Activity of distinct growth factor receptor network components in breast tumors uncovers two biologically relevant
Mumtahena Rahman1,2, Shelley M MacNeil1,3, David F Jenkins4
1Department of Pharmacology and Toxicology, University of Utah, 30 S 2000 E, Salt Lake City, UT, 84108, USA.
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.
Insights
Two distinct breast cancer phenotypes driven by growth factor receptor network (GFRN) activity were identified. These phenotypes predict apoptosis evasion and differential drug responses, offering new therapeutic targets for breast cancer.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- The growth factor receptor network (GFRN) is crucial in oncogenesis, but its complex crosstalk makes global activity assessment difficult in patient tumors.
- Studying complex signaling networks within patient tumors presents challenges for understanding GFRN's role in cancer progression.
Purpose of the Study:
- To interrogate GFRN activity in breast tumors using pathway-specific genomic signatures.
- To investigate the phenotypic impact of distinct GFRN activity patterns on oncogenic processes.
- To correlate GFRN activity with apoptosis evasion and drug response in breast cancer.
Main Methods:
- Generated novel pathway signatures in mammary epithelial cells by overexpressing key GFRN genes (e.g., HER2, IGF1R, AKT1, EGFR).
- Utilized the Adaptive Signature Selection and InteGratioN (ASSIGN) toolkit to assess GFRN pathway activity in 1119 The Cancer Genome Atlas (TCGA) breast tumors and 55 Integrative Cancer Biology Program (ICBP43) cell lines.
- Investigated the relationship between GFRN signatures, apoptotic protein expression, and drug response in breast cancer cell lines.
Main Results:
- Identified two novel breast cancer phenotypes: a 'survival phenotype' (HER2, IGF1R, AKT activation) and a 'growth phenotype' (EGFR, KRAS, RAF1, BAD activation).
- These phenotypes explain significant variability in tumor expression data and are linked to distinct apoptosis evasion mechanisms and drug sensitivities.
- The growth phenotype showed altered BIM/MCL-1 levels and sensitivity to EGFR/MEK inhibitors, while the survival phenotype responded to HER2/PI3K/AKT/mTOR inhibitors but resisted chemotherapy.
Conclusions:
- Gene expression profiling revealed a bifurcation in GFRN activity into two discrete phenotypes.
- These phenotypes correlate with unique apoptosis mechanisms and drug response profiles.
- The identified phenotypes hold potential for pinpointing targetable aberrations for improved breast cancer treatments.
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