Related Experiment Video

Updated: Oct 1, 2025

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

9.1K

Analysis of Breast Cancer Based on the Dysregulated Network

Yanhao Huo1, Xianbin Li1, Peng Xu1,2

  • 1Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.

Frontiers in Genetics
|March 4, 2022
PubMed

Insights

Researchers developed a novel method to analyze gene regulation in breast cancer, identifying key networks linked to cancer pathways, drug targets, and patient survival. These findings offer new insights into breast cancer mechanisms.

Area of Science:

  • Oncology
  • Bioinformatics
  • Systems Biology

Background:

  • Breast cancer is a complex, heterogeneous disease driven by intricate molecular regulatory networks.
  • Understanding these networks is crucial for developing effective diagnostics and therapeutics.

Purpose of the Study:

  • To introduce a novel method for quantifying gene regulation strength using expression values.
  • To construct and analyze dysregulated networks (DNs) for the four major breast cancer subtypes.
  • To identify key dysregulated networks (KDNs) as potential biomarkers and therapeutic targets.

Main Methods:

  • Developed a new metric to measure gene regulation strength from gene expression data.
  • Constructed subtype-specific dysregulated networks (DNs) for breast cancer.
  • Performed enrichment analysis of KDNs for pathways, driver genes, and drug targets.
  • Conducted survival analysis based on KDNs.

Main Results:

  • Key dysregulated networks (KDNs) were significantly enriched in critical breast cancer pathways and driver genes.
  • KDNs demonstrated a strong association with known drug targets.
  • Significant differences in survival analysis were observed across subtypes based on KDNs.
  • Identified key dysregulated genes with potential as prognostic markers.

Conclusions:

  • The novel KDN approach provides an effective and innovative method for dissecting breast cancer mechanisms.
  • KDNs represent a promising resource for identifying potential driver genes, drug targets, and prognostic markers in breast cancer subtypes.
Keywords:
breast cancercancer-related pathwaysdriver genesdrug targetsdysregulated networksurvival analysis

More Related Videos

Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer10:36

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

Published on: March 17, 2016

10.6K
Analyzing the Communication Between Monocytes and Primary Breast Cancer Cells in an Extracellular Matrix Extract ECME-based Three-dimensional System10:55

Analyzing the Communication Between Monocytes and Primary Breast Cancer Cells in an Extracellular Matrix Extract ECME-based Three-dimensional System

Published on: January 8, 2018

11.2K

Related Concept Videos

Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.1K
mTOR Signaling and Cancer Progression03:03

mTOR Signaling and Cancer Progression

The mammalian target of rapamycin or mTOR protein was discovered in 1994 due to its direct interaction with rapamycin. The protein gets its name from a yeast homolog called TOR. The mTOR protein complex in mammalian cells plays a major role in balancing anabolic processes such as the synthesis of proteins, lipids, and nucleotides and catabolic processes, such as autophagy in response to environmental cues, such as availability of nutrients and growth factors.
The mTOR pathway or the...
3.9K
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
472
Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

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...
9.2K