17 research outputs found

    Associations of aspirin and other anti-inflammatory medications with breast cancer risk by the status of COX-2 expression

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    BACKGROUND: We investigated the associations of aspirin and other nonsteroidal anti-inflammatory drugs (NSAIDs) with breast cancer risk by the status of COX-2 protein expression. METHODS: This study included 421 cases and 3,166 controls from a nested case-control study within the Nurses\u27 Health Study (NHS) and Nurses\u27 Health Study II (NHSII) cohorts. Information on medication use was first collected in 1980 (NHS) and 1989 (NHSII) and was updated biennially. Medication use was defined as none, past or current; average cumulative dose and frequency were calculated for all past or current users using data collected from all biannual questionnaires preceding the reference date. Immunochemistry for COX-2 expression was performed using commercial antibody (Cayman Chemical and Thermo Fisher Scientific). We used polychotomous logistic regression to quantify associations of aspirin and NSAIDs with the risk of COX2+ and COX2- breast cancer tumors, while adjusting for known breast cancer risk factors. All tests of statistical significance were two-sided. RESULTS: In multivariate analysis, we found no differences in associations of the aspirin exposures and NSAIDs with breast cancer risk by COX2 expression status. In stratified analyses by COX2 status, significant associations of these medications with breast cancer risk were observed for dosage of aspirin among current users in COX2- tumors (OR for \u3e 5 tablets per week vs. none 1.71, 95% CI 1.01-2.88, p-trend 0.04). Regular aspirin use was marginally associated with the risk of COX2- tumors (p-trend = 0.06). CONCLUSIONS: Our findings suggested no differences in associations of aspirin and other NSAIDs with COX2+ and COX2- tumors

    Tissue-based associations of mammographic breast density with breast stem cell markers

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    Abstract Background Mammographic breast density is a well-established, strong breast cancer risk factor but the biology underlying this association remains unclear. Breast density may reflect underlying alterations in the size and activity of the breast stem cell pool. We examined, for the first time, associations of CD44, CD24, and aldehyde dehydrogenase family 1 member A1 (ALDH1A1) breast stem cell markers with breast density. Methods We included in this study 64 asymptomatic healthy women who previously volunteered for a unique biopsy study of normal breast tissue at the Mayo Clinic (2006-2008). Mammographically identified dense and non-dense areas were confirmed/localized by ultrasound and biopsied. Immunohistochemical analysis of the markers was performed according to a standard protocol and the staining was assessed by a single blinded pathologist. In core biopsy samples retrieved from areas of high vs. low density within the same woman, we compared staining extent and an expression score (the product of staining intensity and extent), using the signed rank test. All tests of statistical significance were two-sided. Results A total of 64, 28, and 10 women were available for CD44, CD24, and ALDH1A1 staining, respectively. For all three markers, we found higher levels of staining extent in dense as compared to non-dense tissue, though for CD24 and ALDH1A1 the difference did not reach statistical significance (CD44, 6.3% vs. 2.0%, p < 0.001; CD24, 8.0% vs. 5.6%, p = 0.10; and ALDH1A1, 0.5% vs. 0.3%, p = 0.12). The expression score for CD44 was significantly greater in dense as compared to non-dense tissue (9.8 vs.3.0, p < 0.001). Conclusions Our findings suggest an increased presence and/or activity of stem cells in dense as compared to non-dense breast tissue

    Data_Sheet_1_Reliability of CD44, CD24, and ALDH1A1 immunohistochemical staining: Pathologist assessment compared to quantitative image analysis.doc

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    BackgroundThe data on the expression of stem cell markers CD44, CD24, and ALDH1A1 in the breast tissue of cancer-free women is very limited and no previous studies have explored the agreement between pathologist and computational assessments of these markers. We compared the immunohistochemical (IHC) expression assessment for CD44, CD24, and ALDH1A1 by an expert pathologist with the automated image analysis results and assessed the homogeneity of the markers across multiple cores pertaining to each woman.MethodsWe included 81 cancer-free women (399 cores) with biopsy-confirmed benign breast disease in the Nurses’ Health Study (NHS) and NHSII cohorts. IHC was conducted with commercial antibodies [CD44 (Dako, Santa Clara, CA, USA) 1:25 dilution; CD24 (Invitrogen, Waltham, MA, USA) 1:200 dilution and ALDH1A1 (Abcam, Cambridge, United Kingdom) 1:300 dilution]. For each core, the percent positivity was quantified by the pathologist and Definiens Tissue Studio. Correlations between pathologist and computational scores were evaluated with Spearman correlation (for categorical positivity: 0, >0–10–50, and >50%) and sensitivity/specificity (for binary positivity defined with 1 and 10% cut-offs), using the pathologist scores as the gold standard. Expression homogeneity was examined with intra-class correlation (ICC). Analyses were stratified by core [normal terminal duct-lobular units (TDLUs), benign lesions] and tissue type (epithelium, stroma).ResultsSpearman correlation between pathologist and Definiens ranged between 0.40–0.64 for stroma and 0.66–0.68 for epithelium in normal TDLUs cores and between 0.24–0.60 for stroma and 0.61–0.64 for epithelium in benign lesions. For stroma, sensitivity and specificity ranged between 0.92–0.95 and 0.24–0.60, respectively, with 1% cut-off and between 0.43–0.88 and 0.73–0.85, respectively, with 10% cut-off. For epithelium, 10% cut-off resulted in better estimates for both sensitivity and specificity. ICC between the cores was strongest for CD44 for both stroma and epithelium in normal TDLUs cores and benign lesions (range 0.74–0.80). ICC for CD24 and ALDH1A ranged between 0.42–0.63 and 0.44–0.55, respectively.ConclusionOur findings show that computational assessments for CD44, CD24, and ALDH1A1 exhibit variable correlations with manual assessment. These findings support the use of computational platforms for IHC evaluation of stem cell markers in large-scale epidemiologic studies. Pilot studies maybe also needed to determine appropriate cut-offs for defining staining positivity.</p

    Postmenopausal mammographic breast density and subsequent breast cancer risk according to selected tissue markers

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    Background: This study aimed to determine if associations of pre-diagnostic percent breast density, absolute dense area, and non-dense area with subsequent breast cancer risk differ by the tumour's molecular marker status. Methods: We included 1010 postmenopausal women with breast cancer and 2077 matched controls from the Nurses' Health Study (NHS) and the Nurses' Health Study II (NHS II) cohorts. Breast density was estimated from digitised film mammograms using computer-assisted thresholding techniques. Information on breast cancer risk factors was obtained prospectively from biennial questionnaires. Polychotomous logistic regression was used to assess associations of breast density measures with tumour subtypes by the status of selected tissue markers. All tests of statistical significance were two sided. Results: The association of percent density with breast cancer risk appeared to be stronger in ER− as compared with ER+ tumours, but the difference did not reach statistical significance (density ⩾50% vs <10% odds ratio (OR)=3.06, 95% confidence interval (CI) 2.17–4.32 for ER+ OR=4.61, 95% CI 2.36–9.03 for ER−, Pheterogeneity=0.08). Stronger positive associations were found for absolute dense area and CK5/6− and EGFR− as compared with respective marker-positive tumours (Pheterogeneity=0.002 and 0.001, respectively). Stronger inverse associations of non-dense area with breast cancer risk were found for ER− as compared with ER+ tumours (Pheterogeneity=0.0001) and for AR+, CK5/6+, and EGFR+ as compared with respective marker-negative tumours (Pheterogeneity=0.03, 0.005, and 0.009, respectively). The associations of density measures with breast cancer did not differ by progesterone receptor and human epidermal growth factor receptor 2 status. Conclusions: Breast density influences the risk of breast cancer subtypes by potentially different mechanisms
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