An integrative transcriptomics approach identifies miR-503 as a candidate master regulator of the estrogen response in MCF-7 breast cancer cells.
Jeanette Baran-GaleJeremy E PurvisPraveen SethupathyPublished in: RNA (New York, N.Y.) (2016)
Estrogen receptor α (ERα) is an important biomarker of breast cancer severity and a common therapeutic target. In response to estrogen, ERα stimulates a dynamic transcriptional program including both coding and noncoding RNAs. We generate a fine-scale map of expression dynamics by performing a temporal profiling of both messenger RNAs (mRNAs) and microRNAs (miRNAs) in MCF-7 cells (an ER+ model cell line for breast cancer) in response to estrogen stimulation. We identified three primary expression trends-transient, induced, and repressed-that were each enriched for genes with distinct cellular functions. Integrative analysis of mRNA and miRNA temporal expression profiles identified miR-503 as the strongest candidate master regulator of the estrogen response, in part through suppression of ZNF217-an oncogene that is frequently amplified in cancer. We confirmed experimentally that miR-503 directly targets ZNF217 and that overexpression of miR-503 suppresses MCF-7 cell proliferation. Moreover, the levels of ZNF217 and miR-503 are associated with opposite outcomes in breast cancer patient cohorts, with high expression of ZNF217 associated with poor survival and high expression of miR-503 associated with improved survival. Overall, these data indicate that miR-503 acts as a potent estrogen-induced candidate tumor suppressor miRNA that opposes cellular proliferation and has promise as a novel therapeutic for breast cancer. More generally, our work provides a systems-level framework for identifying functional interactions that shape the temporal dynamics of gene expression.
Keyphrases
- cell proliferation
- estrogen receptor
- long non coding rna
- breast cancer cells
- poor prognosis
- long noncoding rna
- gene expression
- cell cycle
- pi k akt
- signaling pathway
- transcription factor
- machine learning
- type diabetes
- single cell
- air pollution
- dna methylation
- high glucose
- big data
- oxidative stress
- diabetic rats
- deep learning
- electronic health record
- insulin resistance
- skeletal muscle
- endothelial cells
- case report
- glycemic control
- free survival
- data analysis
- endoplasmic reticulum stress
- cerebral ischemia