Quantification of VEGFRs, NRP1, and PDGFRs on Endothelial Cells and Fibroblasts Reveals Serum, Intra-Family Ligand, and Cross-Family Ligand Regulation

Cross-family interactions of vascular endothelial growth factors and platelet-derived growth factors on the endothelial cell surface: A computational model

Angiogenesis, the formation of new vessels from existing vessels, is mediated by vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF). Despite discoveries supporting the cross-family interactions between VEGF and PDGF families, sharing the binding partners between them makes it challenging to identify growth factors that predominantly affect angiogenesis. Systems biology offers promises to untangle this complexity. Thus, in this study, we developed a mass-action kinetics-based computational model for cross-family interactions between VEGFs (VEGF-A, VEGF-B, and PlGF) and PDGFs (PDGF-AA, PDGF-AB, and PDGF-BB) with their receptors (VEGFR1, VEGFR2, NRP1, PDGFRα, and PDGFRβ). The model, parametrized with our literature mining and surface resonance plasmon assays, was validated by comparing the concentration of VEGFR1 complexes with a previously constructed angiogenesis model. The model predictions include five outcomes: 1) the percentage of free or bound ligands and 2) receptors, 3) the concentration of free ligands, 4) the percentage of ligands occupying each receptor, and 5) the concentration of ligands that is bound to each receptor. We found that at equimolar ligand concentrations (1 nM), PlGF and VEGF-A were the main binding partners of VEGFR1 and VEGFR2, respectively. Varying the density of receptors resulted in the following five outcomes: 1) Increasing VEGFR1 density depletes the free PlGF concentration, 2) increasing VEGFR2 density decreases PDGF:PDGFRα complexes, 3) increased NRP1 density generates a biphasic concentration of the free PlGF, 4) increased PDGFRα density increases PDGFs:PDGFRα binding, and 5) increasing PDGFRβ density increases VEGF-A:PDGFRβ. Our model offers a reproducible, fundamental framework for exploring cross-family interactions that can be extended to the tissue level or intracellular molecular level. Also, our model may help develop therapeutic strategies in pathological angiogenesis by identifying the dominant complex in the cell signaling.

Author summary

New blood vessel formation from existing ones is essential for growth, healing, and reproduction. However, when this process is disrupted-either too much or too little-it can contribute to diseases such as cancer and peripheral arterial disease. Two key families of proteins, vascular endothelial growth factors (VEGFs) and platelet-derived growth factors (PDGFs), regulate this process. Traditionally, scientists believed that VEGFs only bind to VEGF receptors and PDGFs to PDGF receptors. However, recent findings show that these proteins can interact with each other's receptors, making it more challenging to understand and control blood vessel formation. To clarify these complex interactions, we combined computer modeling with biological data to map out which proteins bind to which receptors and to what extent. Our findings show that when VEGFs and PDGFs are present in equal amounts, VEGFs are the primary binding partners for VEGF receptors. We also explored how changes in receptor levels affect these interactions in disease-like conditions. This work provides a foundational computational model for studying cross-family interactions, which can be expanded to investigate tissue-level effects and processes inside cells. Ultimately, our model may help develop better treatments for diseases linked to abnormal blood vessel growth by identifying key protein-receptor interactions.

Sex Differences in VEGF and PDGF Ligand and Receptor Protein Expression during Adipose Tissue Expansion and Regression

Inadequate angiogenesis in obesogenic adipose tissue (AT) has been implicated in disrupted adipogenesis and metabolic disorders. Yet, key cellular and molecular regulators of AT angiogenesis remain largely unidentified. This study sought to identify the dysregulated elements within the Vascular Endothelial Growth Factor (VEGF) and Platelet-Derived Growth Factor (PDGF) systems during obesity progression. We employ a mouse model, comprising both male and female mice, to investigate the changes in the VEGF/PDGF concentration and their receptor distribution in AT during short- and long-term weight gain and weight loss. Our results reveal pronounced sex-specific differences in obesity progression, with male and female mice exhibiting distinct angiogenic ligand and receptor profiles under identical dietary interventions. This data also lays the groundwork for developing computational models of VEGF/PDGF signaling networks in AT, allowing for the simulation of complex biological interactions and the prediction of therapeutic outcomes.

Understanding the effects of oxytocin receptor variants on OXT-OXT receptor binding: A mathematical model

Approximately half of U.S. women giving birth annually receive Pitocin, the synthetic form of oxytocin (OXT), yet its effective dose can vary significantly. This variability presents safety concerns due to unpredictable responses, which may lead to adverse outcomes for both mother and baby. To address the need for improved dosing, we developed a data-driven mathematical model to predict OXT receptor (OXTR) binding. Our study focuses on five prevalent OXTR variants (V45L, P108A, L206V, V281M, and E339K) and their impact on OXT-OXTR binding dynamics in two distinct cell types: human embryonic kidney cells (HEK293T), commonly used in experimental systems, and human myometrial smooth muscle cells, containing endogenous OXTR. We parameterized the model with cell-specific OXTR surface localization measurements. To strengthen the robustness of our study, we conducted a comprehensive meta-analysis of OXT- OXTR binding, enabling parameterization of our model with cell-specific OXT-OXTR binding kinetics (myometrial OXT-OXTR K d = 1.6 nM, kon = 6.8 × 10 5 M -1 min -1 , and koff = 0.0011 min -1 ). Our meta-analysis revealed significant homogeneity in OXT-OXTR affinity across experiments and species with a K d = 0.52 - 9.32 nM and mean K d = 1.48 ± 0.36 nM. Our model achieves several valuable insights into designing dosage strategies. First, we predicted that the OXTR complex reaches maximum occupancy at 10 nM OXT in myometrial cells and at 1 µM in HEK293T cells. This information is pivotal for guiding experimental design and data interpretation when working with these distinct cell types, emphasizing the need to consider effects for specific cell types when choosing OXTR-transfected cell lines. Second, our model recapitulated the significant effects of genetic variants for both experimental and physiologically relevant systems, with V281M and E339K substantially compromising OXT-OXTR binding capacity. These findings suggest the need for personalized oxytocin dosing based on individual genetic profiles to enhance therapeutic efficacy and reduce risks, especially in the context of labor and delivery. Third, we demonstrated the potential for rescuing the attenuated cell response observed in V281M and E339K variants by increasing the OXT dosage at specific, early time points. Cellular responses to OXT, including Ca 2+ release, manifest within minutes. Our model indicates that providing V281M- and E339K-expressing cells with doubled OXT dose during the initial minute of binding can elevate OXT-OXTR complex formation to levels comparable to wild-type OXTR. In summary, our study provides a computational framework for precision oxytocin dosing strategies, paving the way for personalized medicine.

Quantification of surface-localized and total oxytocin receptor in myometrial smooth muscle cells

Oxytocin acts through the oxytocin receptor (OXTR) to modulate uterine contractility. We previously identified OXTR genetic variants and showed that, in HEK293T cells, two of the OXTR protein variants localized to the cell surface less than wild-type OXTR. Here, we sought to measure OXTR in the more native human myometrial smooth muscle cell (HMSMC) line on both the cell-surface and across the whole cell, and used CRISPR editing to add an HA tag to the endogenous OXTR gene for anti-HA measurement. Quantitative flow cytometry revealed that these cells possessed 55,000 ± 3200 total OXTRs and 4900 ± 390 cell-surface OXTRs per cell. To identify any differential wild-type versus variant localization, we transiently transfected HMSMCs to exogenously express wild-type or variant OXTR with HA and green fluorescent protein tags. Total protein expression of wild-type OXTR and all tested variants were similar. However, the two variants with lower surface localization in HEK293T cells also presented lower surface localization in HMSMCs. Overall, we confirm the differential surface localization of variant OXTR in a more native cell type, and further demonstrate that the quantitative flow cytometry technique is adaptable to whole-cell measurements.

Toward Blood-Based Precision Medicine: Identifying Age-Sex-Specific Vascular Biomarker Quantities on Circulating Vascular Cells

Introduction

Abnormal angiogenesis is central to vascular disease and cancer, and noninvasive biomarkers of vascular origin are needed to evaluate patients and therapies. Vascular endothelial growth factor receptors (VEGFRs) are often dysregulated in these diseases, making them promising biomarkers, but the need for an invasive biopsy has limited biomarker research on VEGFRs. Here, we pioneer a blood biopsy approach to quantify VEGFR plasma membrane localization on two circulating vascular proxies: circulating endothelial cells (cECs) and circulating progenitor cells (cPCs).

Methods

Using quantitative flow cytometry, we examined VEGFR expression on cECs and cPCs in four age-sex groups: peri/premenopausal females (aged < 50 years), menopausal/postmenopausal females (≥ 50 years), and younger and older males with the same age cut-off (50 years).

Results

cECs in peri/premenopausal females consisted of two VEGFR populations: VEGFR-low (~ 55% of population: population medians ~ 3000 VEGFR1 and 3000 VEGFR2/cell) and VEGFR-high (~ 45%: 138,000 VEGFR1 and 39,000-236,000 VEGFR2/cell), while the menopausal/postmenopausal group only possessed the VEGFR-low cEC population; and 27% of cECs in males exhibited high plasma membrane VEGFR expression (206,000 VEGFR1 and 155,000 VEGFR2/cell). The absence of VEGFR-high cEC subpopulations in menopausal/postmenopausal females suggests that their high-VEGFR cECs are associated with menstruation and could be noninvasive proxies for studying the intersection of age-sex in angiogenesis. VEGFR1 plasma membrane localization in cPCs was detected only in menopausal/postmenopausal females, suggesting a menopause-specific regenerative mechanism.

Conclusions

Overall, our quantitative, noninvasive approach targeting cECs and cPCs has provided the first insights into how sex and age influence VEGFR plasma membrane localization in vascular cells.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-023-00771-1.

Axl and Vascular Endothelial Growth Factor Receptors Exhibit Variations in Membrane Localization and Heterogeneity Across Monolayer and Spheroid High-Grade Serous Ovarian Cancer Models

Vascular endothelial growth factor receptors (VEGFRs) and Axl are receptor tyrosine kinases (RTK) that are targeted in ovarian cancer therapy. Two-dimensional monolayer culture and three-dimensional spheroids are common models for RTK-targeted drug screening: monolayers are simple and economical while spheroids include several genetic and histological tumor features. RTK membrane localization dictates RTK signaling and drug response, however, it is not characterized in these models. We quantify plasma membrane RTK concentrations and show differential RTK abundance and heterogeneity in monolayers versus spheroids. We show VEGFR1 concentrations on the plasma membrane to be 10 times higher in OVCAR8 spheroids than in monolayers; OVCAR8 spheroids are more heterogeneous than monolayers, exhibiting a bimodal distribution of a low-Axl (6200/cell) and a high-Axl subpopulation (25,000/cell). In addition, plasma membrane Axl concentrations differ by 100 times between chemosensitive (OVCAR3) and chemoresistant (OVCAR8) cells and by 10 times between chemoresistant cell lines (OVCAR5 vs. OVCAR8). These systematic findings can guide ovarian cancer model selection for drug screening.

Absolute Quantification of Plasma Membrane Receptors Via Quantitative Flow Cytometry

Plasma membrane receptors are transmembrane proteins that initiate cellular response following the binding of specific ligands (e.g., growth factors, hormones, and cytokines). The abundance of plasma membrane receptors can be a diagnostic or prognostic biomarker in many human diseases. One of the best techniques for measuring plasma membrane receptors is quantitative flow cytometry (qFlow). qFlow employs fluorophore-conjugated antibodies against the receptors of interest and corresponding fluorophore-loaded calibration beads offers standardized and reproducible measurements of plasma membrane receptors. More importantly, qFlow can achieve absolute quantification of plasma membrane receptors when phycoerythrin (PE) is the fluorophore of choice. Here we describe a detailed qFlow protocol to obtain absolute receptor quantities on the basis of PE calibration. This protocol is foundational for many previous and ongoing studies in quantifying tyrosine kinase receptors and G-protein-coupled receptors with in vitro cell models and ex vivo cell samples.

VEGF-A splice variants bind VEGFRs with differential affinities

Vascular endothelial growth factor A (VEGF-A) and its binding to VEGFRs is an important angiogenesis regulator, especially the earliest-known isoform, VEGF-A165a. Yet several additional splice variants play prominent roles in regulating angiogenesis in health and in vascular disease, including VEGF-A121 and an anti-angiogenic variant, VEGF-A165b. Few studies have attempted to distinguish these forms from their angiogenic counterparts, experimentally. Previous studies of VEGF-A:VEGFR binding have measured binding kinetics for VEGFA165 and VEGF-A121, but binding kinetics of the other two pro- and all anti-angiogenic splice variants are not known. We measured the binding kinetics for VEGF-A165, -A165b, and -A121 with VEGFR1 and VEGF-R2 using surface plasmon resonance. We validated our methods by reproducing the known affinities between VEGF-A165a:VEGFR1 and VEGF-A165a:VEGFR2, 1.0 pM and 10 pM respectively, and validated the known affinity VEGF-A121:VEGFR2 as KD = 0.66 nM. We found that VEGF-A121 also binds VEGFR1 with an affinity KD = 3.7 nM. We further demonstrated that the anti-angiogenic variant, VEGF-A165b selectively prefers VEGFR2 binding at an affinity = 0.67 pM while binding VEGFR1 with a weaker affinity-KD = 1.4 nM. These results suggest that the - A165b anti-angiogenic variant would preferentially bind VEGFR2. These discoveries offer a new paradigm for understanding VEGF-A, while further stressing the need to take care in differentiating the splice variants in all future VEGF-A studies.

Systems Biology Will Direct Vascular-Targeted Therapy for Obesity

Healthy adipose tissue expansion and metabolism during weight gain require coordinated angiogenesis and lymphangiogenesis. These vascular growth processes rely on the vascular endothelial growth factor (VEGF) family of ligands and receptors (VEGFRs). Several studies have shown that controlling vascular growth by regulating VEGF:VEGFR signaling can be beneficial for treating obesity; however, dysregulated angiogenesis and lymphangiogenesis are associated with several chronic tissue inflammation symptoms, including hypoxia, immune cell accumulation, and fibrosis, leading to obesity-related metabolic disorders. An ideal obesity treatment should minimize adipose tissue expansion and the advent of adverse metabolic consequences, which could be achieved by normalizing VEGF:VEGFR signaling. Toward this goal, a systematic investigation of the interdependency of vascular and metabolic systems in obesity and tools to predict personalized treatment ranges are necessary to improve patient outcomes through vascular-targeted therapies. Systems biology can identify the critical VEGF:VEGFR signaling mechanisms that can be targeted to regress adipose tissue expansion and can predict the metabolic consequences of different vascular-targeted approaches. Establishing a predictive, biologically faithful platform requires appropriate computational models and quantitative tissue-specific data. Here, we discuss the involvement of VEGF:VEGFR signaling in angiogenesis, lymphangiogenesis, adipogenesis, and macrophage specification – key mechanisms that regulate adipose tissue expansion and metabolism. We then provide useful computational approaches for simulating these mechanisms, and detail quantitative techniques for acquiring tissue-specific parameters. Systems biology, through computational models and quantitative data, will enable an accurate representation of obese adipose tissue that can be used to direct the development of vascular-targeted therapies for obesity and associated metabolic disorders.

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

Cell biology is driven by complex networks of biomolecular interactions. Characterizing the kinetic and thermodynamic properties of these interactions is crucial to understanding their role in different physiological processes. Surface plasmon resonance (SPR)-based approaches have become a key tool in quantifying biomolecular interactions, however conventional approaches require isolating the interacting components from the cellular system. Cell-based SPR approaches have recently emerged, promising to enable precise measurements of biomolecular interactions within their normal biological context. Two major approaches have been developed, offering their own advantages and limitations. These approaches currently lack a systematic exploration of 'best practices' like those existing for traditional SPR experiments. Toward this end, we describe the two major approaches, and identify the experimental parameters that require exploration, and discuss the experimental considerations constraining the optimization of each. In particular, we discuss the requirements of future biomaterial development needed to advance the cell-based SPR technique.

Mathematical Model Predicts Effective Strategies to Inhibit VEGF-eNOS Signaling

The endothelial nitric oxide synthase (eNOS) signaling pathway in endothelial cells has multiple physiological significances. It produces nitric oxide (NO), an important vasodilator, and enables a long-term proliferative response, contributing to angiogenesis. This signaling pathway is mediated by vascular endothelial growth factor (VEGF), a pro-angiogenic species that is often targeted to inhibit tumor angiogenesis. However, inhibiting VEGF-mediated eNOS signaling can lead to complications such as hypertension. Therefore, it is important to understand the dynamics of eNOS signaling in the context of angiogenesis inhibitors. Thrombospondin-1 (TSP1) is an important angiogenic inhibitor that, through interaction with its receptor CD47, has been shown to redundantly inhibit eNOS signaling. However, the exact mechanisms of TSP1's inhibitory effects on this pathway remain unclear. To address this knowledge gap, we established a molecular-detailed mechanistic model to describe VEGF-mediated eNOS signaling, and we used the model to identify the potential intracellular targets of TSP1. In addition, we applied the predictive model to investigate the effects of several approaches to selectively target eNOS signaling in cells experiencing high VEGF levels present in the tumor microenvironment. This work generates insights for pharmacologic targets and therapeutic strategies to inhibit tumor angiogenesis signaling while avoiding potential side effects in normal vasoregulation.

Sex differences in cancer mechanisms

We now know that cancer is many different diseases, with great variation even within a single histological subtype. With the current emphasis on developing personalized approaches to cancer treatment, it is astonishing that we have not yet systematically incorporated the biology of sex differences into our paradigms for laboratory and clinical cancer research. While some sex differences in cancer arise through the actions of circulating sex hormones, other sex differences are independent of estrogen, testosterone, or progesterone levels. Instead, these differences are the result of sexual differentiation, a process that involves genetic and epigenetic mechanisms, in addition to acute sex hormone actions. Sexual differentiation begins with fertilization and continues beyond menopause. It affects virtually every body system, resulting in marked sex differences in such areas as growth, lifespan, metabolism, and immunity, all of which can impact on cancer progression, treatment response, and survival. These organismal level differences have correlates at the cellular level, and thus, males and females can fundamentally differ in their protections and vulnerabilities to cancer, from cellular transformation through all stages of progression, spread, and response to treatment. Our goal in this review is to cover some of the robust sex differences that exist in core cancer pathways and to make the case for inclusion of sex as a biological variable in all laboratory and clinical cancer research. We finish with a discussion of lab- and clinic-based experimental design that should be used when testing whether sex matters and the appropriate statistical models to apply in data analysis for rigorous evaluations of potential sex effects. It is our goal to facilitate the evaluation of sex differences in cancer in order to improve outcomes for all patients.

Single-Cell Receptor Quantification of an In Vitro Coculture Angiogenesis Model Reveals VEGFR, NRP1, Tie2, and PDGFR Regulation and Endothelial Heterogeneity

Angiogenesis, the formation of new blood vessels from pre-existing ones, is essential for both normal development and numerous pathologies. Systems biology has offered a unique approach to study angiogenesis by profiling tyrosine kinase receptors (RTKs) that regulate angiogenic processes and computationally modeling RTK signaling pathways. Historically, this systems biology approach has been applied on ex vivo angiogenesis assays, however, these assays are difficult to quantify and limited in their potential of temporal analysis. In this study, we adopted a simple two-dimensional angiogenesis assay comprised of human umbilical vein endothelial cells (HUVECs) and human dermal fibroblasts (HDFs) and examined temporal dynamics of a panel of six RTKs and cell heterogeneity up to 17 days. We observed ~2700 VEGFR1 (vascular endothelial growth factor receptor 1) per cell on 24-h-old cocultured HDF plasma membranes, which do not express VEGFR when cultured alone. We observed 4000–8100 VEGFR2 per cell on cocultured HUVEC plasma membranes throughout endothelial tube formation. We showed steady increase of platelet-derived growth factor receptors (PDGFRs) on cocultured HDF plasma membranes, and more interestingly, 1900–2900 PDGFRβ per plasma membrane were found on HUVECs within the first six hours of coculturing. These quantitative findings will offer us insights into molecular regulation during angiogenesis and help assess in vitro tube formation models and their physiological relevance.

Characterizing Glioblastoma Heterogeneity via Single-Cell Receptor Quantification

Dysregulation of tyrosine kinase receptor (RTK) signaling pathways play important roles in glioblastoma (GBM). However, therapies targeting these signaling pathways have not been successful, partially because of drug resistance. Increasing evidence suggests that tumor heterogeneity, more specifically, GBM-associated stem and endothelial cell heterogeneity, may contribute to drug resistance. In this perspective article, we introduce a high-throughput, quantitative approach to profile plasma membrane RTKs on single cells. First, we review the roles of RTKs in cancer. Then, we discuss the sources of cell heterogeneity in GBM, providing context to the key cells directing resistance to drugs. Finally, we present our provisionally patented qFlow cytometry approach, and report results of a "proof of concept" patient-derived xenograft GBM study.

Integrative meta-modeling identifies endocytic vesicles, late endosome and the nucleus as the cellular compartments primarily directing RTK signaling

Recently, intracellular receptor signaling has been identified as a key component mediating cell responses for various receptor tyrosine kinases (RTKs). However, the extent each endocytic compartment (endocytic vesicle, early endosome, recycling endosome, late endosome, lysosome and nucleus) contributes to receptor signaling has not been quantified. Furthermore, our understanding of endocytosis and receptor signaling is complicated by cell- or receptor-specific endocytosis mechanisms. Therefore, towards understanding the differential endocytic compartment signaling roles, and identifying how to achieve signal transduction control for RTKs, we delineate how endocytosis regulates RTK signaling. We achieve this via a meta-analysis across eight RTKs, integrating computational modeling with experimentally derived cell (compartment volume, trafficking kinetics and pH) and ligand-receptor (ligand/receptor concentration and interaction kinetics) physiology. Our simulations predict the abundance of signaling from eight RTKs, identifying the following hierarchy in RTK signaling: PDGFRβ > IGFR1 > EGFR > PDGFRα > VEGFR1 > VEGFR2 > Tie2 > FGFR1. We find that endocytic vesicles are the primary cell signaling compartment; over 43% of total receptor signaling occurs within the endocytic vesicle compartment for these eight RTKs. Mechanistically, we found that high RTK signaling within endocytic vesicles may be attributed to their low volume (5.3 × 10^-19 L) which facilitates an enriched ligand concentration (3.2 μM per ligand molecule within the endocytic vesicle). Under the analyzed physiological conditions, we identified extracellular ligand concentration as the most sensitive parameter to change; hence the most significant one to modify when regulating absolute compartment signaling. We also found that the late endosome and nucleus compartments are important contributors to receptor signaling, where 26% and 18%, respectively, of average receptor signaling occurs across the eight RTKs. Conversely, we found very low membrane-based receptor signaling, exhibiting <1% of the total receptor signaling for these eight RTKs. Moreover, we found that nuclear translocation, mechanistically, requires late endosomal transport; when we blocked receptor trafficking from late endosomes to the nucleus we found a 57% reduction in nuclear translocation. In summary, our research has elucidated the significance of endocytic vesicles, late endosomes and the nucleus in RTK signal propagation.

Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling

BACKGROUND

Thrombospondin-1 (TSP1) is a matricellular protein that functions to inhibit angiogenesis. An important pathway that contributes to this inhibitory effect is triggered by TSP1 binding to the CD36 receptor, inducing endothelial cell apoptosis. However, therapies that mimic this function have not demonstrated clear clinical efficacy. This study explores strategies to enhance TSP1-induced apoptosis in endothelial cells. In particular, we focus on establishing a computational model to describe the signaling pathway, and using this model to investigate the effects of several approaches to perturb the TSP1-CD36 signaling network.

METHODS

We constructed a molecularly-detailed mathematical model of TSP1-mediated intracellular signaling via the CD36 receptor based on literature evidence. We employed systems biology tools to train and validate the model and further expanded the model by accounting for the heterogeneity within the cell population. The initial concentrations of signaling species or kinetic rates were altered to simulate the effects of perturbations to the signaling network.

RESULTS

Model simulations predict the population-based response to strategies to enhance TSP1-mediated apoptosis, such as downregulating the apoptosis inhibitor XIAP and inhibiting phosphatase activity. The model also postulates a new mechanism of low dosage doxorubicin treatment in combination with TSP1 stimulation. Using computational analysis, we predict which cells will undergo apoptosis, based on the initial intracellular concentrations of particular signaling species.

CONCLUSIONS

This new mathematical model recapitulates the intracellular dynamics of the TSP1-induced apoptosis signaling pathway. Overall, the modeling framework predicts molecular strategies that increase TSP1-mediated apoptosis, which is useful in many disease settings.

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

Nearly all studies of angiogenesis have focused on uni-family ligand-receptor binding, e.g., VEGFs bind to VEGF receptors, PDGFs bind to PDGF receptors, etc. The discovery of VEGF-PDGFRs binding challenges this paradigm and calls for investigation of other ligand-receptor binding possibilities. We utilized surface plasmon resonance to identify and measure PDGF-to-VEGFR binding rates, establishing cut-offs for binding and non-binding interactions. We quantified the kinetics of the recent VEGF-A:PDGFRβ interaction for the first time with K_D = 340 pM. We discovered new PDGF:VEGFR2 interactions with PDGF-AA:R2 K_D = 530 nM, PDGF-AB:R2 K_D = 110 pM, PDGF-BB:R2 K_D = 40 nM, and PDGF-CC:R2 K_D = 70 pM. We computationally predict that cross-family PDGF binding could contribute up to 96% of VEGFR2 ligation in healthy conditions and in cancer. Together the identification, quantification, and simulation of these novel cross-family interactions posits new mechanisms for understanding anti-angiogenic drug resistance and presents an expanded role of growth factor signaling with significance in health and disease.

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

Nanosensor-based detection of biomarkers can improve medical diagnosis; however, a critical factor in nanosensor development is deciding which biomarker to target, as most diseases present several biomarkers. Biomarker-targeting decisions can be informed via an understanding of biomarker expression. Currently, immunohistochemistry (IHC) is the accepted standard for profiling biomarker expression. While IHC provides a relative mapping of biomarker expression, it does not provide cell-by-cell readouts of biomarker expression or absolute biomarker quantification. Flow cytometry overcomes both these IHC challenges by offering biomarker expression on a cell-by-cell basis, and when combined with calibration standards, providing quantitation of biomarker concentrations: this is known as qFlow cytometry. Here, we outline the key components for applying qFlow cytometry to detect biomarkers within the angiogenic vascular endothelial growth factor receptor family. The key aspects of the qFlow cytometry methodology include: antibody specificity testing, immunofluorescent cell labeling, saturation analysis, fluorescent microsphere calibration, and quantitative analysis of both ensemble and cell-by-cell data. Together, these methods enable high-throughput quantification of biomarker expression.

Validation of Cross-Species Reactivity of the VEGF-A/PDGFRβ Bifunctional Antibody PF-06653157

PURPOSE

PF-06653157 is a bifunctional antagonist monoclonal antibody (mAb) that targets human VEGF-A ligand and PDGF-Rβ. With the advent of PF-06653157 as an angiogenesis inhibitor and potential treatment for angiogenesis deregulation diseases, a relevant toxicology species is needed for toxicity and efficacy studies. Investigative studies were conducted to validate the mAb dual antagonist properties in a human system and determine its cross-reactive pharmacology in nonhuman cells.

METHODS

Sequence alignment was used to determine percent sequence identity of VEGF and PDGF receptors and ligands; qualitative reverse transcription polymerase chain reaction (qRT-PCR) was used to determine the presence of PDGF-Rβ on cells of interest. The functional activity of PF-06653157 antibody was assessed in human, dog, porcine, rabbit, rat, mouse, and cynomolgus monkey cells treated with VEGF and PDGF ligands through cell proliferation assays and western blot analysis of AKT and p44/p42 (ERK1/2) protein phosphorylation and enzyme-linked immunosorbent assay.

RESULTS

PF-06653157 attenuated phosphorylation of AKT and p44/p42 proteins in human and cynomolgus monkey cells. The antibody did not attenuate AKT nor p44/p42 phosphorylation in any other species tested. PDGFR signaling could not be activated with human PDGF ligand in the porcine cells, so PF-06653157 activity in porcine remains inconclusive.

CONCLUSION

The PF-06653157 mAb cross-reacts with cynomolgus monkey cells in a similar manner to human cells. Therefore, cynomolgus monkeys are considered the appropriate species for efficacy and regulatory toxicology studies in PF-06653157 development.

Improving Bioengineering Student Leadership Identity Via Training and Practice within the Core-Course

The development of a leadership identity has become significant in bioengineering education as a result of an increasing emphasis on teamwork within the profession and corresponding shifts in accreditation criteria. Unsurprisingly, placing bioengineering students in teams to complete classroom-based projects has become a dominant pedagogical tool. However, recent research indicates that engineering students may not develop a leadership identity, much less increased leadership capacity, as a result of such efforts. Within this study, we assessed two similar sections of an introductory course in bioengineering; each placed students in teams, while one also included leadership training and leadership practice. Results suggest that students in the leadership intervention section developed a strong self-image of themselves as leaders compared to students in the control section. These data suggest that creating mechanisms for bioengineering students to be trained in leadership and to practice leadership behaviors within a classroom team may be keys for unlocking leadership development.

Quantum dot multiplexing for the profiling of cellular receptors

The profiling of cellular heterogeneity has wide-reaching importance for our understanding of how cells function and react to their environments in healthy and diseased states. Our ability to interpret and model cell behavior has been limited by the difficulties of measuring cell differences, for example, comparing tumor and non-tumor cells, particularly at the individual cell level. This demonstrates a clear need for a generalizable approach to profile fluorophore sites on cells or molecular assemblies on beads. Here, a multiplex immunoassay for simultaneous detection of five different angiogenic markers was developed. We targeted angiogenic receptors in the vascular endothelial growth factor family (VEGFR1, VEGFR2 and VEGFR3) and Neuropilin (NRP) family (NRP1 and NRP2), using multicolor quantum dots (Qdots). Copper-free click based chemistry was used to conjugate the monoclonal antibodies with 525, 565, 605, 655 and 705 nm CdSe/ZnS Qdots. We tested and performed colocalization analysis of our nanoprobes using the Pearson correlation coefficient statistical analysis. Human umbilical vein endothelial cells (HUVEC) were tested. The ability to easily monitor the molecular indicators of angiogenesis that are a precursor to cancer in a fast and cost effective system is an important step towards personalized nanomedicine.

Secondary anchor targeted cell release

Personalized medicine offers the promise of tailoring therapy to patients, based on their cellular biomarkers. To achieve this goal, cellular profiling systems are needed that can quickly and efficiently isolate specific cell types without disrupting cellular biomarkers. Here we describe the development of a unique platform that facilitates gentle cell capture via a secondary, surface-anchoring moiety, and cell release. The cellular capture system consists of a glass surface functionalized with APTES, d-desthiobiotin, and streptavidin. Biotinylated mCD11b and hIgG antibodies are used to capture mouse macrophages (RAW 264.7) and human breast cancer (MCF7-GFP) cell lines, respectively. The surface functionalization is optimized by altering assay components, such as streptavidin, d-desthiobiotin, and APTES, to achieve cell capture on 80% of the functionalized surface and cell release upon biotin treatment. We also demonstrate an ability to capture 50% of target cells within a dual-cell mixture. This engineering advancement is a critical step towards achieving cell isolation platforms for personalized medicine.