Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Metastasis02:30

Metastasis

Metastasis is the spread of cancer cells from the original site to distant locations in the body. Cancer cells can spread via blood vessels (hematogenous) as well as lymph vessels in the body.
Epithelial-to-Mesenchymal Transition
The epithelial-to-mesenchymal transition or EMT is a developmental process commonly observed in wound healing, embryogenesis, and cancer metastasis. EMT is induced by transforming growth factor-beta (TGF-β) or receptor tyrosine kinase (RTK) ligands, which further...
Overview of Cell-Matrix Interactions01:24

Overview of Cell-Matrix Interactions

The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...

You might also read

Related Articles

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

Sort by
Same author

Explaining hidden mechanisms: a generative model for causal graphs with nonlinear latent factors.

Frontiers in artificial intelligence·2026
Same author

Daily Stress and Heart Rate Variability Among Mindfulness Meditation Practitioners: mHealth Observational Study.

Journal of medical Internet research·2026
Same author

Genome-Wide Meta-Analysis for High Myopia Provides Insights into Disease Mechanisms and Reveals a Causal Link to Primary Open-Angle Glaucoma.

Ophthalmology science·2026
Same author

Correction: Machine learning model for predicting the cold-heat pattern in Kampo medicine: a multicenter prospective observational study.

Frontiers in pharmacology·2026
Same author

Case Report: Mixed ductal-lobular carcinoma consisting of invasive lobular carcinoma with a glycogen-rich clear cell pattern and elevated tumor mutation burden.

Frontiers in oncology·2026
Same author

Dual knockout of Fas and TCRα in Jurkat reporter cells enables highly sensitive identification of antigen-specific TCRs.

Biochemical and biophysical research communications·2026

Related Experiment Video

Updated: May 31, 2026

Induction and Analysis of Epithelial to Mesenchymal Transition
10:37

Induction and Analysis of Epithelial to Mesenchymal Transition

Published on: August 27, 2013

A novel network profiling analysis reveals system changes in epithelial-mesenchymal transition.

Teppei Shimamura1, Seiya Imoto, Yukako Shimada

  • 1Human Genome Center, Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo, Japan. shima@ims.u-tokyo.ac.jp

Plos One
|June 21, 2011
PubMed
Summary

NetworkProfiler infers patient-specific gene regulatory networks from cancer data. This method identified key regulators of epithelial-mesenchymal transition (EMT), aiding personalized cancer therapy and risk prediction.

More Related Videos

Detection of Alternative Splicing During Epithelial-Mesenchymal Transition
11:48

Detection of Alternative Splicing During Epithelial-Mesenchymal Transition

Published on: October 9, 2014

Induction of Mesenchymal-Epithelial Transitions in Sarcoma Cells
11:42

Induction of Mesenchymal-Epithelial Transitions in Sarcoma Cells

Published on: April 7, 2017

Related Experiment Videos

Last Updated: May 31, 2026

Induction and Analysis of Epithelial to Mesenchymal Transition
10:37

Induction and Analysis of Epithelial to Mesenchymal Transition

Published on: August 27, 2013

Detection of Alternative Splicing During Epithelial-Mesenchymal Transition
11:48

Detection of Alternative Splicing During Epithelial-Mesenchymal Transition

Published on: October 9, 2014

Induction of Mesenchymal-Epithelial Transitions in Sarcoma Cells
11:42

Induction of Mesenchymal-Epithelial Transitions in Sarcoma Cells

Published on: April 7, 2017

Area of Science:

  • Computational Biology
  • Systems Biology
  • Genomics

Background:

  • Patient-specific molecular network analysis is crucial for personalized cancer therapy.
  • Traditional methods provide averaged networks, missing individual variations during cancer progression.
  • Systems biology reconstructs cellular gene networks from expression data.

Purpose of the Study:

  • To develop NetworkProfiler, a novel statistical method for inferring patient-specific gene regulatory networks.
  • To identify system changes related to epithelial-mesenchymal transition (EMT) during cancer progression.
  • To predict patient-specific regulators of EMT for improved cancer treatment decisions.

Main Methods:

  • Applied NetworkProfiler to microarray gene expression data from 762 cancer cell lines.
  • Identified candidate regulators of E-cadherin, a key molecule in EMT.
  • Utilized in vitro validation experiments, including siRNA knockdown and microRNA analysis.

Main Results:

  • NetworkProfiler identified 25 candidate regulators of E-cadherin, with ~50% experimental verification.
  • Predicted EMT-dependent master regulators involved in cell adhesion, migration, invasion, and metastasis.
  • Validated KLF5 and miR-100 as key players in EMT, consistent with NetworkProfiler predictions.

Conclusions:

  • NetworkProfiler enables patient-specific network inference for cancer research.
  • The method successfully identified novel EMT regulators, including KLF5 and miR-100.
  • This approach holds promise for personalized risk prediction and treatment strategies in oncology.