Abstract
BackgroundThe 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.MethodsNovel 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.ResultsApplication 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.ConclusionsGene 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.
Highlights
The growth factor receptor network (GFRN) plays a significant role in driving key oncogenic processes
ASSIGN was used to estimate the activation of each GFRN member (AKT, BAD, epidermal growth factor receptor 1 (EGFR), human epidermal growth factor receptor 2 (HER2), insulin-like growth factor 1 receptor (IGF1R), KRAS (G12V), and RAF1) in 1119 breast cancer patient samples from The Cancer Genome Atlas (TCGA) and 55 samples from the ICBP panel of breast cancer cell lines
ASSIGN was used to measure highly correlated GFRN pathway activity more accurately in patient samples with signatures generated in human mammary epithelial cells (HMECs) since ASSIGN estimates correlated pathway activities robustly by adapting pathway signatures into specific disease context
Summary
The growth factor receptor network (GFRN) plays a significant role in driving key oncogenic processes. Molecular aberrations can occur in various growth factor receptor network (GFRN) members and have been described in breast cancer [4,5,6]. These findings have paved the way for GFRN-targeted treatments which are currently approved for use and being evaluated in various stages of clinical development and in clinical trials [7, 8]. These treatments do hold promise, relatively few data are available on the cooperativity and diversity of complicated GFRN signaling in actual breast tumors. There is a strong need to develop better methods for measuring and understanding GFRN signaling events in breast tumors in order to deliver the most effective treatment regimens and combat drug resistance [2, 9, 11]
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