | Konstantopoulou, Irene | Kosma, Veli-Matti | Kulkarni, Swati | Lambrechts, Diether | Lee, Adam M | Le Marchand, Loïc | Lesnick, Timothy | Liu, Jianjun | Lindstrom, Sara | Mannermaa, Arto | Margolin, Sara | Martin, Nicholas G | Miron, Penelope | Montgomery, Grant W | Nevanlinna, Heli | Nickels, Stephan | Nyante, Sarah | Olswold, Curtis | Palmer, Julie | Pathak, Harsh | Pectasides, Dimitrios | Perou, Charles M | Peto, Julian | Pharoah, Paul D P | Pooler, Loreall C | Press, Michael F | Pylkäs, Katri | Rebbeck, Timothy R | Rodriguez-Gil, Jorge L | Rosenberg, Lynn | Ross, Eric | Rüdiger, Thomas | Silva, Isabel dos Santos | Sawyer, Elinor | Schmidt, Marjanka K | Schulz-Wendtland, Rüdiger | Schumacher, Fredrick | Severi, Gianluca | Sheng, Xin | Signorello, Lisa B | Sinn, Hans-Peter | Stevens, Kristen N | Southey, Melissa C | Tapper, William J | Tomlinson, Ian | Hogervorst, Frans B L | Wauters, Els | Weaver, JoEllen | Wildiers, Hans | Winqvist, Robert | Van Den Berg, David | Wan, Peggy | Xia, Lucy Y | Yannoukakos, Drakoulis | Zheng, Wei | Ziegler, Regina G | Siddiq, Afshan | Slager, Susan L | Stram, Daniel O | Easton, Douglas | Kraft, Peter | Henderson, Brian E | Couch, Fergus J
Nature Genetics  2011;43(12):1210-1214.
Estrogen receptor (ER)-negative breast cancer shows a higher incidence in women of African ancestry compared to women of European ancestry. In search of common risk alleles for ER-negative breast cancer, we combined genome-wide association study (GWAS) data from women of African ancestry (1,004 ER-negative cases and 2,745 controls) and European ancestry (1,718 ER-negative cases and 3,670 controls), with replication testing conducted in an additional 2,292 ER-negative cases and 16,901 controls of European ancestry. We identified a common risk variant for ER-negative breast cancer at the TERT-CLPTM1L locus on chromosome 5p15 (rs10069690: per-allele odds ratio (OR) = 1.18 per allele, P = 1.0 × 10−10). The variant was also significantly associated with triple-negative (ER-negative, progesterone receptor (PR)-negative and human epidermal growth factor-2 (HER2)-negative) breast cancer (OR = 1.25, P = 1.1 × 10−9), particularly in younger women (<50 years of age) (OR = 1.48, P = 1.9 × 10−9). Our results identify a genetic locus associated with estrogen receptor negative breast cancer subtypes in multiple populations.
doi:10.1038/ng.985
PMCID: PMC3279120  PMID: 22037553
19.  Evaluation of associations between common variation in mitotic regulatory pathways and risk of overall and high grade breast cancer 
Mitotic regulatory pathways ensure proper timing of mitotic entry, sister chromatid cohesion and separation, and cytokinesis. Disruption of this process results in inappropriate chromosome segregation and aneuploidy and appears to contribute to cancer. Specifically, disregulation and somatic mutation of mitotic regulators has been observed in human cancers, and overexpression of mitotic regulators is common in aggressive and late stage tumors. However, the role of germline variation in mitotic pathways and risk of cancer is not well understood. We tested 1,084 haplotype-tagging and functional variants from 164 genes in mitotic regulatory pathways in 791 Caucasian women with breast cancer and 843 healthy controls for association with risk of overall and high grade breast cancer. Sixty-one single nucleotide polymorphisms (SNPs) from 40 genes were associated (p<0.05) with risk of breast cancer in a log-additive model. In addition 60 SNPs were associated (p<0.05) with risk of high grade breast cancer. However, none of these associations were significant after Bonferroni correction for multiple testing. In gene-level analyses, CDC25C, SCC1/RAD21, TLK2, and SMC6L1 were associated (p<0.05) with overall breast cancer risk, CDC6, CDC27, SUMO3, RASSF1, KIF2, and CDC14A were associated with high grade breast cancer risk, and EIF3S10 and CDC25A were associated with both. Further investigation in breast and other cancers are needed to understand the influence of inherited variation in mitotic genes on tumor grade and cancer risk.
doi:10.1007/s10549-011-1587-y
PMCID: PMC3508696  PMID: 21607584
breast cancer; genetics; mitotic; grade
20.  19p13.1 is a triple negative-specific breast cancer susceptibility locus 
Stevens, Kristen N. | Fredericksen, Zachary | Vachon, Celine M. | Wang, Xianshu | Margolin, Sara | Lindblom, Annika | Nevanlinna, Heli | Greco, Dario | Aittomäki, Kristiina | Blomqvist, Carl | Chang-Claude, Jenny | Vrieling, Alina | Flesch-Janys, Dieter | Sinn, Hans-Peter | Wang-Gohrke, Shan | Nickels, Stefan | Brauch, Hiltrud | Ko, Yon-Dschun | Fischer, Hans-Peter | Schmutzler, Rita K. | Meindl, Alfons | Bartram, Claus R. | Schott, Sarah | Engel, Christof | Godwin, Andrew K. | Weaver, JoEllen | Pathak, Harsh B. | Sharma, Priyanka | Brenner, Hermann | Müller, Heiko | Arndt, Volker | Stegmaier, Christa | Miron, Penelope | Yannoukakos, Drakoulis | Stavropoulou, Alexandra | Fountzilas, George | Gogas, Helen J. | Swann, Ruth | Dwek, Miriam | Perkins, Annie | Milne, Roger L. | Benítez, Javier | Zamora, M Pilar | Pérez, José Ignacio Arias | Bojesen, Stig E. | Nielsen, Sune F. | Nordestgaard, Børge G | Flyger, Henrik | Guénel, Pascal | Truong, Thérèse | Menegaux, Florence | Cordina-Duverger, Emilie | Burwinkel, Barbara | Marmé, Frederick | Schneeweiss, Andreas | Sohn, Christof | Sawyer, Elinor | Tomlinson, Ian | Kerin, Michael J. | Peto, Julian | Johnson, Nichola | Fletcher, Olivia | Silva, Isabel dos Santos | Fasching, Peter A. | Beckmann, Matthias W. | Hartmann, Arndt | Ekici, Arif B. | Lophatananon, Artitaya | Muir, Kenneth | Puttawibul, Puttisak | Wiangnon, Surapon | Schmidt, Marjanka K | Broeks, Annegien | Braaf, Linde M | Rosenberg, Efraim H | Hopper, John L. | Apicella, Carmel | Park, Daniel J. | Southey, Melissa C. | Swerdlow, Anthony J. | Ashworth, Alan | Orr, Nicholas | Schoemaker, Minouk J. | Anton-Culver, Hoda | Ziogas, Argyrios | Bernstein, Leslie | Dur, Christina Clarke | Shen, Chen-Yang | Yu, Jyh-Cherng | Hsu, Huan-Ming | Hsiung, Chia-Ni | Hamann, Ute | Dünnebier, Thomas | Rüdiger, Thomas | Ulmer, Hans Ulrich | Pharoah, Paul P. | Dunning, Alison M | Humphreys, Manjeet K. | Wang, Qin | Cox, Angela | Cross, Simon S. | Reed, Malcom W. | Hall, Per | Czene, Kamila | Ambrosone, Christine B. | Ademuyiwa, Foluso | Hwang, Helena | Eccles, Diana M. | Garcia-Closas, Montserrat | Figueroa, Jonine D. | Sherman, Mark E. | Lissowska, Jolanta | Devilee, Peter | Seynaeve, Caroline | Tollenaar, R.A.E.M. | Hooning, Maartje J. | Andrulis, Irene L. | Knight, Julia A. | Glendon, Gord | Mulligan, Anna Marie | Winqvist, Robert | Pylkäs, Katri | Jukkola-Vuorinen, Arja | Grip, Mervi | John, Esther M. | Miron, Alexander | Alnæs, Grethe Grenaker | Kristensen, Vessela | Børresen-Dale, Anne-Lise | Giles, Graham G. | Baglietto, Laura | McLean, Catriona A | Severi, Gianluca | Kosel, Matthew L. | Pankratz, V.S. | Slager, Susan | Olson, Janet E. | Radice, Paolo | Peterlongo, Paolo | Manoukian, Siranoush | Barile, Monica | Lambrechts, Diether | Hatse, Sigrid | Dieudonne, Anne-Sophie | Christiaens, Marie-Rose | Chenevix-Trench, Georgia | Beesley, Jonathan | Chen, Xiaoqing | Mannermaa, Arto | Kosma, Veli-Matti | Hartikainen, Jaana M. | Soini, Ylermi | Easton, Douglas F. | Couch, Fergus J.
Cancer Research  2012;72(7):1795-1803.
The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with risk of ovarian cancer. Here we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 Odds Ratio (OR)=1.10, 95% Confidence Interval (CI) 1.05 – 1.15, p=3.49 × 10-5] and triple negative (TN) (ER, PR and HER2 negative) breast cancer [rs8170 OR=1.22, 95% CI 1.13 – 1.31, p=2.22 × 10-7]. However, rs8170 was no longer associated with ER-negative breast cancer risk when TN cases were excluded [OR=0.98, 95% CI 0.89 – 1.07, p=0.62]. In addition, a combined analysis of TN cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC) (n=3,566) identified a genome-wide significant association between rs8170 and TN breast cancer risk [OR=1.25, 95% CI 1.18 – 1.33, p=3.31 × 10-13]. Thus, 19p13.1 is the first triple negative-specific breast cancer risk locus and the first locus specific to a histological subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple negative tumors and other subtypes likely arise through distinct etiologic pathways.
doi:10.1158/0008-5472.CAN-11-3364
PMCID: PMC3319792  PMID: 22331459
genetic susceptibility; association study; subtype; neoplasms; common variant
21.  Mammographic breast density and breast cancer: evidence of a shared genetic basis 
Cancer research  2012;72(6):1478-1484.
Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3628 breast cancer cases and 5190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of SNPs were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using ten different cut-offs for the most significant density SNPs (1-10% representing 5,222-50,899 SNPs). Permutation analysis was also performed across all 10 cut-offs. The association between risk score and breast cancer was significant for all cut-offs from 3-10% of top density SNPs, being most significant for the 6% (2-sided P=0.002) to 10% (P=0.001) cut-offs (overall permutation P=0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR= 1.31 (95%CI 1.08-1.59)] compared to women in the bottom 10%. Together, our results demonstrate that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants.
doi:10.1158/0008-5472.CAN-11-3295
PMCID: PMC3378688  PMID: 22266113
breast cancer; mammographic density; SNPs; polygenic; Mendelian Randomisation
22.  Evaluating the Influence of Quality Control Decisions and Software Algorithms on SNP Calling for the Affymetrix 6.0 SNP Array Platform 
Human Heredity  2011;71(4):221-233.
Objective
Our goal was to evaluate the influence of quality control (QC) decisions using two genotype calling algorithms, CRLMM and Birdseed, designed for the Affymetrix SNP Array 6.0.
Methods
Various QC options were tried using the two algorithms and comparisons were made on subject and call rate and on association results using two data sets.
Results
For Birdseed, we recommend using the contrast QC instead of QC call rate for sample QC. For CRLMM, we recommend using the signal-to-noise rate ≥4 for sample QC and a posterior probability of 90% for genotype accuracy. For both algorithms, we recommend calling the genotype separately for each plate, and dropping SNPs with a lower call rate (<95%) before evaluating samples with lower call rates. To investigate whether the genotype calls from the two algorithms impacted the genome-wide association results, we performed association analysis using data from the GENOA cohort; we observed that the number of significant SNPs were similar using either CRLMM or Birdseed.
Conclusions
Using our suggested workflow both algorithms performed similarly; however, fewer samples were removed and CRLMM took half the time to run our 854 study samples (4.2 h) compared to Birdseed (8.4 h).
doi:10.1159/000328843
PMCID: PMC3136375  PMID: 21734406
Genotype call; Birdseed; CRLMM; Quality control decisions; Association
23.  Histologic Findings in Normal Breast Tissues: Comparison to Reduction Mammaplasty and Benign Breast Disease Tissues 
Background
Investigations of breast carcinogenesis often rely upon comparisons between cancer tissue and nonmalignant breast tissue. It is unclear how well common reference sources of nonmalignant breast tissues reflect normal breast tissue.
Methods
Breast tissue samples were evaluated from three sources: 1) normal donor tissues in the Susan G. Komen for the Cure® Tissue Bank at Indiana University Simon Cancer Center (KTB), 2) women who underwent reduction mammaplasty (RM) at Mayo Clinic Rochester, and 3) the Mayo Clinic Benign Breast Disease Cohort Study (BBD). Samples were examined histologically and assessed for proliferative disease and degree of lobular involution. Univariate comparisons were performed among the study groups, and multivariate analyses were performed with logistic regression to assess the association between study group and the presence of epithelial proliferative disease and complete lobular involution.
Results
Histologic data were collected for 455 KTB samples, 259 RM samples, and 319 BBD samples. Histologic findings and the frequency of epithelial proliferation were significantly different among the groups. Histologic abnormalities were seen in a minority of the KTB samples (35%), whereas an abnormality was present in 88% of RM tissues and 97.5% of BBD samples. The presence of proliferative disease (with or without atypical hyperplasia) was present in 3.3% of normal donors (3.3%), 17% of RM samples, and 34.9% of BBD samples, (p<0.0001 for each comparison). Multivariate analyses confirmed that these differences remained significant and also showed higher likelihood of complete lobular involution in the normal donor samples compared to RM and BBD tissues.
Conclusion
Compared to benign breast disease tissues and reduction mammaplasty tissues, breast tissue samples from normal donors have significantly fewer histologic abnormalities and a higher frequency of more complete lobular involution. Breast tissue samples from normal donors represent a unique tissue resource with histologic features consistent with lower breast cancer risk.
doi:10.1007/s10549-011-1746-1
PMCID: PMC3242875  PMID: 21881938
24.  Common breast cancer susceptibility loci are associated with triple negative breast cancer 
Stevens, Kristen N. | Vachon, Celine M. | Lee, Adam M. | Slager, Susan | Lesnick, Timothy | Olswold, Curtis | Fasching, Peter A. | Miron, Penelope | Eccles, Diana | Carpenter, Jane E. | Godwin, Andrew K. | Ambrosone, Christine | Winqvist, Robert | Schmidt, Marjanka K. | Cox, Angela | Cross, Simon S. | Sawyer, Elinor | Hartmann, Arndt | Beckmann, Matthias W. | Schulz-Wendtland, Rüdiger | Ekici, Arif B. | Tapper, William J | Gerty, Susan M | Durcan, Lorraine | Graham, Nikki | Hein, Rebecca | Nickels, Stephan | Flesch-Janys, Dieter | Heinz, Judith | Sinn, Hans-Peter | Konstantopoulou, Irene | Fostira, Florentia | Pectasides, Dimitrios | Dimopoulos, Athanasios M. | Fountzilas, George | Clarke, Christine L. | Balleine, Rosemary | Olson, Janet E. | Fredericksen, Zachary | Diasio, Robert B. | Pathak, Harsh | Ross, Eric | Weaver, JoEllen | Rüdiger, Thomas | Försti, Asta | Dünnebier, Thomas | Ademuyiwa, Foluso | Kulkarni, Swati | Pylkäs, Katri | Jukkola-Vuorinen, Arja | Ko, Yon-Dschun | Van Limbergen, Erik | Janssen, Hilde | Peto, Julian | Fletcher, Olivia | Giles, Graham G. | Baglietto, Laura | Verhoef, Senno | Tomlinson, Ian | Kosma, Veli-Matti | Beesley, Jonathan | Greco, Dario | Blomqvist, Carl | Irwanto, Astrid | Liu, Jianjun | Blows, Fiona M. | Dawson, Sarah-Jane | Margolin, Sara | Mannermaa, Arto | Martin, Nicholas G. | Montgomery, Grant W | Lambrechts, Diether | dos Santos Silva, Isabel | Severi, Gianluca | Hamann, Ute | Pharoah, Paul | Easton, Douglas F. | Chang-Claude, Jenny | Yannoukakos, Drakoulis | Nevanlinna, Heli | Wang, Xianshu | Couch, Fergus J.
Cancer Research  2011;71(19):6240-6249.
Triple negative breast cancers are an aggressive subtype of breast cancer with poor survival, but there remains little known about the etiological factors which promote its initiation and development. Commonly inherited breast cancer risk factors identified through genome wide association studies (GWAS) display heterogeneity of effect among breast cancer subtypes as defined by estrogen receptor (ER) and progesterone receptor (PR) status. In the Triple Negative Breast Cancer Consortium (TNBCC), 22 common breast cancer susceptibility variants were investigated in 2,980 Caucasian women with triple negative breast cancer and 4,978 healthy controls. We identified six single nucleotide polymorphisms (SNPs) significantly associated with risk of triple negative breast cancer, including rs2046210 (ESR1), rs12662670 (ESR1), rs3803662 (TOX3), rs999737 (RAD51L1), rs8170 (19p13.11) and rs8100241 (19p13.11). Together, our results provide convincing evidence of genetic susceptibility for triple negative breast cancer.
doi:10.1158/0008-5472.CAN-11-1266
PMCID: PMC3327299  PMID: 21844186
genetic susceptibility; neoplasms; association study; subtypes; common variant
25.  Effect of Aspirin and other NSAIDs on Postmenopausal Breast Cancer Incidence by Hormone Receptor Status: Results from a Prospective Cohort Study 
Purpose
Aspirin and other non-aspirin non-steroidal anti-inflammatory drugs (NSAIDs) can inhibit aromatase activity and thus could selectively lower incidence of hormone receptor positive tumors. We assessed whether the association of aspirin and other NSAIDs with postmenopausal breast cancer risk differs by estrogen and progesterone receptor (ER, PR) status of the tumor.
Methods
A population-based cohort of 26,580 postmenopausal women was linked to a SEER Cancer Registry to identify incident breast cancers. Regular use of aspirin and other NSAIDs was reported on a self-administered questionnaire mailed in 1992. Cox proportional hazards models were used to estimate multivariate relative risks (RRs) and 95% confidence intervals (CIs) of breast cancer incidence overall and by ER and PR status, adjusting for multiple breast cancer risk factors.
Results
Through 2005, 1,581 incident breast cancer cases were observed. Compared to aspirin never users, women who regularly consumed aspirin had a lower risk of breast cancer (RR=0.80; 95% CI: 0.71–0.90), and there was evidence for lower risk with increasing frequency of use (RR=0.71 for aspirin use 6 or more times/week versus never use; p-trend=0.00001). Inverse associations for regular aspirin use were observed for ER+ (RR=0.77; 95% CI 0.67–0.89), ER− (RR=0.78; 95% CI 0.56–1.08), PR+ (RR=0.79; 95% CI 0.68–0.92), and PR− (RR=0.73; 95% CI 0.56–0.95) breast cancers. In contrast, use of other NSAIDs was not associated with breast cancer incidence overall (RR=0.95, 95% CI: 0.85–1.07), or by ER or PR status.
Conclusions
Aspirin, but not other NSAID use, was associated with about 20% lower risk of postmenopausal breast cancer and did not vary by ER or PR status of the tumor, suggesting that the hypothesized protective effects of aspirin may either be through cellular pathways independent of estrogen or progesterone signaling, or on tumor microenvironment.
doi:10.1007/s10549-010-1074-x
PMCID: PMC2997337  PMID: 20669045
breast cancer; aspirin; NSAIDs; hormone receptors; prevention

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