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Mining for regulatory programs in the cancer transcriptome

Daniel R Rhodes1, Shanker Kalyana-Sundaram, Vasudeva Mahavisno

  • 1Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA.

Nature Genetics
|May 28, 2005
PubMed

Insights

Cancer gene deregulation is linked to transcription factors. E2F targets are broadly overexpressed across cancers, while others like Myc-Max are specific, suggesting pathway alterations drive cancer pathogenesis.

Area of Science:

  • Genomics
  • Cancer Biology
  • Bioinformatics

Background:

  • DNA microarrays are crucial for cancer transcriptome analysis.
  • The Oncomine database houses extensive gene expression data and signatures.
  • Understanding gene deregulation mechanisms in cancer is vital.

Purpose of the Study:

  • Investigate regulatory mechanisms behind gene deregulation in cancer signatures.
  • Identify transcription factors involved in coordinated gene regulation in cancer.
  • Explore the role of transcription factor binding sites in cancer pathogenesis.

Main Methods:

  • Analyzed gene-expression signatures from the Oncomine database.
  • Searched for coordinate regulation of genes sharing common transcription factor binding sites.
  • Utilized bioinformatics approaches to identify overexpressed genes linked to specific transcription factors.

Main Results:

  • Genes with E2F transcription factor binding sites showed disproportionate overexpression across diverse cancer types.
  • Genes associated with Myc-Max, c-Rel, and ATF transcription factors were overexpressed in specific cancer types.
  • Demonstrated a link between transcription factor binding and broad or specific gene deregulation in cancer.

Conclusions:

  • Alterations in pathways regulating transcription factors like E2F may drive widespread gene deregulation in cancer.
  • Specific transcription factor pathway alterations contribute to the pathogenesis of particular cancer types.
  • Transcription factor binding site analysis provides insights into cancer gene regulatory networks.

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