Homo sapiens
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PROVIDER: PRJNA215168 | ENA |
REPOSITORIES: ENA
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Project description:Purpose: Previous studies of breast tissue gene expression have demonstrated that the extratumoral microenvironment has substantial variability across individuals, some of which can be attributed to epidemiologic factors. To evaluate how mammographic density (MD) and breast tissue composition relate to extratumoral microenvironment gene expression, we used data on 121 breast cancer patients from the population-based Polish Women’s Breast Cancer Study.Design: Breast cancer cases were classified based on a previously reported, biologically-defined extratumoral gene expression signature with two subtypes: an Active subtype, which is associated with high expression of genes related to fibrosis and wound response, and an Inactive subtype, which has high expression of cellular adhesion genes. MD of the contralateral breast was assessed using pre-treatment mammograms and a quantitative, reliable computer-assisted thresholding method. Breast tissue composition was evaluated based on digital image analysis of tissue sections. Results:The Inactive extratumoral subtype was associated with significantly higher percentage mammographic density (PD) and dense area (DA) in univariate analysis (PD: p=0.001; DA: p=0.049) and in multivariable analyses adjusted for age and body mass index (PD: p=0.004; DA: p=0.049). Inactive/higher MD tissue was characterized by a significantly higher percentage of stroma and a significantly lower percentage of adipose tissue, with no significant change in epithelial content. Analysis of published gene expression signatures suggested that Inactive/higher MD tissue expressed increased estrogen response and decreased TGF-ß signaling. Conclusions:By linking novel molecular phenotypes with MD, our results indicate that MD reflects broad transcriptional changes, including changes in both epithelia- and stroma-derived signaling.
2013-10-21 | GSE49175 | GEO
Project description:High mammographic density (MD) is associated with a 4-6 times increase in breast cancer risk. MD often decreases over time, but little is known about the corresponding biological mechanisms. We obtained biopsies from breasts of healthy women at two different time points years apart. After RNA isolation, Agilent Sureprint G3 Human Gene Expression 8x60K microarrays were performed. Mammographic density was calculated based on mammograms. We explored associations between clinical parameters, MD and gene expression and performed microenvironment tissue subtyping. Gene expression data from previous biopsies are deposited separately.
2019-01-01 | E-MTAB-5885 | biostudies-arrayexpress
Project description:Purpose: Previous studies of breast tissue gene expression have demonstrated that the extratumoral microenvironment has substantial variability across individuals, some of which can be attributed to epidemiologic factors. To evaluate how mammographic density (MD) and breast tissue composition relate to extratumoral microenvironment gene expression, we used data on 121 breast cancer patients from the population-based Polish Women’s Breast Cancer Study.Design: Breast cancer cases were classified based on a previously reported, biologically-defined extratumoral gene expression signature with two subtypes: an Active subtype, which is associated with high expression of genes related to fibrosis and wound response, and an Inactive subtype, which has high expression of cellular adhesion genes. MD of the contralateral breast was assessed using pre-treatment mammograms and a quantitative, reliable computer-assisted thresholding method. Breast tissue composition was evaluated based on digital image analysis of tissue sections. Results:The Inactive extratumoral subtype was associated with significantly higher percentage mammographic density (PD) and dense area (DA) in univariate analysis (PD: p=0.001; DA: p=0.049) and in multivariable analyses adjusted for age and body mass index (PD: p=0.004; DA: p=0.049). Inactive/higher MD tissue was characterized by a significantly higher percentage of stroma and a significantly lower percentage of adipose tissue, with no significant change in epithelial content. Analysis of published gene expression signatures suggested that Inactive/higher MD tissue expressed increased estrogen response and decreased TGF-ß signaling. Conclusions:By linking novel molecular phenotypes with MD, our results indicate that MD reflects broad transcriptional changes, including changes in both epithelia- and stroma-derived signaling. reference x sample
2013-10-21 | E-GEOD-49175 | biostudies-arrayexpress
Project description:<p>The Nurses' Health Study is an on-going prospective cohort study of women that was initiated in 1976. This specific study was part of a larger study to advance our knowledge of breast cancer etiology, expand the current knowledge of mammographic density, and clarify the relationship between mammographic density and breast cancer risk. We conducted a nested case control study of breast cancer among women who provided a blood sample. We then targeted our mammogram collection to participants that were selected as part of this nested case-control study (i.e. those who had provided a blood sample). The mammogram closest to the date of blood draw (~1989-1990) was used. We assessed mammographic breast density from digitized film images using a computer assisted thresholding method (Cumulus). The women in this study were genotyped using the Illumina Omni Express Platform. </p>
| phs000975 | dbGaP
Project description:Introduction Mammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, a high percentage of MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of density are little known. Methods Gene expression analysis using whole genome arrays was performed on breast biopsies from 143 women; 79 women with no malignancy (healthy women) and 64 newly diagnosed breast cancer patients, both included from mammographic centres. Percent MD was determined using a previously validated, computerized method on scanned mammograms. Significance analysis of microarrays (SAM) was performed to identify genes influencing MD and generalized regression models were used to assess the independent contribution from different variables to MD. Results SAM-analysis identified 24 genes differentially expressed between samples from breasts with high and low MD. These genes included three uridine 5'-diphospho-glucuronosyltransferase (UGT) genes and the oestrogen receptor gene (ESR1). These genes were down-regulated in samples with high MD compared to those with low MD. The UGT gene products, which are known to inactivate oestrogen metabolites, were also down-regulated in tumour samples compared to samples from healthy individuals. Several single nucleotide polymorphisms (SNPs) in the UGT genes associated with the expression of UGT and other genes in their vicinity were identified. Conclusions Three UGT enzymes were lower expressed both in breast tissue biopsies from healthy women with high MD and in biopsies from newly diagnosed breast cancers. The association was strongest among young women and women using hormonal therapy. UGT2B10 predicts MD independently of age, hormone therapy and parity. Our results indicate that down-regulation of UGT genes in women exposed to female sex hormones is associated with high MD and might increase the risk of breast cancer. Gene expression analysis of breast biopsies from 143 women, 79 non-cancer (healthy women with no cancer who had a mammogram taken) and 64 breast cancer.
2010-08-13 | E-GEOD-18672 | biostudies-arrayexpress
Project description:CIDR Mapping Genes for Mammographic Breast Density
| PRJNA192861 | ENA
Project description:CIDR Mapping Genes for Mammographic Breast Density
| PRJNA192862 | ENA
Project description:Introduction Mammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, a high percentage of MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of density are little known. Methods Gene expression analysis using whole genome arrays was performed on breast biopsies from 143 women; 79 women with no malignancy (healthy women) and 64 newly diagnosed breast cancer patients, both included from mammographic centres. Percent MD was determined using a previously validated, computerized method on scanned mammograms. Significance analysis of microarrays (SAM) was performed to identify genes influencing MD and generalized regression models were used to assess the independent contribution from different variables to MD. Results SAM-analysis identified 24 genes differentially expressed between samples from breasts with high and low MD. These genes included three uridine 5'-diphospho-glucuronosyltransferase (UGT) genes and the oestrogen receptor gene (ESR1). These genes were down-regulated in samples with high MD compared to those with low MD. The UGT gene products, which are known to inactivate oestrogen metabolites, were also down-regulated in tumour samples compared to samples from healthy individuals. Several single nucleotide polymorphisms (SNPs) in the UGT genes associated with the expression of UGT and other genes in their vicinity were identified. Conclusions Three UGT enzymes were lower expressed both in breast tissue biopsies from healthy women with high MD and in biopsies from newly diagnosed breast cancers. The association was strongest among young women and women using hormonal therapy. UGT2B10 predicts MD independently of age, hormone therapy and parity. Our results indicate that down-regulation of UGT genes in women exposed to female sex hormones is associated with high MD and might increase the risk of breast cancer.
2010-08-13 | GSE18672 | GEO
Project description:Although high mammographic density (MD) is considered one of the strongest risk factors for invasive breast cancer, the genes involved in modulating this clinical feature are unknown. Histologically, areas of high MD are associated with low adipocyte content and high matrix content, both stromal phenotypes. We hypothesized that fibroblasts purified from low and high MD tissues would show gene expression differences responsible for these histologic differences. Fibroblasts were purified from disease-free breast tissue from 6 women with low MD (MD quartile 2) and 7 women with high MD (MD quartile 4). The fibroblasts were cultured for 3 to 6 passages before cells pellets were collected for this study.
2012-06-05 | E-GEOD-38506 | biostudies-arrayexpress
Project description:Although high mammographic density (MD) is considered one of the strongest risk factors for invasive breast cancer, the genes involved in modulating this clinical feature are unknown. Histologically, areas of high MD are associated with low adipocyte content and high matrix content, both stromal phenotypes. We hypothesized that fibroblasts purified from low and high MD tissues would show gene expression differences responsible for these histologic differences.
2012-06-06 | GSE38506 | GEO