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Related Concept Videos

Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...

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Related Experiment Video

Updated: Jun 25, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Gene set-based module discovery in the breast cancer transcriptome.

Atsushi Niida1, Andrew D Smith, Seiya Imoto

  • 1Laboratory of Molecular and Genetic Information, Institute of Molecular and Cellular Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, Japan. aniida@ims.u-tokyo.ac.jp

BMC Bioinformatics
|February 27, 2009
PubMed
Summary

We developed EEM, a novel method to discover gene expression modules in breast cancer. EEM identified key regulatory programs, revealing PRC2 downregulation in triple-negative tumors and predicting regulatory circuits.

Related Experiment Videos

Last Updated: Jun 25, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Area of Science:

  • Genomics
  • Computational Biology
  • Cancer Research

Background:

  • Microarray studies offer a global view of cancer cell gene expression but lack insight into regulatory mechanisms.
  • Computational methods have identified gene expression modules in yeast, but not yet in cancer transcriptomes.

Purpose of the Study:

  • To decode oncogenic regulatory programs in cancer cells using a novel module discovery method.
  • To apply this method to breast cancer expression data and identify key regulatory modules and their activities.

Main Methods:

  • Developed EEM (Expression Ensemble Modules), an extended module discovery method.
  • Applied EEM to breast cancer expression data, using seed gene sets from cis-regulatory elements, ChIP-chip data, and gene locus information.
  • Analyzed expression coherence to identify modules and their activity profiles across tumor subtypes.

Main Results:

  • Identified 10 principal expression modules in breast cancer.
  • Depicted module activity profiles predicting regulatory programs in tumor subtypes.
  • Revealed downregulation of the Polycomb repressive complex 2 (PRC2) module in triple-negative breast cancers, suggesting stem cell-like transcriptional programs.
  • Found negative correlation between PRC2 module activity and EZH2 expression, suggesting E2F-driven EZH2 overexpression represses PRC2 modules in triple-negative tumors.
  • Predicted regulatory circuits in breast cancer cells through network analysis.

Conclusions:

  • Gene set-based module discovery is a powerful approach for decoding cancer cell regulatory programs.
  • EEM successfully identified key regulatory modules and their subtype-specific activities in breast cancer.