Meta-analysis and gene set enrichment relative to er status reveal elevated activity of MYC and E2F in the "basal" breast cancer subgroup

PLoS One. 2009;4(3):e4710. doi: 10.1371/journal.pone.0004710. Epub 2009 Mar 9.


Background: Breast cancers lacking the estrogen receptor (ER) can be distinguished from other breast cancers on the basis of poor prognosis, high grade, distinctive histopathology and unique molecular signatures. These features further distinguish estrogen receptor negative (ER-) tumor subtypes, but targeted therapy is currently limited to tumors over-expressing the ErbB2 receptor.

Methodology/principal findings: To uncover the pathways against which future therapies could be developed we undertook a meta-analysis of gene expression from five large microarray datasets relative to ER status. A measure of association with ER status was calculated for every Affymetrix HG-U133A probe set and the pathways that distinguished ER- tumors were defined by testing for enrichment of biologically defined gene sets using Gene Set Enrichment Analysis (GSEA). As expected, the expression of the direct transcriptional targets of the ER was muted in ER- tumors, but the expression of genes indirectly regulated by estrogen was enhanced. We also observed enrichment of independent MYC- and E2F-driven transcriptional programs. We used a cell model of estrogen and MYC action to define the interaction between estrogen and MYC transcriptional activity in breast cancer. We found that the basal subgroup of ER- breast cancer showed a strong MYC transcriptional response that reproduced the indirect estrogen response seen in estrogen receptor positive (ER+) breast cancer cells.

Conclusions/significance: Increased transcriptional activity of MYC is a characteristic of basal breast cancers where it mimics a large part of an estrogen response in the absence of the ER, suggesting a mechanism by which these cancers achieve estrogen-independence and providing a potential therapeutic target for this poor prognosis sub group of breast cancer.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / metabolism
  • Breast Neoplasms / genetics*
  • Breast Neoplasms / metabolism
  • Carcinoma, Basal Cell / genetics*
  • Carcinoma, Basal Cell / metabolism
  • Diagnosis, Computer-Assisted
  • E2F Transcription Factors / genetics*
  • Female
  • Gene Expression Profiling*
  • Gene Expression Regulation, Neoplastic / physiology*
  • Humans
  • Oligonucleotide Array Sequence Analysis
  • Proto-Oncogene Proteins c-myc / genetics*
  • Receptors, Estrogen / genetics*
  • Regulatory Elements, Transcriptional


  • Biomarkers, Tumor
  • E2F Transcription Factors
  • MYC protein, human
  • Proto-Oncogene Proteins c-myc
  • Receptors, Estrogen