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Updated: May 17, 2026

Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer
Published on: March 17, 2016
A modulator based regulatory network for ERα signaling pathway.
Heng-Yi Wu1, Pengyue Zheng, Guanglong Jiang
1Center for Computational Biology and Bioinformatics, Indiana University, Indianapolis, IN, USA. hengwu@umail.iu.edu
We developed a new method to map estrogen receptor alpha (ERα) regulatory networks. The non-genomic ERα network proved more reliable than the genomic network in breast cancer cells.
Area of Science:
- Molecular Biology
- Genomics
- Cancer Research
Background:
- Estrogen receptor alpha (ERα) critically regulates gene expression in hormone-responsive breast cancer.
- ERα mediates its effects through complex genomic and non-genomic mechanisms involving co-regulators.
- Understanding ERα's regulatory network is vital for studying breast cancer progression.
Purpose of the Study:
- To investigate the ERα regulatory network and identify novel modulators of ERα function.
- To develop and apply an analytical method for constructing ERα genomic and non-genomic regulatory networks.
- To categorize ERα/modulator/target relationships based on various functional parameters.
Main Methods:
- Proposed a linear regression model to identify translational modulators and their network relationships.
- Constructed ERα genomic and non-genomic regulatory networks using gene expression and ERα Chip-seq data from MCF-7 cells.
- Validated the networks by analyzing gene expression data from ZR-75.1 cells and comparing network overlaps.
Main Results:
- Successfully built ERα genomic and non-genomic regulatory networks by analyzing ERα/modulator/target triplets.
- The ERα non-genomic network exhibited a lower False Discovery Rate (FDR) compared to the genomic network.
- Network overlap analysis revealed a higher consistency (4%) for the non-genomic network versus the genomic network (1%) between MCF-7 and ZR-75.1 cell lines.
Conclusions:
- Introduced a novel approach to infer ERα/modulator/target relationships and construct regulatory networks.
- Demonstrated that the non-genomic regulatory network is more reliable and consistent across different breast cancer cell lines.
- The findings provide a foundation for systematic studies on ERα's role in breast cancer.
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