Abstract 924: A mathematical-experimental approach for predicting host responses in a preclinical model for trastuzumab-treated HER2+ breast cancer
Authors: Jarrett Angela M. , Bloom Meghan , Godfrey Wesley , Syed Anum , Ekrut David A. , Ehrlich Lauren I. , Yankeelov Thomas E. , Sorace Anna G. 
Published: August 2018

Introduction: Trastuzumab, a targeted therapy for human epidermal growth factor receptor 2 (HER2) positive breast cancer, induces cell cycle arrest and inhibits HER2 expression. Trastuzumab has been shown to improve vascular delivery of subsequent cytotoxic therapies, but the mechanism by which it regulates tumor-associated angiogenesis is not well characterized. Therefore, we developed an integrated, mathematical-experimental approach to systematically investigate the interactions of tumor-growth characteristics—vasculature, immune response, hypoxia, and necrosis—and to evaluate their effects on tumor response to treatment in a murine model of HER2+ breast cancer.

Experimental: Mice (N=102) were injected subcutaneously with HER2-overexpressing BT474 breast cancer cells and treated with trastuzumab (10 mg/kg) or saline. Tumor volumes for two separate cohorts of treated and control mice were recorded longitudinally, and either mice were quantitatively imaged or tumors extracted for histology over seven days. Necrosis, vasculature, and hypoxia were characterized by: immunohistochemistry for percent necrosis, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the percentage of well-vascularized tissue, and 18F-fluoromisonidazole positron emission tomography (FMISO-PET) for percent hypoxia. Preliminary immune (myeloid) cell infiltration was quantified using immunofluorescence of F4/80 and CD11c.

Mathematical Model: A system of five coupled, ordinary differential equations describing the temporal variation in tumor growth, vasculature, hypoxia, necrosis, and immune response was calibrated using data for tumor volume and percentages of well-vascularized tissue, hypoxia, and necrosis. After validation using a second tumor volume data set, uncertainty analysis was used to verify plausible overlap between the model's simulations and the experimental data when considering calibration error, and sensitivity analysis identified critical parameters for experimental estimation and potential model reductions.

Results and Discussion: The calibrated model was used to predict immune response behavior over time and yielded different results between the two groups—stagnant versus increasing immune component values for control versus treated mice, respectively. Preliminary immunofluorescence data support the immunological predictions of the model; in particular, F4/80 and CD11c co-staining in the total tissue is greater in trastuzumab treated than control tumors (p &lt; 0.03). Furthermore, differences in the calibrated parameter sets indicate several experimentally testable hypotheses, including increased cross-talk between immune cells and vasculature as a mechanism for vascular stabilization due to trastuzumab therapy.

We acknowledge the support of CPRIT RR160005 and NCI R01CA186193.

Citation Format: Angela M. Jarrett, Meghan Bloom, Wesley Godfrey, Anum Syed, David A. Ekrut, Lauren I. Ehrlich, Thomas E. Yankeelov, Anna G. Sorace. A mathematical-experimental approach for predicting host responses in a preclinical model for trastuzumab-treated HER2+ breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 924.