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.

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:Objectives and goals: The causes and molecular pathology of ovarian cancer are essentially unknown. However, it is generally understood that serous ovarian borderline tumors (SBOT) and well differentiated (WD) serous ovarian carcinomas (SC) have a similar tumorigenetic pathway, distinct from moderately (MD) and poorly differentiated (PD) SC. The aim of this study was to identify mRNAs differentially expressed between MD/PD SC, SBOT and superficial scrapings from normal ovaries (SNO),and to correlate these mRNAs with clinical parameters. Results: From the global gene expression analyses, thirty mRNAs differentially expressed between MD/PD SC, SBOT and SNO were selected and validated by RT-qPCR, verifying 21 mRNAs to be significantly differentially expressed (p<0.01). Of these, 13 mRNAs were differentially expressed in MD/PD SC compared with SNO (p<0.01) and were correlated with clinical parameters. VEGFA was significantly upregulated (FC=6.1, p=6.0x10-6), and correlated with progression-free survival (p=0.037). ZNF385B was significantly downregulated (FC=-130.5, p=1.2x10-7), and correlated with overall survival (p=0.03). An increased TPX2 (p=0.03) and FOXM1 (p=0.044) expression correlated with optimal normalization of serum CA125 after treatment. Furthermore, we present a common molecular pathway for MD/PD SC, including VEGFA, FOXM1, TPX2, BIRC5 and TOP2A, all significantly upregulated and interacting with TP53. Conclusions: We have identified 21 mRNAs differentially expressed (p<0.01) between MD/PD SC, SBOT and SNO. Thirteen were differentially expressed in MD/PD SC, including VEGFA and ZNF385B, correlating with survival, and FOXM1 and TPX2, correlating with normalization of serum CA125. By the use of oligonucleotid microarrays (Affymetrix U133 Plus 2.0 Arrays) differences in mRNA expression between eleven MD/PD SC, eight SBOT and four SNO samples were analyzed. Differentially expressed mRNAs were selected for validation by RT-qPCR in additional samples totaling 21 MD/PD SC, 13 SBOT and seven samples of SNO. Each mRNA was run in quadruple. The mRNAs differentially expressed in MD/PD SC compared with SNO were correlated with clinical parameters.

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Relationship of mammographic density and gene expression: analysis of normal breast tissue surrounding breast cancer

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