Serum estradiol levels associated with specific gene expression patterns in normal breast tissue and in breast carcinomas.

BACKGROUND: High serum levels of estradiol are associated with increased risk of postmenopausal breast cancer. Little is known about the gene expression in normal breast tissue in relation to levels of circulating serum estradiol. METHODS: We compared whole genome expression data of breast tissue samples with serum hormone levels using data from 79 healthy women and 64 breast cancer patients. Significance analysis of microarrays (SAM) was used to identify differentially expressed genes and multivariate linear regression was used to identify independent associations. RESULTS: Six genes (SCGB3A1, RSPO1, TLN2, SLITRK4, DCLK1, PTGS1) were found differentially expressed according to serum estradiol levels (FDR = 0). Three of these independently predicted estradiol levels in a multivariate model, as SCGB3A1 (HIN1) and TLN2 were up-regulated and PTGS1 (COX1) was down-regulated in breast samples from women with high serum estradiol. Serum estradiol, but none of the differentially expressed genes were significantly associated with mammographic density, another strong breast cancer risk factor. In breast carcinomas, expression of GREB1 and AREG was associated with serum estradiol in all cancers and in the subgroup of estrogen receptor positive cases. CONCLUSIONS: We have identified genes associated with serum estradiol levels in normal breast tissue and in breast carcinomas. SCGB3A1 is a suggested tumor suppressor gene that inhibits cell growth and invasion and is methylated and down-regulated in many epithelial cancers. Our findings indicate this gene as an important inhibitor of breast cell proliferation in healthy women with high estradiol levels. In the breast, this gene is expressed in luminal cells only and is methylated in non-BRCA-related breast cancers. The possibility of a carcinogenic contribution of silencing of this gene for luminal, but not basal-like cancers should be further explored. PTGS1 induces prostaglandin E2 (PGE2) production which in turn stimulates aromatase expression and hence increases the local production of estradiol. This is the first report studying such associations in normal breast tissue in humans.

Expression levels of uridine 5'-diphospho-glucuronosyltransferase genes in breast tissue from healthy women are associated with mammographic density.

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 a linear regression model was 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 amongst 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.

Different gene expression patterns in invasive lobular and ductal carcinomas of the breast.

Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two major histological types of breast cancer worldwide. Whereas IDC incidence has remained stable, ILC is the most rapidly increasing breast cancer phenotype in the United States and Western Europe. It is not clear whether IDC and ILC represent molecularly distinct entities and what genes might be involved in the development of these two phenotypes. We conducted comprehensive gene expression profiling studies to address these questions. Total RNA from 21 ILCs, 38 IDCs, two lymph node metastases, and three normal tissues were amplified and hybridized to approximately 42,000 clone cDNA microarrays. Data were analyzed using hierarchical clustering algorithms and statistical analyses that identify differentially expressed genes (significance analysis of microarrays) and minimal subsets of genes (prediction analysis for microarrays) that succinctly distinguish ILCs and IDCs. Eleven of 21 (52%) of the ILCs ("typical" ILCs) clustered together and displayed different gene expression profiles from IDCs, whereas the other ILCs ("ductal-like" ILCs) were distributed between different IDC subtypes. Many of the differentially expressed genes between ILCs and IDCs code for proteins involved in cell adhesion/motility, lipid/fatty acid transport and metabolism, immune/defense response, and electron transport. Many genes that distinguish typical and ductal-like ILCs are involved in regulation of cell growth and immune response. Our data strongly suggest that over half the ILCs differ from IDCs not only in histological and clinical features but also in global transcription programs. The remaining ILCs closely resemble IDCs in their transcription patterns. Further studies are needed to explore the differences between ILC molecular subtypes and to determine whether they require different therapeutic strategies.

High relative content of lysophospholipids of Helicobacter pylori mediates increased risk for ulcer disease.

Helicobacter pylori phospholipase A (OMPLA) degrades bacterial membrane phospholipids to lysophospholipids. High levels of lysophospholipids are associated with higher hemolytic activity, increased release of urease and vacA and better adherence to epithelial cells in vitro. The phospholipase A gene (pldA) displays phase variation due to a slippage in a homopolymeric tract. The aim of this study was to determine if the relative amount of lysophospholipids in the cell wall is associated with ulcer disease, and to further investigate the significance of pldA phase variation. H. pylori isolates of 40 patients were examined. The relative lysophospholipid content of each isolate was determined and the pldA gene was sequenced. The study indicated that H. pylori can regulate its OMPLA activity by phase variation in the pldA gene or by protein level regulation among phase variants in the pldA 'ON' status. We found a significant difference between the relative amount of lysophospholipids of the ulcer group and the non-ulcer group (p=0.022). When the lysophospholipid/phospholipid ratios were compared with outcome, the OR for ulcer disease was 9.0 (95% CI 1.6-49.4; p=0.014). Isolates with a high OMPLA activity are significantly associated with patients with ulcer disease.

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features.

BACKGROUND: Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. METHODS: Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. RESULTS: Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. CONCLUSION: This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer.