Will develop a dynamic model of response to HER family inhibitors in tumors in which HER2 is amplified that encompasses both fast, phosphorylation-based events (on the order of a few minutes) and slower transcriptional and epigenomic processes (on the order of a few days). This model will eventually enable comparative assessment ofthe relative importance of mechanisms of response and resistance and guide development of combinatorial therapeutic strategies to counter resistance. This project is motivated by observations that responses to trastuzumab and lapatinib are not uniform between patients and are frequently not durable. Work in this CCSB project and the general scientific community suggests several mechanisms that may confer resistance including: (a) activating downstream mutations in the PI3K pathway, (b) microenvironment mediated activation of interacting networks, (c) PI3K mediated changes in HERS expression and signaling and (d) transcriptional feedback regulation from response related network elements. An initial dynamic version ofthe model will be developed in collaboration with the MIT CCSB (see letter of collaboration from Dr. Lauffenburger). The model will differ from existing work in three important ways: it will exploit a mathematical separation of time scales for fast and slow dynamics, incorporate underlying genetic aberrations, and include parallel signaling from the microenvironment. Analysis ofthis initial model will be used to help understand the roles of cooperating genetic aberrations, transcriptional and translational regulation, vesicle control and microenvironment in fast and slow dynamic processes. Subsequent versions of the model will build on experimental measurements of temporal biological and molecular responses of HER2+ breast cancer cell lines to HER2 family signaling network inhibitors administered alone and in combination as well as information from Projects 1, 2 and 4 and from the Stanford CCSB's MYC modeling efforts (see letter of collaboration from Dr. Plevritis). A combination of Bayesian network analysis and dynamic modeling will be used to model the unexplored effects of epigenomic modulation of transcription on HER2/3 signaling.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Specialized Center--Cooperative Agreements (U54)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Oregon Health and Science University
United States
Zip Code
Risom, Tyler; Langer, Ellen M; Chapman, Margaret P et al. (2018) Differentiation-state plasticity is a targetable resistance mechanism in basal-like breast cancer. Nat Commun 9:3815
Gast, Charles E; Silk, Alain D; Zarour, Luai et al. (2018) Cell fusion potentiates tumor heterogeneity and reveals circulating hybrid cells that correlate with stage and survival. Sci Adv 4:eaat7828
Seviour, E G; Sehgal, V; Mishra, D et al. (2017) Targeting KRas-dependent tumour growth, circulating tumour cells and metastasis in vivo by clinically significant miR-193a-3p. Oncogene 36:1339-1350
Riesco, Adrián; Santos-Buitrago, Beatriz; De Las Rivas, Javier et al. (2017) Epidermal Growth Factor Signaling towards Proliferation: Modeling and Logic Inference Using Forward and Backward Search. Biomed Res Int 2017:1809513
Hassan, Saima; Esch, Amanda; Liby, Tiera et al. (2017) Pathway-Enriched Gene Signature Associated with 53BP1 Response to PARP Inhibition in Triple-Negative Breast Cancer. Mol Cancer Ther 16:2892-2901
Sears, Rosalie; Gray, Joe W (2017) Epigenomic Inactivation of RasGAPs Activates RAS Signaling in a Subset of Luminal B Breast Cancers. Cancer Discov 7:131-133
Gendelman, Rina; Xing, Heming; Mirzoeva, Olga K et al. (2017) Bayesian Network Inference Modeling Identifies TRIB1 as a Novel Regulator of Cell-Cycle Progression and Survival in Cancer Cells. Cancer Res 77:1575-1585
Hafner, Marc; Heiser, Laura M; Williams, Elizabeth H et al. (2017) Quantification of sensitivity and resistance of breast cancer cell lines to anti-cancer drugs using GR metrics. Sci Data 4:170166
Xu, Xiaowei; De Angelis, Carmine; Burke, Kathleen A et al. (2017) HER2 Reactivation through Acquisition of the HER2 L755S Mutation as a Mechanism of Acquired Resistance to HER2-targeted Therapy in HER2+ Breast Cancer. Clin Cancer Res 23:5123-5134
Hill, Steven M; Nesser, Nicole K; Johnson-Camacho, Katie et al. (2017) Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling. Cell Syst 4:73-83.e10

Showing the most recent 10 out of 193 publications