HER2+ Cancer Cell Dependence on PI3K vs. MAPK Signaling Axes Is Determined by Expression of EGFR, ERBB3 and CDKN1B

Understanding the molecular pathways by which oncogenes drive cancerous cell growth, and how dependence on such pathways varies between tumors could be highly valuable for the design of anti-cancer treatment strategies. In this work we study how dependence upon the canonical PI3K and MAPK cascades v...

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Bibliographic Details
Published in:PLoS computational biology 2016-04, Vol.12 (4), p.e1004827-e1004827
Main Authors: Kirouac, Daniel C, Du, Jinyan, Lahdenranta, Johanna, Onsum, Matthew D, Nielsen, Ulrik B, Schoeberl, Birgit, McDonagh, Charlotte F
Format: Article
Language:English
Subjects:
Bias
Biology and life sciences
Biomarkers
Biomarkers, Tumor - genetics
Biomarkers, Tumor - metabolism
Breast cancer
Breast Neoplasms - genetics
Breast Neoplasms - metabolism
Breast Neoplasms - pathology
Cancer cells
Cancer therapies
Cell growth
Cell Line, Tumor
Cellular signal transduction
Computational Biology
Cyclin-Dependent Kinase Inhibitor p27 - genetics
Cyclin-Dependent Kinase Inhibitor p27 - metabolism
Dependence
Drugs
ErbB Receptors - genetics
ErbB Receptors - metabolism
Female
Funding
Gene expression
Gene Knockdown Techniques
Genes, erbB-2
Genetic aspects
Growth models
Health aspects
Humans
Kinases
Ligands
Logistics
MAP Kinase Signaling System - genetics
Medicine and Health Sciences
Mitogen-activated protein kinases
Mortality
Mutation
Neoplasms - genetics
Neoplasms - metabolism
Neoplasms - pathology
Patients
Phosphatidylinositol 3-Kinases - antagonists & inhibitors
Phosphatidylinositol 3-Kinases - genetics
Phosphatidylinositol 3-Kinases - metabolism
Protein expression
Proteins
Receptor, ErbB-2 - metabolism
Receptor, ErbB-3 - genetics
Receptor, ErbB-3 - metabolism
Research and Analysis Methods
RNA, Messenger - genetics
RNA, Messenger - metabolism
RNA, Neoplasm - genetics
RNA, Neoplasm - metabolism
Tumors
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Summary:Understanding the molecular pathways by which oncogenes drive cancerous cell growth, and how dependence on such pathways varies between tumors could be highly valuable for the design of anti-cancer treatment strategies. In this work we study how dependence upon the canonical PI3K and MAPK cascades varies across HER2+ cancers, and define biomarkers predictive of pathway dependencies. A panel of 18 HER2+ (ERBB2-amplified) cell lines representing a variety of indications was used to characterize the functional and molecular diversity within this oncogene-defined cancer. PI3K and MAPK-pathway dependencies were quantified by measuring in vitro cell growth responses to combinations of AKT (MK2206) and MEK (GSK1120212; trametinib) inhibitors, in the presence and absence of the ERBB3 ligand heregulin (NRG1). A combination of three protein measurements comprising the receptors EGFR, ERBB3 (HER3), and the cyclin-dependent kinase inhibitor p27 (CDKN1B) was found to accurately predict dependence on PI3K/AKT vs. MAPK/ERK signaling axes. Notably, this multivariate classifier outperformed the more intuitive and clinically employed metrics, such as expression of phospho-AKT and phospho-ERK, and PI3K pathway mutations (PIK3CA, PTEN, and PIK3R1). In both cell lines and primary patient samples, we observed consistent expression patterns of these biomarkers varies by cancer indication, such that ERBB3 and CDKN1B expression are relatively high in breast tumors while EGFR expression is relatively high in other indications. The predictability of the three protein biomarkers for differentiating PI3K/AKT vs. MAPK dependence in HER2+ cancers was confirmed using external datasets (Project Achilles and GDSC), again out-performing clinically used genetic markers. Measurement of this minimal set of three protein biomarkers could thus inform treatment, and predict mechanisms of drug resistance in HER2+ cancers. More generally, our results show a single oncogenic transformation can have differing effects on cell signaling and growth, contingent upon the molecular and cellular context.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1004827