Blood vessels supply the nutrients necessary for organ & tissue function—every action is dependent upon a healthy, intact vasculature. Indeed, over 70 diseases are angiogenesis-related. Cancers represent a well-known angiogenesis-related disease. Here, abnormal blood vessels sustain tumor growth, development, and metastasis. However, anti-angiogenic therapies only moderately affect patient survival, ultimately leading to patient resistance.

We believe that unraveling vascular signaling complexities can occur by engineering quantitative experimental tools and computational models. Our research directly addresses this need, applying a “bottom-up,” systems biology paradigm to measure, integrate, and simulate mechanisms regulating angiogenesis.

Protein Quantification: Measuring Protein Concentrations

Why are protein data necessary? In order for  computational models to accurately predict cell response, they require data on the molecules that elicit cell response. Proteins are the cell signaling transducers, so predicting cell behavior requires protein data.

There are a plethora of qualitative data available on protein expression (e.g., Western blots) and protein-protein interactions (e.g., Co-IP). Unfortunately, there are few quantitative data available. Our work aims to overcome this challenge by measuring: (1) plasma membrane protein concentrations via quantitative flow (qFlow) cytometry and (2) protein-protein interaction kinetics via surface plasmon resonance (SPR).

In vitro receptor quantification: We measure protein concentrations on several commonly used primary and expanded cell lines, in vitro, including: HUVECs, human dermal microvascular endothelial cells (HDMECs), human dermal lymphatic microvascular endothelial cells (HDLMECs), human dermal fibroblasts (HDFs), human tumor cells (MDA-MB-231, MCF-7, and U87), mouse fibroblasts (BALB/3T3 clone A31), mouse macrophages (RAW 264.7).  

Ex vivo receptor quantification: We have quantified receptors on endothelial cells from mouse skeletal muscle and two pre-clinical models of human vascular dysfunction: peripheral artery disease (PAD) and breast cancer. We are currently quantifying receptors in glioblastomas, ovarian cancers, and and peripheral blood cell samples.

Protein-protein interaction (PPI) quantification: We measure the association and kinetics of VEGFs-to-VEGFRs; engineered probes-to-Integrins; and cross-family interactions PDGFs-to-VEGFRs and VEGFs-to-PDGFRs.  We are currently optimizing cell-based PPI quantification.

Exploring a New Signaling Paradigm: Cross-family Binding

Non-canonical or cross-family interactions, which involve growth factors from one family binding to receptors of another family offers a powerful scheme for understanding ligand-receptor signaling, and ultimately, manipulating it for therapeutic purposes. We recently discovered high-affinity cross-family PDGF:VEGFR binding. We are currently examining the signaling implications of this novel set of  interactions.

New Biological Insight via Computation

Our computational models are exploring several key questions in vascular signaling: 

  • We are examining the roles of VEGFRs as predictors of drug resistance in cancer.
  • We are examining how the structure of the VEGFR1 leads to signaling and angiogenic cell function
  • We are exploring how cross-family binding leads to functional angiogenic signaling.
  • We are ranking signaling occurring via the canonical RTK pathways (e.g., PDGFRs, IGFR1, EGFR, VEGFRs, Tie2, and FGFR1).

Together this integrative approach is advancing us towards rational control of angiogenesis.

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