Project description:BackgroundMicroarray experiments enable simultaneous measurement of the expression levels of virtually all transcripts present in cells, thereby providing a 'molecular picture' of the cell state. On the other hand, the genomic responses to a pharmacological or hormonal stimulus are dynamic molecular processes, where time influences gene activity and expression. The potential use of the statistical analysis of microarray data in time series has not been fully exploited so far, due to the fact that only few methods are available which take into proper account temporal relationships between samples.ResultsWe compared here four different methods to analyze data derived from a time course mRNA expression profiling experiment which consisted in the study of the effects of estrogen on hormone-responsive human breast cancer cells. Gene expression was monitored with the innovative Illumina BeadArray platform, which includes an average of 30-40 replicates for each probe sequence randomly distributed on the chip surface. We present and discuss the results obtained by applying to these datasets different statistical methods for serial gene expression analysis. The influence of the normalization algorithm applied on data and of different parameter or threshold choices for the selection of differentially expressed transcripts has also been evaluated. In most cases, the selection was found fairly robust with respect to changes in parameters and type of normalization. We then identified which genes showed an expression profile significantly affected by the hormonal treatment over time. The final list of differentially expressed genes underwent cluster analysis of functional type, to identify groups of genes with similar regulation dynamics.ConclusionsSeveral methods for processing time series gene expression data are presented, including evaluation of benefits and drawbacks of the different methods applied. The resulting protocol for data analysis was applied to characterization of the gene expression changes induced by estrogen in human breast cancer ZR-75.1 cells over an entire cell cycle.

Project description:BACKGROUND: The AP2 transcription factor family is a set of developmentally regulated, retinoic acid (RA) inducible genes, which regulate expression of estrogen receptor-alpha (ERalpha) in breast carcinoma. We hypothesized that AP2 factors regulate a set of genes characteristic of the hormone responsive breast cancer phenotype. To better understand the role of AP2 factors in hormone responsive breast cancer, we sought to identify AP2-target genes in breast epithelial cells. MATERIALS AND METHODS: Overexpression of AP2 factors was achieved in human mammary epithelial cells (HMECs) using adenoviral vectors. AP2 target genes were identified by comparative hybridization to cDNA microarrays containing 30,000 human genes. Expression patterns were confirmed by Northern and Western blot and by elimination of AP2 using siRNA. Potential regulatory elements in promoters of target genes were identified by DNase I hypersensitive site mapping. : Comparative cDNA microarray hybridization identified a set of genes induced by overexpression of AP2alpha and AP2gamma in HMECs. The up-regulation of cellular retinoic acid-binding protein 2 (CRABPII), EST-1, and ECM1 was induced by overexpression of AP2alpha, AP2gamma, or a chimeric AP2 factor in which the activation domain of AP2alpha was replaced by the activation domain of herpesvirus VP16. Interestingly, hormone unresponsive MDA-MB-231 cells were resistant to CRABPII induction by any of the AP2 factors. Elimination of AP2gamma in MCF7 cells resulted in a significant reduction in CRABPII expression. AP2alpha induced DNase I hypersensitive sites in the promoter of the CRABPII gene at -5000 bp, which corresponds to the site of action of RAR/RXR factors. CONCLUSIONS: AP2 factors regulate CRABPII expression in HMECs and breast cancer cells and accounts for the associated expression of ERalpha and CRABPII in hormone responsive breast cancer. Because CRABPII mediates growth suppressive effects of RA in breast cancer, the data suggest that AP2 factors have the ability to mediate RA responsiveness through the regulation of CRABP II expression. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set

Project description:BACKGROUND: The AP2 transcription factor family is a set of developmentally regulated, retinoic acid (RA) inducible genes, which regulate expression of estrogen receptor-alpha (ERalpha) in breast carcinoma. We hypothesized that AP2 factors regulate a set of genes characteristic of the hormone responsive breast cancer phenotype. To better understand the role of AP2 factors in hormone responsive breast cancer, we sought to identify AP2-target genes in breast epithelial cells. MATERIALS AND METHODS: Overexpression of AP2 factors was achieved in human mammary epithelial cells (HMECs) using adenoviral vectors. AP2 target genes were identified by comparative hybridization to cDNA microarrays containing 30,000 human genes. Expression patterns were confirmed by Northern and Western blot and by elimination of AP2 using siRNA. Potential regulatory elements in promoters of target genes were identified by DNase I hypersensitive site mapping. : Comparative cDNA microarray hybridization identified a set of genes induced by overexpression of AP2alpha and AP2gamma in HMECs. The up-regulation of cellular retinoic acid-binding protein 2 (CRABPII), EST-1, and ECM1 was induced by overexpression of AP2alpha, AP2gamma, or a chimeric AP2 factor in which the activation domain of AP2alpha was replaced by the activation domain of herpesvirus VP16. Interestingly, hormone unresponsive MDA-MB-231 cells were resistant to CRABPII induction by any of the AP2 factors. Elimination of AP2gamma in MCF7 cells resulted in a significant reduction in CRABPII expression. AP2alpha induced DNase I hypersensitive sites in the promoter of the CRABPII gene at -5000 bp, which corresponds to the site of action of RAR/RXR factors. CONCLUSIONS: AP2 factors regulate CRABPII expression in HMECs and breast cancer cells and accounts for the associated expression of ERalpha and CRABPII in hormone responsive breast cancer. Because CRABPII mediates growth suppressive effects of RA in breast cancer, the data suggest that AP2 factors have the ability to mediate RA responsiveness through the regulation of CRABP II expression. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Computed

Dataset Information

Identification of primary gene targets of TFAP2C in hormone responsive breast carcinoma cells.

Publications

Identification of primary gene targets of TFAP2C in hormone responsive breast carcinoma cells.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets