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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.

Our Research Projects


Law of mass action

What are VEGFRs?

Angiogenesis, the growth of blood vessels from pre-existing vasculature, is primarily regulated by vascular endothelial growth factor receptors (VEGFRs). Dysregulated VEGFR signaling is associated with cancers, obesity, and over 70 vascular diseases; thus, VEGFRs are extensively studied as promising biomarkers and targets for vascular dysfunctions.

Why are quantitative receptor protein data necessary?

In order for computational models to accurately predict cell response, they require data on the molecules that elicit cell response. Receptor proteins are the cell signaling transducers, so predicting cell behavior requires receptor 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 little 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), and mouse macrophages (RAW 264.7).

qflow cytometry
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, normal vs. obese fat tissues, and circulating cells from peripheral blood 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.

Related Reads:
Computational Systems Biology for the VEGF Family in Angiogenesis 

Systems Biology Will Direct Vascular-Targeted Therapy for Obesity

The Convergence of Cell-Based Surface Plasmon Resonance and Biomaterials: The Future of Quantifying Bio-molecular Interactions—A Review

qFlow Cytometry-Based Receptoromic Screening:
A High-Throughput Quantification Approach
Informing Biomarker Selection and Nanosensor

Cross-family interactions

Targeting VEGF:VEGFR signaling axis alone has not achieved the promise of stable vascular control, so new approaches are needed to control and direct vascular development.

Toward this goal, we examine a novel paradigm of network regulation called cross-family signaling, in which members from one growth factor family (e.g., platelet-derived growth factors (PDGFs)) bind to and signal through members of another family (e.g., VEGFRs). Cross-family interactions offer a powerful scheme for understanding ancillary ligand-receptor signaling, and ultimately, manipulating it for therapeutic purposes.

Studying cross-family interactions needs to account for the complexity of additional, multi-component signaling networks, a goal that can be achieved via data-driven, computational systems biology in close concert with experimental analysis of signaling and functional response. Our research goal is to biologically and computationally assess how the new theory of cross-family signaling may control vascular signaling at the molecular, protein, and cellular levels.

We hypothesize that systematic examination of protein structure and downstream signaling within the cross-family paradigm via simulation, ligand-engineering, network quantification, and computational modeling can uncover novel mechanisms to control angiogenesis. We are testing this hypothesis through three aims: (1) sensitively quantifying receptor activation rates and functional responses of cross-family binding (e.g., proliferation, migration, and barrier function); (2) predicting and measuring the structural properties of cross-family binding via molecular simulations and directed evolution; and (3) developing validated deterministic models (mass-action kinetic modeling) of cross- family signaling and applying them to study and control the dynamics of cross-family signaling in human cell systems, in silico. We are primed to lead this new research because we are among the first to pursue this important theoretical paradigm, and we lead this cause to understand cell signaling via structure/function-based computational modeling. This work will catalyze a shift in perspective and innovation in the areas of cell signaling, systems biology, and the predictive design of obesity-focused therapies.

Cross-family interactions also show important implications in vascular ciliopathy (disordered cilia). Cilia are the mechano- and chemo-sensory organelles that project into the lumen of blood vessels from the apical membrane of endothelia. Patients with vascular ciliopathy are at increased risk for aneurysm formation (AF) and consequent cerebral hemorrhage (CH), which contribute to morbidity and mortality. Ciliopathy patients are 10 times more likely than the general population to have vascular aneurysms, and AF occurs in patients as young as three years old, increasing the likelihood for CH in young kids. Therefore, there is a pressing need to understand the signaling mechanisms that lead to vascular ciliopathy and for manipulating the key mechanisms for therapeutic purposes.

PDGFs (particularly PDGF-BB) and VEGF act in concert to induce the formation and stabilization of new blood vessels. We recently discovered high-affinity cross-family PDGF:VEGFR binding. Preliminary data also suggest that PDGF-BB:VEGFR2 interaction may mediate brain vascular cilial formation via Pak2-Arl13b pathway. We are using computational modeling to assess the PDGF-BB/Pak2/Arl13b signaling involved in brain vascular cilia formation and stability.

Related Reads:

Discovery of High-Affinity PDGF-VEGFR Interactions: Redefining RTK Dynamics

Improving the efficacy and safety for oxytocin use in labor and delivery

Oxytocin is administered to approximately one-half of the four million women who give birth in the United States each year.

A significant challenge for providers is that the oxytocin dose required to induce or augment labor varies by up to 20-fold, and they have no way to predict how, or even whether, a woman will respond to a given dose. This lack of predictability raises important safety concerns and underlies oxytocin’s association with adverse maternal events and neonatal outcomes. Thus, it is essential to develop a method to predict oxytocin responsiveness and thereby personalize the dosing regimens.

Our lab uses quantitative and computational approaches to define the cellular and molecular underpinnings of disease and has specific expertise in the quantitative analysis of receptors. Our goal is to develop computational models to predict oxytocin receptor function in uterine smooth muscle cells and how oxytocin signaling and functions are affected by oxytocin receptor gene variants. Successful completion of this project will provide important information regarding the influence of OXTR variants on responsiveness to oxytocin.

Related Reads:

Imoukhuede teams with England on $2.4M NIH grant

Naturally Occurring Genetic Variants in the Oxytocin Receptor Alter Receptor Signaling Profiles