Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of immortalised human mammary luminal epithelial cells and variants expressing a moderate and high level of ERBB2

ABSTRACT: To investigate changes in gene expression associated with ERBB2, expression profiling of immortalised human mammary luminal epithelial cells and variants expressing a moderate and high level of ERBB2 has been carried out using cDNA microarrays corresponding to approximately 6,000 unique genes/ESTs. Sixty-three (63) significantly up- or down-regulated (>2.0 fold) genes were identified and further validated by RT-PCR and Northern blot analysis as well as microarray comparisons with a spontaneously ERBB2- overexpressing breast cancer cell line and ERBB2-positive primary breast tumours. Proteins predicted to be associated ERBB2 overexpression in breast cancers were analysed together with their clinical relevance by antibody screening using a tissue array. Differentially regulated genes include those involved in cell matrix interactions including P4HA2 (proline 4-hydroxylase), galectin 1 (LGALS1) and galectin 3 (LGALS3), FN1 (fibronectin 1), and CDH3 (p-cadherin) and cell proliferation (CRIP1, IGFBP3) and transformation (S100P, S100A4). A number of genes associated with MYC signalling were also differentially expressed, including NDRG1, USF2 and the epithelial membrane proteins 1 and 3 (EMP1, EMP3). These data represent profile of the transcriptional changes associated with ERBB2-related pathways in the breast, and identify novel and potentially useful targets for prognosis and therapy.

INSTRUMENT(S): microcentrifuge

ORGANISM(S): Homo sapiens

SUBMITTER: Tim Dexter

PROVIDER: E-SNGR-8 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Subconfluent AG01518 fibroblasts were starved for 16 hours in the presence of 0.1% BSA, and then stimulated for 1, 4, 10 or 24 hours with PDGF-BB (10 ng/ml in starvation medium), or left untreated for the same periods of time. Total RNA was isolated using the RNeasy kit (Qiagen). The RNA quality was checked by formaldehyde agarose gel electrophoresis (RNeasy protocol, Qiagen). Total RNA (40 mg) from cells treated for a given period of time with PDGF or control medium were labelled in reverse transcription reactions (Superscript II kit, Invitrogen) with dCTP-Cy5 and dCTP-Cy3, respectively (Amersham). In every second replicate experiment the fluorescent deoxynucleotides were swapped. Purified cDNA probes labelled with Cy3 and Cy5 were mixed per pair, and hybridized to cDNA microarray chips (Sanger Institute H. sapiens 10K array, Hver1.2.1) from the Sanger Institute/LICR/CRUK Consortium (see http://www.sanger.ac.uk/Projects/Microarrays/ for details and hybridization protocols). For each time point, we performed at least four independent hybridizations, and used at least two different batches of RNA. Chips were scanned in a Perkin Elmer/GSI Lumonics ScanArray 4000 scanner and spot intensities were measured using the QuantArray software (histogram method with background subtraction). Normalization and statistical analysis of the quadruplicate data sets were performed using GeneSpring 5.0 analysis software (Silicon Genetics). A Lowess non-linear normalization was applied and the median of the ratio distribution for each array was set to 1. Regulated spots were selected based on the average ratio values > 1.750 for up-regulated genes and < 0.571 for down-regulated genes. In addition, we considered only genes that were significantly regulated (t-test, p<0.05) based on replicate hybridizations (global error model, GeneSpring). For all features selected using this protocol, the signal was significantly above the background, indicating that the expression of these genes was detectable. Finally, Hver1.2.1 microarrays contain replicate spots (1 to 6) corresponding to the same gene. Genes represented by spots that were not regulated in a similar manner were discarded. We show the average ratio of one representative spot for each regulated gene, with standard error calculated from multiple hybridizations and with the annotation provided by the microarray facility (Hver1.2.1_NCBI33).

Project description:Background: Gene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene, in a group of breast cancer patients with long-term (12-16 years) follow-up. Methods: The clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using TTGE and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples. Results: Both univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. The TP53 mutation status showed strong association with the ?basal-like? and ?ERBB2+? gene expression subgroups, and tumors with mutation had a characteristic gene expression pattern. Conclusions: TP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease. Experiment set consisting of 80 primary breast carcinomas collected at Ulleval University Hospital (ULL-samples), Oslo, Norway from 1990-94, and one normal sample from breast reduction surgery.

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Transcription profiling of immortalised human mammary luminal epithelial cells and variants expressing a moderate and high level of ERBB2

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