Activity of distinct growth factor receptor network components in breast tumors uncovers two biologically relevant subtypes

Mumtahena Rahman, Shelley M. MacNeil, David F. Jenkins, Gajendra Shrestha, Sydney R. Wyatt, Jasmine A. McQuerry, Stephen R. Piccolo, Laura M. Heiser, Joe W. Gray, W. Evan Johnson, Andrea H. Bild

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Background: The growth factor receptor network (GFRN) plays a significant role in driving key oncogenic processes. However, assessment of global GFRN activity is challenging due to complex crosstalk among GFRN components, or pathways, and the inability to study complex signaling networks in patient tumors. Here, pathway-specific genomic signatures were used to interrogate GFRN activity in breast tumors and the consequent phenotypic impact of GRFN activity patterns. Methods: Novel pathway signatures were generated in human primary mammary epithelial cells by overexpressing key genes from GFRN pathways (HER2, IGF1R, AKT1, EGFR, KRAS (G12V), RAF1, BAD). The pathway analysis toolkit Adaptive Signature Selection and InteGratioN (ASSIGN) was used to estimate pathway activity for GFRN components in 1119 breast tumors from The Cancer Genome Atlas (TCGA) and across 55 breast cancer cell lines from the Integrative Cancer Biology Program (ICBP43). These signatures were investigated for their relationship to pro- and anti-apoptotic protein expression and drug response in breast cancer cell lines. Results: Application of these signatures to breast tumor gene expression data identified two novel discrete phenotypes characterized by concordant, aberrant activation of either the HER2, IGF1R, and AKT pathways ("the survival phenotype") or the EGFR, KRAS (G12V), RAF1, and BAD pathways ("the growth phenotype"). These phenotypes described a significant amount of the variability in the total expression data across breast cancer tumors and characterized distinctive patterns in apoptosis evasion and drug response. The growth phenotype expressed lower levels of BIM and higher levels of MCL-1 proteins. Further, the growth phenotype was more sensitive to common chemotherapies and targeted therapies directed at EGFR and MEK. Alternatively, the survival phenotype was more sensitive to drugs inhibiting HER2, PI3K, AKT, and mTOR, but more resistant to chemotherapies. Conclusions: Gene expression profiling revealed a bifurcation pattern in GFRN activity represented by two discrete phenotypes. These phenotypes correlate to unique mechanisms of apoptosis and drug response and have the potential of pinpointing targetable aberration(s) for more effective breast cancer treatments.

Original languageEnglish (US)
Article number40
JournalGenome Medicine
Volume9
Issue number1
DOIs
StatePublished - Apr 26 2017

Keywords

  • Breast cancer
  • Cancer phenotypes
  • Gene expression signatures
  • Genomics
  • Growth factor receptor network
  • Targeted therapy

ASJC Scopus subject areas

  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Genetics(clinical)

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    Rahman, M., MacNeil, S. M., Jenkins, D. F., Shrestha, G., Wyatt, S. R., McQuerry, J. A., Piccolo, S. R., Heiser, L. M., Gray, J. W., Johnson, W. E., & Bild, A. H. (2017). Activity of distinct growth factor receptor network components in breast tumors uncovers two biologically relevant subtypes. Genome Medicine, 9(1), [40]. https://doi.org/10.1186/s13073-017-0429-x