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Related Concept Videos

Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
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...
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...

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Related Experiment Video

Updated: Jun 4, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

Functional modules with disease discrimination abilities for various cancers.

Chen Yao1, Min Zhang, JinFeng Zou

  • 1Bioinformatics Centre, School of Life Science, University of Electronic Science and Technology of China, Chengdu 610054, China.

Science China. Life Sciences
|February 15, 2011
PubMed
Summary
This summary is machine-generated.

Identifying differentially expressed genes (DEGs) in cancer research is challenging due to small sample sizes. This study proposes using functional gene modules instead of individual DEGs for more reproducible cancer mechanism studies and robust diagnostics.

Related Experiment Videos

Last Updated: Jun 4, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

Area of Science:

  • Genomics
  • Cancer Biology
  • Bioinformatics

Background:

  • Selecting differentially expressed genes (DEGs) is crucial for understanding multi-factor diseases like cancer using microarray data.
  • Current methods using small sample sizes often yield lists of DEGs with low reproducibility, limiting insights into complex diseases.
  • The variability in gene expression in complex diseases is not fully captured by individual gene analysis.

Purpose of the Study:

  • To investigate the utility of functional gene modules as an alternative to individual DEGs for cancer research.
  • To identify reproducible molecular signatures across different cancer types.
  • To explore the potential of functional modules for developing robust diagnostic classifiers.

Main Methods:

  • Analysis of seven diverse cancer microarray datasets.
  • Identification and evaluation of altered functional gene modules within each cancer type.
  • Comparison of gene modules across multiple cancers to find shared signatures.

Main Results:

  • A wide range of functional modules exhibit altered gene expression in each analyzed cancer.
  • These altered modules demonstrate high disease classification abilities.
  • Seven specific functional modules were found to be consistently altered across diverse cancers, suggesting commonalities in cancer mechanisms.

Conclusions:

  • Functional gene modules offer a more reproducible and robust approach than individual DEGs for studying cancer.
  • Shared functional modules across cancers provide insights into fundamental cancer biology.
  • Functional modules can serve as effective signatures for robust diagnostic classifier development in oncology.