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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 12, 2026

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
11:15

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

Published on: September 20, 2016

Robust multi-tissue gene panel for cancer detection.

Joseph Irgon1, C Chris Huang, Yi Zhang

  • 1Centocor R&D, Inc, 145 King of Prussia Rd, Radnor, PA 19087, USA.

BMC Cancer
|June 24, 2010
PubMed
Summary
This summary is machine-generated.

A novel gene panel accurately distinguishes cancerous from normal tissue across multiple solid tumors. This robust tool aids in cancer diagnosis and research, improving accuracy in identifying tumor types.

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Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
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Last Updated: Jun 12, 2026

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
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Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
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Published on: August 1, 2018

Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Identified a set of genes with distinct mRNA expression levels in solid tumors versus normal tissue.
  • Developed a gene panel of 113 probes for 104 unique genes from microarray data on the Affymetrix HG-U133A platform.
  • Focused on five tissue types: breast, colon, lung, prostate, and ovary.

Purpose of the Study:

  • To develop and validate a robust gene expression-based classification tool for distinguishing solid tumors from normal tissues.
  • To create a common cancer gene panel applicable across multiple tumor types.

Main Methods:

  • Utilized microarray data to identify significantly differentially expressed genes (p-value < 0.05) between tumor and normal tissues.
  • Employed Genes@Work software for differential expression discovery and Support Vector Machine (SVM) light linear kernel for classification model building.
  • Validated the gene panel on publicly available datasets and high-throughput validation on the Dana Farber Cancer Institute GCOD database and GEO datasets.

Main Results:

  • The developed gene panel demonstrated high accuracy in distinguishing tumor from normal tissue across five cancer types.
  • Achieved 94.7% leave-one-out accuracy for lung cancer classification using an SVM linear kernel, outperforming a previously published panel (87.8%).
  • Confirmed the predictability and robustness of the gene list on multiple public datasets.

Conclusions:

  • The gene panel serves as a robust classification tool for various tumor types on the Affymetrix platform and other whole-genome arrays.
  • Potential applications include early tumorigenesis diagnosis, assisting pathologists with precancerous lesions, defining tumor boundaries, and assessing sample integrity.
  • The panel's accuracy in normal vs. tumor identification can confidently pinpoint mislabeled or misinterpreted samples.