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Identification of gene expression signature in estrogen receptor positive breast carcinoma.

ABSTRACT: A significant group of patient with estrogen receptor (ER) ? positive breast tumors fails to appreciably respond to endocrine therapy. An increased understanding of the molecular basis of estrogen-mediated signal transduction and resultant gene expression may lead to novel strategies for treating breast cancer. In this study, we sought to identify the dysregulated genes in breast tumors related to ER? status. Microarray analyses of 31 tumor samples showed 108 genes differentially expressed in ER? (+) and ER? (-) primary breast tumors. Further analyses of gene lists indicated that a significant number of dysregulated genes were involved in mRNA transcription and cellular differentiation. The majority of these genes were found to have promoter-binding sites for E74-like factor 5 (ELF5; 54.6% genes), E2F transcription factor 1 (E2F1; 22.2% genes), and nuclear transcription factor Y alpha (NFYA; 32.4% genes). Six candidate genes (NTN4, SLC7A8, MLPH, ENPP1, LAMB2, and PLAT) with differential expression were selected for further validation studies using RT-qPCR (76 clinical specimen) and immunohistochemistry (48 clinical specimen). Our studies indicate significant over-expression of all the six genes in ER? (+) breast tumors as compared to ER? (-) breast tumors. In vitro studies using T-47D breast cancer cell line confirmed the estrogen dependant expression of four of the above six genes (SLC7A8, ENPP1, LAMB2, and PLAT). Collectively, our study provides further insights into the molecular basis of estrogen-dependent breast cancer and identifies "candidate biomarkers" that could be useful for predicting endocrine responsiveness.

SUBMITTER: Thakkar AD

PROVIDER: S-EPMC3783308 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Identification of gene expression signature in estrogen receptor positive breast carcinoma.

Thakkar Arvind D AD Raj Hemanth H Chakrabarti Debarshi D Ravishankar Saravanan N N Muthuvelan Bhaskaran B Balakrishnan Arun A Padigaru Muralidhara M

Biomarkers in cancer 20100211

A significant group of patient with estrogen receptor (ER) α positive breast tumors fails to appreciably respond to endocrine therapy. An increased understanding of the molecular basis of estrogen-mediated signal transduction and resultant gene expression may lead to novel strategies for treating breast cancer. In this study, we sought to identify the dysregulated genes in breast tumors related to ERα status. Microarray analyses of 31 tumor samples showed 108 genes differentially expressed in ER ...[more]

PMID: 24179381

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Project description:BackgroundEstrogens are known to regulate the proliferation of breast cancer cells and to modify their phenotypic properties. Identification of estrogen-regulated genes in human breast tumors is an essential step toward understanding the molecular mechanisms of estrogen action in cancer. To this end we generated and compared the Serial Analysis of Gene Expression (SAGE) profiles of 26 human breast carcinomas based on their estrogen receptor alpha (ER) status. Thus, producing a breast cancer SAGE database of almost 2.5 million tags, representing over 50,000 transcripts.ResultsWe identified 520 transcripts differentially expressed between ERalpha-positive (+) and ERalpha-negative (-) primary breast tumors (Fold change >or= 2; p < 0.05). Furthermore, we identified 220 high-affinity Estrogen Responsive Elements (EREs) distributed on the promoter regions of 163 out of the 473 up-modulated genes in ERalpha (+) breast tumors. In brief, we observed predominantly up-regulation of cell growth related genes, DNA binding and transcription factor activity related genes based on Gene Ontology (GO) biological functional annotation. GO terms over-representation analysis showed a statistically significant enrichment of various transcript families including: metal ion binding related transcripts (p = 0.011), calcium ion binding related transcripts (p = 0.033) and steroid hormone receptor activity related transcripts (p = 0.031). SAGE data associated with ERalpha status was compared with reported information from breast cancer DNA microarrays studies. A significant proportion of ERalpha associated gene expression changes was validated by this cross-platform comparison. However, our SAGE study also identified novel sets of genes as highly expressed in ERalpha (+) invasive breast tumors not previously reported. These observations were further validated in an independent set of human breast tumors by means of real time RT-PCR.ConclusionThe integration of the breast cancer comparative transcriptome analysis based on ERalpha status coupled to the genome-wide identification of high-affinity EREs and GO over-representation analysis, provide useful information for validation and discovery of signaling networks related to estrogen response in this malignancy.

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Identification of gene expression signature in estrogen receptor positive breast carcinoma.

Publications

Identification of gene expression signature in estrogen receptor positive breast carcinoma.

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