This research will focus on triple-negative breast cancer (TNBC), which is highly metastatic, has the worst prognosis among breast cancer subtypes, and is lacking effective therapies. Interactions between different cell types in the tumor microenvironment and metastatic niches are determinants of metastatic progression. In particular, tumor angiogenesis plays an important role since tumors require blood supply to grow and metastasize. A quantitative understanding of the complexity of these interactions is presently lacking. To achieve a better understanding of these processes, the development of predictive experiment-based molecular-detailed computational models of tumor growth and metastasis is necessary. The long-term goal of this project is to develop experiment-based mechanistic models of breast cancer and apply them to modeling therapeutic interventions. Specifically, we will use experimental and computational approaches to: (1) investigate key angiogenic factors, cytokines and chemokines in the progression of breast tumors to metastases;(2) investigate the characteristics of lung metastasis, the most common site for TNBC metastases;(3) test anti-metastatic agents by targeting selective cytokines, angiogenic factors and chemokines. The computational developments will be tightly coupled to the cutting-edge imaging techniques at the molecular, cellular, microvascular, and tissue levels. Invasive human breast cancer cell lines will be used to generate orthotopic xenografts in the mammary fat pad of female mice. The measurements will include the characterization and localization of receptor and ligand expression for a wide range of molecules of the VEGF family together with selected cytokines and chemokines at different stages of tumor growth and metastasis, such as interleukin-6 and CCL5;temporal and spatial development of hypoxia and microvasculature in growing tumors, and functional characteristics of the tumor vasculature and interstitium, e.g. blood volume, vascular permeability, diffusive transport in the tumor extracellular matrix (ECM). Immunohistochemistry and 3D microscopy will be used to characterize lung metastases. Part of these data will serve as the input to computational models and part used for model validation. Several therapeutic, anti-metastatic agents targeting selective cytokines, chemokines and angiogenic factors will be used, and their molecular interactions and transport will be modeled using ordinary differential equation-based compartmental models, three-dimensional partial differential equation-based models, agent-based models, and hybrid models. The research will contribute to a fundamental understanding of breast cancer biology, to the identification of therapeutic targets and biomarkers, and to a quantitative interpretation of clinical data. The synergistic combination of computational and experimental studies will provide significant insights into metastatic TNBC.

Public Health Relevance

Breast cancer is the most commonly diagnosed female malignancy in the United States. The goal of the project is to couple computational modeling with state-of-the-art imaging and signaling experimental studies at the molecular, cellular, microvascular, tissue and organ levels, to provide a better quantitative understanding of breast cancer and to test anti-metastatic agents that could lead to translational applications.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Modeling and Analysis of Biological Systems Study Section (MABS)
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Couch, Jennifer A
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Johns Hopkins University
Biomedical Engineering
Schools of Medicine
United States
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Bazzazi, Hojjat; Zhang, Yu; Jafarnejad, Mohammad et al. (2018) Computational modeling of synergistic interaction between ?V?3 integrin and VEGFR2 in endothelial cells: Implications for the mechanism of action of angiogenesis-modulating integrin-binding peptides. J Theor Biol 455:212-221
Jin, Kideok; Pandey, Niranjan B; Popel, Aleksander S (2018) Simultaneous blockade of IL-6 and CCL5 signaling for synergistic inhibition of triple-negative breast cancer growth and metastasis. Breast Cancer Res 20:54
Norton, Kerri-Ann; Jin, Kideok; Popel, Aleksander S (2018) Modeling triple-negative breast cancer heterogeneity: Effects of stromal macrophages, fibroblasts and tumor vasculature. J Theor Biol 452:56-68
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Norton, Kerri-Ann; Wallace, Travis; Pandey, Niranjan B et al. (2017) An agent-based model of triple-negative breast cancer: the interplay between chemokine receptor CCR5 expression, cancer stem cells, and hypoxia. BMC Syst Biol 11:68
Bazzazi, Hojjat; Isenberg, Jeffery S; Popel, Aleksander S (2017) Inhibition of VEGFR2 Activation and Its Downstream Signaling to ERK1/2 and Calcium by Thrombospondin-1 (TSP1):In silicoInvestigation. Front Physiol 8:48
Zhao, Chen; Isenberg, Jeffrey S; Popel, Aleksander S (2017) Transcriptional and Post-Transcriptional Regulation of Thrombospondin-1 Expression: A Computational Model. PLoS Comput Biol 13:e1005272
Bazzazi, Hojjat; Popel, Aleksander S (2017) Computational investigation of sphingosine kinase 1 (SphK1) and calcium dependent ERK1/2 activation downstream of VEGFR2 in endothelial cells. PLoS Comput Biol 13:e1005332
Noren, David P; Chou, Wesley H; Lee, Sung Hoon et al. (2016) Endothelial cells decode VEGF-mediated Ca2+ signaling patterns to produce distinct functional responses. Sci Signal 9:ra20

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