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.
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.
Project description:Normal primary epithelial cells from women following reduction mammoplasty or BRCA1 or 2 mutated women following preventive mastectomy were purified from the mammary tissue and analyzed by RNAseq. Since all samples were certified tumor-free by an anatomo-pathologist prior to processing, this study aims to better understand the transcriptomic alterations inudced by BRCA genes mutations in primary cells prior to any detectable transformation event.
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.
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.
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.