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.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
2R01CA138264-06A1
Application #
8756923
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Couch, Jennifer A
Project Start
2009-02-13
Project End
2019-07-31
Budget Start
2014-08-26
Budget End
2015-07-31
Support Year
6
Fiscal Year
2014
Total Cost
$526,097
Indirect Cost
$201,346
Name
Johns Hopkins University
Department
Biomedical Engineering
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Finley, Stacey D; Chu, Liang-Hui; Popel, Aleksander S (2015) Computational systems biology approaches to anti-angiogenic cancer therapeutics. Drug Discov Today 20:187-97
Stamatelos, Spyros K; Kim, Eugene; Pathak, Arvind P et al. (2014) A bioimage informatics based reconstruction of breast tumor microvasculature with computational blood flow predictions. Microvasc Res 91:8-21
Norton, Kerri-Ann; Popel, Aleksander S (2014) An agent-based model of cancer stem cell initiated avascular tumour growth and metastasis: the effect of seeding frequency and location. J R Soc Interface 11:20140640
Lee, Esak; Pandey, Niranjan B; Popel, Aleksander S (2014) Lymphatic endothelial cells support tumor growth in breast cancer. Sci Rep 4:5853
Chu, Liang-Hui; Lee, Esak; Bader, Joel S et al. (2014) Angiogenesis interactome and time course microarray data reveal the distinct activation patterns in endothelial cells. PLoS One 9:e110871
Vempati, Prakash; Popel, Aleksander S; Mac Gabhann, Feilim (2014) Extracellular regulation of VEGF: isoforms, proteolysis, and vascular patterning. Cytokine Growth Factor Rev 25:1-19
Lee, Esak; Pandey, Niranjan B; Popel, Aleksander S (2014) Pre-treatment of mice with tumor-conditioned media accelerates metastasis to lymph nodes and lungs: a new spontaneous breast cancer metastasis model. Clin Exp Metastasis 31:67-79
Lee, Esak; Fertig, Elana J; Jin, Kideok et al. (2014) Breast cancer cells condition lymphatic endothelial cells within pre-metastatic niches to promote metastasis. Nat Commun 5:4715
Rosca, Elena V; Penet, Marie-France; Mori, Noriko et al. (2014) A biomimetic collagen derived peptide exhibits anti-angiogenic activity in triple negative breast cancer. PLoS One 9:e111901
Imoukhuede, Princess I; Popel, Aleksander S (2014) Quantitative fluorescent profiling of VEGFRs reveals tumor cell and endothelial cell heterogeneity in breast cancer xenografts. Cancer Med 3:225-44

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