Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Global Regulatory Systems

Global Regulatory Systems

Global regulatory systems in bacteria enable rapid and coordinated responses to environmental changes by integrating sensory inputs with gene expression, ensuring efficient adaptation to fluctuating conditions. Key global regulatory mechanisms include regulons, two-component systems, sigma factors, and secondary messengers.Regulons and Global RegulatorsA regulon is a collection of genes and operons controlled by a common global regulator. These regulators enable bacteria to prioritize resource...

Interactions Between Signaling Pathways

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...

Amplifying Signals via Enzymatic Cascade

Amplifying Signals via Enzymatic Cascade

When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze the...

Master Transcription Regulators

Master Transcription Regulators

Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...

Positive Regulator Molecules

Positive Regulator Molecules

Mitotic cell division results in daughter cells that exactly resemble the parent cell. However, errors in the DNA replication or distribution of genetic material may lead to genetic mutations that may be passed down to every new cell formed from the resulting abnormal cell. Propagation of such mutant cells is restricted through checkpoint mechanisms present at different stages of the cell cycle. These checkpoints involve regulator molecules that either promote or demote cell cycle events.

Calmodulin-dependent Signaling

Calmodulin-dependent Signaling

Calmodulin (CaM) is a calcium-binding protein in eukaryotes that controls various calcium-regulated cellular processes. It has four calcium-binding sites that bind calcium to form the calcium-calmodulin ( Ca2+-CaM) complex. GPCR stimulation increases the calcium levels in the cells that bind to CaM and induces a conformational change.
The Ca2+-CaM complex does not have enzymatic activity by itself. Instead, the complex binds downstream target proteins, including membrane proteins or enzymes,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Retraction Note: Heterozygous deletion of chromosome 17p renders prostate cancer vulnerable to inhibition of RNA polymerase II.

Nature communications·2026

Same author

ERG function in prostate cells is regulated by distinct positive feedback loops depending on AKT signaling status.

Research square·2026

Same author

DNA Methyltransferase Inhibition Prevents Platinum-Induced Ovarian Cancer Stem Cell Enrichment.

Cancer research communications·2026

Same author

Impact of patient-reported taxane-induced peripheral neuropathy on dose reductions or worsening quality of life in Black women with breast cancer: Analysis from ECOG-ACRIN EAZ171.

Cancer·2026

Same author

Effects of the Hypomethylating Agent Guadecitabine on Peripheral Blood Mononuclear Cell Methylomes and Immune Cell Populations in Small-Cell Lung Cancer Patients.

Pharmaceuticals (Basel, Switzerland)·2026

Same author

Blood Based Biomarkers of DNA Methylation Associated with Platinum Resistance in High Grade Serous Ovarian Cancer.

bioRxiv : the preprint server for biology·2026

Search research articles

Related Experiment Video

Updated: May 17, 2026

Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer

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

|November 9, 2012

Summary

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.

More Related Videos

Detecting the Ligand-binding Domain Dimerization Activity of Estrogen Receptor Alpha Using the Mammalian Two-Hybrid Assay

Detecting the Ligand-binding Domain Dimerization Activity of Estrogen Receptor Alpha Using the Mammalian Two-Hybrid Assay

Published on: December 19, 2018

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Published on: June 21, 2016

Related Experiment Videos

Last Updated: May 17, 2026

Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer

Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer

Published on: March 17, 2016

Detecting the Ligand-binding Domain Dimerization Activity of Estrogen Receptor Alpha Using the Mammalian Two-Hybrid Assay

Detecting the Ligand-binding Domain Dimerization Activity of Estrogen Receptor Alpha Using the Mammalian Two-Hybrid Assay

Published on: December 19, 2018

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Published on: June 21, 2016

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.