Predicting the effects of anti-angiogenic agents targeting specific VEGF isoforms

Quantitative systems pharmacology modeling of macrophage-targeted therapy combined with PD-L1 inhibition in advanced NSCLC

Immune checkpoint inhibitors remained the standard-of-care treatment for advanced non-small cell lung cancer (NSCLC) for the past decade. In unselected patients, anti-PD-(L)1 monotherapy achieved an overall response rate of about 20%. In this analysis, we developed a pharmacokinetic and pharmacodynamic module for our previously calibrated quantitative systems pharmacology model (QSP) to simulate the effectiveness of macrophage-targeted therapies in combination with PD-L1 inhibition in advanced NSCLC. By conducting in silico clinical trials, the model confirmed that anti-CD47 treatment is not an optimal option of second- and later-line treatment for advanced NSCLC resistant to PD-(L)1 blockade. Furthermore, the model predicted that inhibition of macrophage recruitment, such as using CCR2 inhibitors, can potentially improve tumor size reduction when combined with anti-PD-(L)1 therapy, especially in patients who are likely to respond to anti-PD-(L)1 monotherapy and those with a high level of tumor-associated macrophages. Here, we demonstrate the application of the QSP platform on predicting the effectiveness of novel drug combinations involving immune checkpoint inhibitors based on preclinical or early-stage clinical trial data.

Molecularly Imprinted Nanomedicine for Anti-angiogenic Cancer Therapy via Blocking Vascular Endothelial Growth Factor Signaling

The VEGF-VEGFR2 (VEGF = vascular endothelial growth factor) signaling has been a promising target in cancer therapy. However, because conventional anti-angiogenic therapeutics suffer from drawbacks, particularly severe side effects, novel anti-angiogenic strategies are much needed. Herein, we report the rational engineering of VEGF-targeted molecularly imprinted polymer nanoparticles (nanoMIP) for anti-angiogenic cancer therapy. The anti-VEGF nanomedicine was prepared via a state-of-the-art molecular imprinting approach using the N-terminal epitope of VEGF as the template. The nanoMIP could target the two major pro-angiogenic isoforms (VEGF165 and VEGF121) with high affinity and thereby effectively block the VEGF-VEGFR2 signaling, yielding a potent anti-angiogenic effect of "killing two birds with one stone". In vivo experiments demonstrated that the anti-VEGF nanoMIP effectively suppressed tumor growth via anti-angiogenesis in a xenograft model of human colon carcinoma without apparent side effects. Thus, this study not only proposes an unprecedented anti-angiogenic strategy for cancer therapy but also provides a new paradigm for the rational development of MIPs-based "drug-free" nanomedicines.

Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition

Generating realistic virtual patients from a limited amount of patient data is one of the major challenges for quantitative systems pharmacology modeling in immuno-oncology. Quantitative systems pharmacology (QSP) is a mathematical modeling methodology that integrates mechanistic knowledge of biological systems to investigate dynamics in a whole system during disease progression and drug treatment. In the present analysis, we parameterized our previously published QSP model of the cancer-immunity cycle to non-small cell lung cancer (NSCLC) and generated a virtual patient cohort to predict clinical response to PD-L1 inhibition in NSCLC. The virtual patient generation was guided by immunogenomic data from iAtlas portal and population pharmacokinetic data of durvalumab, a PD-L1 inhibitor. With virtual patients generated following the immunogenomic data distribution, our model predicted a response rate of 18.6% (95% bootstrap confidence interval: 13.3-24.2%) and identified CD8/Treg ratio as a potential predictive biomarker in addition to PD-L1 expression and tumor mutational burden. We demonstrated that omics data served as a reliable resource for virtual patient generation techniques in immuno-oncology using QSP models.

Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition

Generating realistic virtual patients from a limited amount of patient data is one of the major challenges for quantitative systems pharmacology modeling in immuno-oncology. Quantitative systems pharmacology (QSP) is a mathematical modeling methodology that integrates mechanistic knowledge of biological systems to investigate dynamics in a whole system during disease progression and drug treatment. In the present analysis, we parameterized our previously published QSP model of the cancer-immunity cycle to non-small cell lung cancer (NSCLC) and generated a virtual patient cohort to predict clinical response to PD-L1 inhibition in NSCLC. The virtual patient generation was guided by immunogenomic data from iAtlas portal and population pharmacokinetic data of durvalumab, a PD-L1 inhibitor. With virtual patients generated following the immunogenomic data distribution, our model predicted a response rate of 18.6% (95% bootstrap confidence interval: 13.3-24.2%) and identified CD8/Treg ratio as a potential predictive biomarker in addition to PD-L1 expression and tumor mutational burden. We demonstrated that omics data served as a reliable resource for virtual patient generation techniques in immuno-oncology using QSP models.

Mechanistic insights into the development of severe fetal growth restriction

Fetal growth restriction (FGR), which most commonly results from suboptimal placental function, substantially increases risks for adverse perinatal and long-term outcomes. The only "treatment" that exists is delivery, which averts stillbirth but does not improve outcomes in survivors. Furthermore, the potential long-term consequences of FGR to the fetus, including cardiometabolic disorders, predispose these individuals to developing FGR in their future pregnancies. This creates a multi-generational cascade of adverse effects stemming from a single dysfunctional placenta, and understanding the mechanisms underlying placental-mediated FGR is critically important if we are to improve outcomes and overall health. The mechanisms behind FGR remain unknown. However, placental insufficiency derived from maldevelopment of the placental vascular systems is the most common etiology. To highlight important mechanistic interactions within the placenta, we focus on placental vascular development in the setting of FGR. We delve into fetoplacental angiogenesis, a robust and ongoing process in normal pregnancies that is impaired in severe FGR. We review cellular models of FGR, with special attention to fetoplacental angiogenesis, and we highlight novel integrin-extracellular matrix interactions that regulate placental angiogenesis in severe FGR. In total, this review focuses on key developmental processes, with specific focus on the human placenta, an underexplored area of research.

Nanocarriers for the Delivery of Neuroprotective Agents in the Treatment of Ocular Neurodegenerative Diseases

Retinal neurodegeneration is considered an early event in the pathogenesis of several ocular diseases, such as diabetic retinopathy, age-related macular degeneration, and glaucoma. At present, there is no definitive treatment to prevent the progression or reversal of vision loss caused by photoreceptor degeneration and the death of retinal ganglion cells. Neuroprotective approaches are being developed to increase the life expectancy of neurons by maintaining their shape/function and thus prevent the loss of vision and blindness. A successful neuroprotective approach could prolong patients' vision functioning and quality of life. Conventional pharmaceutical technologies have been investigated for delivering ocular medications; however, the distinctive structural characteristics of the eye and the physiological ocular barriers restrict the efficient delivery of drugs. Recent developments in bio-adhesive in situ gelling systems and nanotechnology-based targeted/sustained drug delivery systems are receiving a lot of attention. This review summarizes the putative mechanism, pharmacokinetics, and mode of administration of neuroprotective drugs used to treat ocular disorders. Additionally, this review focuses on cutting-edge nanocarriers that demonstrated promising results in treating ocular neurodegenerative diseases.

Dynamics of tumor-associated macrophages in a quantitative systems pharmacology model of immunotherapy in triple-negative breast cancer

Quantitative systems pharmacology (QSP) modeling is an emerging mechanistic computational approach that couples drug pharmacokinetics/pharmacodynamics and the course of disease progression. It has begun to play important roles in drug development for complex diseases such as cancer, including triple-negative breast cancer (TNBC). The combination of the anti-PD-L1 antibody atezolizumab and nab-paclitaxel has shown clinical activity in advanced TNBC with PD-L1-positive tumor-infiltrating immune cells. As tumor-associated macrophages (TAMs) serve as major contributors to the immuno-suppressive tumor microenvironment, we incorporated the dynamics of TAMs into our previously published QSP model to investigate their impact on cancer treatment. We show that through proper calibration, the model captures the macrophage heterogeneity in the tumor microenvironment while maintaining its predictive power of the trial results at the population level. Despite its high mechanistic complexity, the modularized QSP platform can be readily reproduced, expanded for new species of interest, and applied in clinical trial simulation.

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A mechanistic model of quantitative systems pharmacology in immuno-oncology

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Dynamics of tumor-associated macrophages are integrated into our previous work

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Conducting in silico clinical trials to predict clinical response to cancer therapy

Cancer combination therapies by angiogenesis inhibitors; a comprehensive review

Abnormal vasculature is one of the most conspicuous traits of tumor tissue, largely contributing to tumor immune evasion. The deregulation mainly arises from the potentiated pro-angiogenic factors secretion and can also target immune cells' biological events, such as migration and activation. Owing to this fact, angiogenesis blockade therapy was established to fight cancer by eliminating the nutrient and oxygen supply to the malignant cells by impairing the vascular network. Given the dominant role of vascular-endothelium growth factor (VEGF) in the angiogenesis process, the well-known anti-angiogenic agents mainly depend on the targeting of its actions. However, cancer cells mainly show resistance to anti-angiogenic agents by several mechanisms, and also potentiated local invasiveness and also distant metastasis have been observed following their administration. Herein, we will focus on clinical developments of angiogenesis blockade therapy, more particular, in combination with other conventional treatments, such as immunotherapy, chemoradiotherapy, targeted therapy, and also cancer vaccines. Video abstract.

Isoforms of soluble vascular endothelial growth factor in stress-related mental disorders: a cross-sectional study

Vascular endothelial growth factor (VEGF) has been implicated in the pathophysiology of stress-related mental disorders. However, VEGF levels have seldom been compared across mental disorders and never by isoforms. Pathophysiological processes involving leakage of astrocyte-derived extracellular vesicles (EVs) across the blood–brain barrier could be associated with VEGF levels in patients with stress-related mental disorders. This cross-sectional study compared plasma levels of VEGF₁₂₁, VEGF₁₆₅, and VEGF₁₂₁ + VEGF₁₆₅ (VEGF_total) in patients with stress-induced exhaustion disorder (SED) (n = 31), patients with major depressive disorder (MDD) (n = 31), and healthy controls (n = 61). It also analyzed the correlation between VEGF and astrocyte-derived EVs in plasma. An enzyme-linked immunosorbent assay (ELISA) was used to measure VEGF₁₂₁ and VEGF₁₆₅ in citrate plasma, and flow cytometry was used to measure astrocyte-derived EVs in plasma. The mean concentration of soluble VEGF₁₂₁ (sVEGF₁₂₁) was significantly higher in patients with SED than healthy controls (P = 0.043). Mean sVEGF₁₆₅ was significantly lower in patients with MDD than patients with SED (P = 0.004) or healthy controls (P = 0.037). Mean sVEGF_total was significantly higher in patients with SED than in patients with MDD (P = 0.021) and also higher in patients with SED than healthy controls (P = 0.040). Levels of sVEGF₁₂₁ were positively correlated with levels of astrocyte-derived EVs only in patients with SED (P = 0.0128). The same was true of levels of sVEGF_total and astrocyte-derived EVs (P = 0.0046). Differing levels of VEGF isoforms may reflect different pathophysiological mechanisms in SED and MDD. Further research is needed to better understand the potential roles of VEGF isoforms and astrocyte-derived EVs in mental disorders.

VEGF and VEGFR2 bind to similar pH-sensitive sites on fibronectin, exposed by heparin-mediated conformational changes

Physical interactions between vascular endothelial growth factor (VEGF), a central player in blood endothelial cell biology, and fibronectin, a major fibrillar protein of the extracellular matrix, are important determinants of angiogenic activity in health and disease. Conditions signaling the need for new blood vessel growth, such as hypoxia and low extracellular pH, increase VEGF–fibronectin interactions. These interactions can be further fine-tuned through changes in the availability of the VEGF-binding sites on fibronectin, regulated by conformational changes induced by heparin and heparan sulfate chains within the extracellular matrix. These interactions may alter VEGF bioavailability, generate gradients, or alter the way VEGF is recognized by and activates its cell-surface receptors. Here, using equilibrium and kinetic studies, we discovered that fibronectin can also interact with the extracellular domain of the VEGF receptor 2 (VEGFR2). The VEGFR2-binding sites on fibronectin show great similarity to the VEGF-binding sites, as they were also exposed upon heparin-induced conformational changes in fibronectin, and the interaction was enhanced at acidic pH. Kinetic parameters and affinities for VEGF and VEGFR2 binding to fibronectin were determined by surface plasmon resonance measurements, revealing two populations of fibronectin-binding sites for each molecule. Our data also suggest that a VEGF/VEGFR2/fibronectin triple complex may be formed by VEGF or VEGFR2 first binding to fibronectin and subsequently recruiting the third binding partner. The formation of such a complex may lead to the activation of distinct angiogenic signaling pathways, offering new possibilities for clinical applications that target angiogenesis.

Melatonin ameliorates microvessel abnormalities in the cerebral cortex and hippocampus in a rat model of Alzheimer's disease

Melatonin can attenuate cardiac microvascular ischemia/reperfusion injury, but it remains unclear whether melatonin can also ameliorate cerebral microvascular abnormalities. Rat models of Alzheimer’s disease were established by six intracerebroventricular injections of amyloid-beta 1–42, administered once every other day. Melatonin (30 mg/kg) was intraperitoneally administered for 13 successive days, with the first dose given 24 hours prior to the first administration of amyloid-beta 1–42. Melatonin ameliorated learning and memory impairments in the Morris water maze test, improved the morphology of microvessels in the cerebral cortex and hippocampus, increased microvessel density, alleviated pathological injuries of cerebral neurons, and decreased the expression of vascular endothelial growth factor and vascular endothelial growth factor receptors 1 and 2. These findings suggest that melatonin can improve microvessel abnormalities in the cerebral cortex and hippocampus by lowering the expression of vascular endothelial growth factor and its receptors, thereby improving the cognitive function of patients with Alzheimer’s disease. This study was approved by the Animal Care and Use Committee of Jinzhou Medical University, China (approval No. 2019015) on December 6, 2018.

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.

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.

Splicing regulatory factors in breast cancer hallmarks and disease progression

By regulating transcript isoform expression levels, alternative splicing provides an additional layer of protein control. Recent studies show evidence that cancer cells use different splicing events to fulfill their requirements in order to develop, progress and metastasize. However, there has been less attention for the role of the complex catalyzing the complicated multistep splicing reaction: the spliceosome. The spliceosome consists of multiple sub-complexes in total comprising 244 proteins or splice factors and 5 associated RNA molecules. Here we discuss the role of splice factors in the oncogenic processes tumors cells need to fulfill their oncogenic properties (the so-called the hallmarks of cancer). Despite the fact that splice factors have been investigated only recently, they seem to play a prominent role in already five hallmarks of cancer: angiogenesis, resisting cell death, sustaining proliferation, deregulating cellular energetics and invasion and metastasis formation by affecting major signaling pathways such as epithelial-to-mesenchymal transition, the Warburg effect, DNA damage response and hormone receptor dependent proliferation. Moreover, we could relate expression of representative genes of four other hallmarks (enabling replicative mortality, genomic instability, avoiding immune destruction and evading growth suppression) to splice factor levels in human breast cancer tumors, suggesting that also these hallmarks could be regulated by splice factors. Since many splice factors are involved in multiple hallmarks of cancer, inhibiting splice factors might provide a new layer of oncogenic control and a powerful method to combat breast cancer progression.

Network-based method for drug target discovery at the isoform level

Identification of primary targets associated with phenotypes can facilitate exploration of the underlying molecular mechanisms of compounds and optimization of the structures of promising drugs. However, the literature reports limited effort to identify the target major isoform of a single known target gene. The majority of genes generate multiple transcripts that are translated into proteins that may carry out distinct and even opposing biological functions through alternative splicing. In addition, isoform expression is dynamic and varies depending on the developmental stage and cell type. To identify target major isoforms, we integrated a breast cancer type-specific isoform coexpression network with gene perturbation signatures in the MCF7 cell line in the Connectivity Map database using the ‘shortest path’ drug target prioritization method. We used a leukemia cancer network and differential expression data for drugs in the HL-60 cell line to test the robustness of the detection algorithm for target major isoforms. We further analyzed the properties of target major isoforms for each multi-isoform gene using pharmacogenomic datasets, proteomic data and the principal isoforms defined by the APPRIS and STRING datasets. Then, we tested our predictions for the most promising target major protein isoforms of DNMT1, MGEA5 and P4HB4 based on expression data and topological features in the coexpression network. Interestingly, these isoforms are not annotated as principal isoforms in APPRIS. Lastly, we tested the affinity of the target major isoform of MGEA5 for streptozocin through in silico docking. Our findings will pave the way for more effective and targeted therapies via studies of drug targets at the isoform level.

VEGF-121 plasma level as biomarker for response to anti-angiogenetic therapy in recurrent glioblastoma

Background

Vascular endothelial growth factor (VEGF) isoforms, particularly the diffusible VEGF-121, could play a major role in the response of recurrent glioblastoma (GB) to anti-angiogenetic treatment with bevacizumab. We hypothesized that circulating VEGF-121 may reduce the amount of bevacizumab available to target the heavier isoforms of VEGF, which are the most clinically relevant.

Methods

We assessed the plasma level of VEGF-121 in a brain xenograft model, in human healthy controls, and in patients suffering from recurrent GB before and after bevacizumab treatment. Data were matched with patients’ clinical outcome.

Results

In athymic rats with U87MG brain xenografts, the level of plasma VEGF-121 relates with tumor volume and it significantly decreases after iv infusion of bevacizumab. Patients with recurrent GB show higher plasma VEGF-121 than healthy controls (p = 0.0002) and treatment with bevacizumab remarkably reduced the expression of VEGF-121 in plasma of these patients (p = 0.0002). Higher plasma level of VEGF-121 was significantly associated to worse PFS and OS (p = 0.0295 and p = 0.0246, respectively).

Conclusions

Quantitative analysis of VEGF-121 isoform in the plasma of patients with recurrent GB could be a promising predictor of response to anti-angiogenetic treatment.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4442-2) contains supplementary material, which is available to authorized users.

Mechanistic modeling quantifies the influence of tumor growth kinetics on the response to anti-angiogenic treatment

Tumors exploit angiogenesis, the formation of new blood vessels from pre-existing vasculature, in order to obtain nutrients required for continued growth and proliferation. Targeting factors that regulate angiogenesis, including the potent promoter vascular endothelial growth factor (VEGF), is therefore an attractive strategy for inhibiting tumor growth. Computational modeling can be used to identify tumor-specific properties that influence the response to anti-angiogenic strategies. Here, we build on our previous systems biology model of VEGF transport and kinetics in tumor-bearing mice to include a tumor compartment whose volume depends on the “angiogenic signal” produced when VEGF binds to its receptors on tumor endothelial cells. We trained and validated the model using published in vivo measurements of xenograft tumor volume, producing a model that accurately predicts the tumor’s response to anti-angiogenic treatment. We applied the model to investigate how tumor growth kinetics influence the response to anti-angiogenic treatment targeting VEGF. Based on multivariate regression analysis, we found that certain intrinsic kinetic parameters that characterize the growth of tumors could successfully predict response to anti-VEGF treatment, the reduction in tumor volume. Lastly, we use the trained model to predict the response to anti-VEGF therapy for tumors expressing different levels of VEGF receptors. The model predicts that certain tumors are more sensitive to treatment than others, and the response to treatment shows a nonlinear dependence on the VEGF receptor expression. Overall, this model is a useful tool for predicting how tumors will respond to anti-VEGF treatment, and it complements pre-clinical in vivo mouse studies.

One hallmark of cancer is angiogenesis, the formation of new blood capillaries from pre-existing vessels. Angiogenesis promotes tumor growth by enabling the tumor to obtain oxygen and nutrients from the surrounding microenvironment. Cancer drugs that inhibit angiogenesis ("anti-angiogenic therapies") have focused on inhibiting proteins that promote the growth of new blood vessels. The response to anti-angiogenic therapy is highly variable, and some tumors do not respond at all. Therefore, identifying a biomarker that predicts how specific tumors will respond would be extremely valuable. This work uses a computational model of tumor-bearing mice to investigate the response to anti-angiogenic treatment that targets the potent promoter of angiogenesis, vascular endothelial growth factor (VEGF), and how the response is influenced by tumor growth kinetics. We show that certain properties of tumor growth can be used to predict how much the tumor volume will be reduced upon administration of an anti-VEGF drug. This work identifies tumor growth parameters that may be reliable biomarkers for predicting how tumors will respond to anti-VEGF therapy. Our computational model generates novel, testable hypotheses and nicely complements pre-clinical studies of anti-angiogenic therapeutics.

VEGFR1 promotes cell migration and proliferation through PLCγ and PI3K pathways

The ability to control vascular endothelial growth factor (VEGF) signaling offers promising therapeutic potential for vascular diseases and cancer. Despite this promise, VEGF-targeted therapies are not clinically effective for many pathologies, such as breast cancer. VEGFR1 has recently emerged as a predictive biomarker for anti-VEGF efficacy, implying a functional VEGFR1 role beyond its classically defined decoy receptor status. Here we introduce a computational approach that accurately predicts cellular responses elicited via VEGFR1 signaling. Aligned with our model prediction, we show empirically that VEGFR1 promotes macrophage migration through PLCγ and PI3K pathways and promotes macrophage proliferation through a PLCγ pathway. These results provide new insight into the basic function of VEGFR1 signaling while offering a computational platform to quantify signaling of any receptor.

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.

Angiogenesis inhibitors in early development for gastric cancer

INTRODUCTION

Angiogenesis, or the generation of new blood vessels from pre-existent ones is a critical process for tumor growth and progression. Hence, the development of angiogenesis inhibitors with therapeutic potential has been a central focus for researchers. Most angiogenesis inhibitors target the Vascular Endothelial Growth Factor (VEGF) pathway, however a number of tyrosine kinase inhibitors (TKIs), immunomodulatory drugs (IMiDs) and inhibitors of the mammalian Target-Of-Rapamycin (mTOR) pathway also display antiangiogenic activity. Areas covered: Here we review the effectiveness of a variety of compounds with antiangiogenic properties in preclinical and clinical settings in gastric cancer (GC). Expert opinion: In coming years angiogenesis will remain as a therapeutic target in GC. To date, ramucirumab a monoclonal antibody that targets VEGFR2 is the most successful antiangiogenic tested in clinical studies, and it is now well established as a second-line therapy in GC. The arrival of precision medicine and the success of immune checkpoint inhibitors will increase the number of clinical trials using targeted agents like ramucirumab in combination with immune checkpoint inhibitors. A hypothetical working model that combines ramucirumab with immunotherapy is presented. Also, the impact of nanotechnology and a molecular subtype classification of GC are discussed.

Monitoring Severity of Multiple Organ Dysfunction Syndrome: New Technologies

OBJECTIVE

To describe new technologies (biomarkers and tests) used to assess and monitor the severity and progression of multiple organ dysfunction syndrome in children as discussed as part of the Eunice Kennedy Shriver National Institute of Child Health and Human Development MODS Workshop (March 26-27, 2015).

DATA SOURCES

Literature review, research data, and expert opinion.

STUDY SELECTION

Not applicable.

DATA EXTRACTION

Moderated by an experienced expert from the field, investigators developing and assessing new technologies to improve the care and understanding of critical illness presented their research and the relevant literature.

DATA SYNTHESIS

Summary of presentations and discussion supported and supplemented by relevant literature.

CONCLUSIONS

There are many innovative tools and techniques with the potential application for the assessment and monitoring of severity of multiple organ dysfunction syndrome. If the reliability and added value of these candidate technologies can be established, they hold promise to enhance the understanding, monitoring, and perhaps, treatment of multiple organ dysfunction syndrome in children.

A multiscale computational model predicts distribution of anti-angiogenic isoform VEGF165b in peripheral arterial disease in human and mouse

Angiogenesis is the growth of new blood vessels from pre-existing microvessels. Peripheral arterial disease (PAD) is caused by atherosclerosis that results in ischemia mostly in the lower extremities. Clinical trials including VEGF-A administration for therapeutic angiogenesis have not been successful. The existence of anti-angiogenic isoform (VEGF_165b) in PAD muscle tissues is a potential cause for the failure of therapeutic angiogenesis. Experimental measurements show that in PAD human muscle biopsies the VEGF_165b isoform is at least as abundant if not greater than the VEGF_165a isoform. We constructed three-compartment models describing VEGF isoforms and receptors, in human and mouse, to make predictions on the secretion rate of VEGF_165b and the distribution of various isoforms throughout the body based on the experimental data. The computational results are consistent with the data showing that in PAD calf muscles secrete mostly VEGF_165b over total VEGF. In the PAD calf compartment of human and mouse models, most VEGF_165a and VEGF_165b are bound to the extracellular matrix. VEGF receptors VEGFR1, VEGFR2 and Neuropilin-1 (NRP1) are mostly in ‘Free State’. This study provides a computational model of VEGF_165b in PAD supported by experimental measurements of VEGF_165b in human and mouse, which gives insight of VEGF_165b in therapeutic angiogenesis and VEGF distribution in human and mouse PAD model.

Effects of endothelial cell proliferation and migration rates in a computational model of sprouting angiogenesis

Angiogenesis, the recruitment of new blood vessels, is a critical process for the growth, expansion, and metastatic dissemination of developing tumors. Three types of cells make up the new vasculature: tip cells, which migrate in response to gradients of vascular endothelial growth factor (VEGF), stalk cells, which proliferate and extend the vessels, and phalanx cells, which are quiescent and support the sprout. In this study we examine the contribution of tip cell migration rate and stalk cell proliferation rate on the formation of new vasculature. We calculate several vascular metrics, such as the number of vascular bifurcations per unit volume, vascular segment length per unit volume, and vascular tortuosity. These measurements predict that proliferation rate has a greater effect on the spread and extent of vascular growth compared to migration rate. Together, these findings provide strong implications for designing anti-angiogenic therapies that may differentially target endothelial cell proliferation and migration. Computational models can be used to predict optimal anti-angiogenic therapies in combination with other therapeutics to improve outcome.

Escaping Antiangiogenic Therapy: Strategies Employed by Cancer Cells

Tumor angiogenesis is widely recognized as one of the "hallmarks of cancer". Consequently, during the last decades the development and testing of commercial angiogenic inhibitors has been a central focus for both basic and clinical cancer research. While antiangiogenic drugs are now incorporated into standard clinical practice, as with all cancer therapies, tumors can eventually become resistant by employing a variety of strategies to receive nutrients and oxygen in the event of therapeutic assault. Herein, we concentrate and review in detail three of the principal mechanisms of antiangiogenic therapy escape: (1) upregulation of compensatory/alternative pathways for angiogenesis; (2) vasculogenic mimicry; and (3) vessel co-option. We suggest that an understanding of how a cancer cell adapts to antiangiogenic therapy may also parallel the mechanisms employed in the bourgeoning tumor and isolated metastatic cells delivering responsible for residual disease. Finally, we speculate on strategies to adapt antiangiogenic therapy for future clinical uses.

Escape from tumor dormancy and time to angiogenic switch as mitigated by tumor-induced stimulation of stroma

A variety of mechanisms have been proposed to explain "cancer without disease", the state of tumor dormancy, characterized by balance in cell proliferation and cell death within a tumor. Here we have investigated a theoretical construct, whereby one of such mechanisms, the time to induction of angiogenesis, or "angiogenic switch", is mitigated by the degree of stromal stimulation by the tumor. We tested this hypothesis and its implications by introducing a mathematical model that captures how angiogenesis regulators, released from the platelet clot, contribute to formation of normal vasculature. We then modified the model to introduce tumor-induced increase in production of angiogenesis regulators and were able to simulate pathological angiogenesis. Through varying parameters governing the degree of tumor-induced stromal stimulation, we were able to qualitatively replicate experimentally observed growth curves for both dormant and actively growing tumors of breast cancer and liposarcoma. In fact, variation of very few parameters was sufficient to replicate any experimentally observed time to angiogenic switch in the available data. Finally, we investigated the effects of tighter binding isoforms of angiogenesis stimulators on neovasculature formation and tumor growth, which may provide an explanation for variations in angiogenesis -dependence in tumors of different tissue origin.

Pharmacokinetics of Anti-VEGF Agent Aflibercept in Cancer Predicted by Data-Driven, Molecular-Detailed Model

Mathematical models can support the drug development process by predicting the pharmacokinetic (PK) properties of the drug and optimal dosing regimens. We have developed a pharmacokinetic model that includes a biochemical molecular interaction network linked to a whole-body compartment model. We applied the model to study the PK of the anti-vascular endothelial growth factor (VEGF) cancer therapeutic agent, aflibercept. Clinical data is used to infer model parameters using a Bayesian approach, enabling a quantitative estimation of the contributions of specific transport processes and molecular interactions of the drug that cannot be examined in other PK modeling, and insight into the mechanisms of aflibercept's antiangiogenic action. Additionally, we predict the plasma and tissue concentrations of unbound and VEGF-bound aflibercept. Thus, we present a computational framework that can serve as a valuable tool for drug development efforts.

Overexpression of miRNA-497 inhibits tumor angiogenesis by targeting VEGFR2

Recent studies reported miR-497 exhibited inhibitory effects in various cancers. However, whether miR-497 is involved in inhibiting angiogenesis, which is critical for tumor growth and metastasis, is still unknown. The purpose of this study was to investigate the potential role of miR-497 in tumor angiogenesis. In this work, cell proliferation and apoptosis analyses were conducted to explore the potential function of miR-497 in HUVECs by using MTT and TUNEL assays. Western blotting (WB) was employed to validate the downstream targets of miR-497. Furthermore, in order to disclose the role of miR-497 on angiogenesis, VEGFR2-luc transgenic mice were treated with miR-497 mimic and applied to monitor tumor angiogenesis and growth by in vivo bioluminescent imaging (BLI). The results demonstrated that overexpression of miR-497 showed inhibitory effects on VEGFR2 activation and downstream Raf/MEK/ERK signal pathways in vitro and in vivo. Moreover, overexpression of miR-497 effectively induced HUVECs apoptosis by targeting VEGFR2 and downstream PI3K/AKT signaling pathway. Furthermore, miR-497 exhibited anti-angiogenesis and anti-tumor effects in the VEGFR2-luc breast tumor model proven by BLI, WB and immunohistochemistry analysis. In summary, miR-497 inhibits tumor angiogenesis and growth via targeting VEGFR2, indicating miR-497 can be explored as a potential drug candidate for cancer therapy.

High-resolution profiling of histone h3 lysine 36 trimethylation in metastatic renal cell carcinoma

Mutations in SETD2, a histone H3 lysine trimethyltransferase, have been identified in clear cell renal cell carcinoma (ccRCC); however it is unclear if loss of SETD2 function alters the genomic distribution of histone 3 lysine 36 trimethylation (H3K36me3) in ccRCC. Furthermore, published epigenomic profiles are not specific to H3K36me3 or metastatic tumors. To determine if progressive SETD2 and H3K36me3 dysregulation occurs in metastatic tumors, H3K36me3, SETD2 copy number (CN) or SETD2 mRNA abundance was assessed in two independent cohorts: metastatic ccRCC (n=71) and the Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma data set (n=413). Although SETD2 CN loss occurs with high frequency (>90%), H3K36me3 is not significantly impacted by monoallelic loss of SETD2. H3K36me3-positive nuclei were reduced an average of ~20% in primary ccRCC (90% positive nuclei in uninvolved vs 70% positive nuclei in ccRCC) and reduced by ~60% in metastases (90% positive in uninvolved kidney vs 30% positive in metastases) (P<0.001). To define a kidney-specific H3K36me3 profile, we generated genome-wide H3K36me3 profiles from four cytoreductive nephrectomies and SETD2 isogenic renal cell carcinoma (RCC) cell lines using chromatin immunoprecipitation coupled with high-throughput DNA sequencing and RNA sequencing. SETD2 loss of methyltransferase activity leads to regional alterations of H3K36me3 associated with aberrant RNA splicing in a SETD2 mutant RCC and SETD2 knockout cell line. These data suggest that during progression of ccRCC, a decline in H3K36me3 is observed in distant metastases, and regional H3K36me3 alterations influence alternative splicing in ccRCC.

Systems pharmacology approaches for optimization of antiangiogenic therapies: challenges and opportunities

Targeted therapies have become an important therapeutic paradigm for multiple malignancies. The rapid development of resistance to these therapies impedes the successful management of advanced cancer. Due to the redundancy in angiogenic signaling, alternative proangiogenic factors are activated upon treatment with anti-VEGF agents. Higher doses of the agents lead to greater stimulation of compensatory proangiogenic pathways that limit the therapeutic efficacy of VEGF-targeted drugs and produce escape mechanisms for tumor. Evidence suggests that dose intensity and schedules affect the dynamics of the development of this resistance. Thus, an optimal dosing regimen is crucial to maximizing the therapeutic benefit of antiangiogenic agents and limiting treatment resistance. A systems pharmacology approach using multiscale computational modeling can facilitate a mechanistic understanding of these dynamics of angiogenic biomarkers and their impacts on tumor reduction and resistance. Herein, we discuss a systems pharmacology approach integrating the biology of VEGF-targeted therapy resistance, including circulating biomarkers, and pharmacodynamics to enable the optimization of antiangiogenic therapy for therapeutic gains.

Computational systems biology approaches to anti-angiogenic cancer therapeutics

Angiogenesis is an exquisitely regulated process that is required for physiological processes and is also important in numerous diseases. Tumors utilize angiogenesis to generate the vascular network needed to supply the cancer cells with nutrients and oxygen, and many cancer drugs aim to inhibit tumor angiogenesis. Anti-angiogenic therapy involves inhibiting multiple cell types, molecular targets, and intracellular signaling pathways. Computational tools are useful in guiding treatment strategies, predicting the response to treatment, and identifying new targets of interest. Here, we describe progress that has been made in applying mathematical modeling and bioinformatics approaches to study anti-angiogenic therapeutics in cancer.

Vascular endothelial growth factor: therapeutic possibilities and challenges for the treatment of ischemia

Vascular endothelial growth factor (VEGF) is a notable chemokine that plays critical roles in angiogenesis and vasculogenesis. The contemporary body of literature contains a substantial amount of information regarding its chemical properties as well as its fundamental role in vascular development. Studies strongly indicate its potential use as a therapeutic agent, especially in the vascular restoration of injured and ischemic tissues. VEGF therapy could be most beneficial for diseases whose pathologies revolve around tissue inflammation and necrosis, such as myocardial infarction and stroke, as well as ischemic bowel diseases such as acute mesenteric ischemia and necrotizing enterocolitis. However, a delicate balance exists between the therapeutic benefits of VEGF and the hazards of tumor growth and neo-angiogenesis. Effective future research surrounding VEGF may allow for the development of effective therapies for ischemia which simultaneously limit its more deleterious side effects. This review will: (1) summarize the current understanding of the molecular aspects and function of VEGF, (2) review potential benefits of its use in medical therapy, (3) denote its role in tumorigenesis and inflammation when overexpressed, and (4) elucidate the qualities which make it a viable compound of study for diagnostic and therapeutic applications.

Antiangiogenic cancer drug sunitinib exhibits unexpected proangiogenic effects on endothelial cells

Angiogenesis, the formation of new blood vessels, is an essential step for cancer progression, but antiangiogenic therapies have shown limited success. Therefore, a better understanding of the effects of antiangiogenic treatments on endothelial cells is necessary. In this study, we evaluate the changes in cell surface vascular endothelial growth factor receptor (VEGFR) expression on endothelial cells in culture treated with the antiangiogenic tyrosine kinase inhibitor drug sunitinib, using quantitative flow cytometry. We find that proangiogenic VEGFR2 cell surface receptor numbers are increased with sunitinib treatment. This proangiogenic effect might account for the limited effects of sunitinib as a cancer therapy. We also find that this increase is inhibited by brefeldin A, an inhibitor of protein transport from the endoplasmic reticulum to the Golgi apparatus. The complex dynamics of cell surface VEGFRs may be important for successful treatment of cancer with antiangiogenic therapeutics.

Quantitative characterization of cellular membrane-receptor heterogeneity through statistical and computational modeling

Cell population heterogeneity can affect cellular response and is a major factor in drug resistance. However, there are few techniques available to represent and explore how heterogeneity is linked to population response. Recent high-throughput genomic, proteomic, and cellomic approaches offer opportunities for profiling heterogeneity on several scales. We have recently examined heterogeneity in vascular endothelial growth factor receptor (VEGFR) membrane localization in endothelial cells. We and others processed the heterogeneous data through ensemble averaging and integrated the data into computational models of anti-angiogenic drug effects in breast cancer. Here we show that additional modeling insight can be gained when cellular heterogeneity is considered. We present comprehensive statistical and computational methods for analyzing cellomic data sets and integrating them into deterministic models. We present a novel method for optimizing the fit of statistical distributions to heterogeneous data sets to preserve important data and exclude outliers. We compare methods of representing heterogeneous data and show methodology can affect model predictions up to 3.9-fold. We find that VEGF levels, a target for tuning angiogenesis, are more sensitive to VEGFR1 cell surface levels than VEGFR2; updating VEGFR1 levels in the tumor model gave a 64% change in free VEGF levels in the blood compartment, whereas updating VEGFR2 levels gave a 17% change. Furthermore, we find that subpopulations of tumor cells and tumor endothelial cells (tEC) expressing high levels of VEGFR (>35,000 VEGFR/cell) negate anti-VEGF treatments. We show that lowering the VEGFR membrane insertion rate for these subpopulations recovers the anti-angiogenic effect of anti-VEGF treatment, revealing new treatment targets for specific tumor cell subpopulations. This novel method of characterizing heterogeneous distributions shows for the first time how different representations of the same data set lead to different predictions of drug efficacy.

Network dynamics in the tumor microenvironment

The evolutionary path from tumor initiation to metastasis can only be fully understood by considering cancer cells as part of a multi-species ecosystem within the tumor microenvironment. This paper reviews and suggests two important recent trends. Firstly, I review arguments that interactions among diverse cells in the tumor microenvironment create a distinct cellular environment that can confer growth advantages, resist interventions, and allow tumors to remain dormant for long periods. Second, I review and highlight a trend toward data-rich, molecularly detailed, computational models of the tumor microenvironment. I argue that data-driven molecularly detailed tumor microenvironment models can now be built using data from multiple emerging high-throughput technologies, and that such models can pinpoint mechanisms of dysregulation and suggest specific drug targets and follow up experiments.

A systems biology view of blood vessel growth and remodelling

Blood travels throughout the body in an extensive network of vessels – arteries, veins and capillaries. This vascular network is not static, but instead dynamically remodels in response to stimuli from cells in the nearby tissue. In particular, the smallest vessels – arterioles, venules and capillaries – can be extended, expanded or pruned, in response to exercise, ischaemic events, pharmacological interventions, or other physiological and pathophysiological events. In this review, we describe the multi-step morphogenic process of angiogenesis – the sprouting of new blood vessels – and the stability of vascular networks in vivo. In particular, we review the known interactions between endothelial cells and the various blood cells and plasma components they convey. We describe progress that has been made in applying computational modelling, quantitative biology and high-throughput experimentation to the angiogenesis process.

Oncogenic alternative splicing switches: role in cancer progression and prospects for therapy

Alterations in the abundance or activities of alternative splicing regulators generate alternatively spliced variants that contribute to multiple aspects of tumor establishment, progression and resistance to therapeutic treatments. Notably, many cancer-associated genes are regulated through alternative splicing suggesting a significant role of this post-transcriptional regulatory mechanism in the production of oncogenes and tumor suppressors. Thus, the study of alternative splicing in cancer might provide a better understanding of the malignant transformation and identify novel pathways that are uniquely relevant to tumorigenesis. Understanding the molecular underpinnings of cancer-associated alternative splicing isoforms will not only help to explain many fundamental hallmarks of cancer, but will also offer unprecedented opportunities to improve the efficacy of anti-cancer treatments.

Compartment model predicts VEGF secretion and investigates the effects of VEGF trap in tumor-bearing mice

Angiogenesis, the formation of new blood vessels from existing vasculature, is important in tumor growth and metastasis. A key regulator of angiogenesis is vascular endothelial growth factor (VEGF), which has been targeted in numerous anti-angiogenic therapies aimed at inhibiting tumor angiogenesis. Systems biology approaches, including computational modeling, are useful for understanding this complex biological process and can aid in the development of novel and effective therapeutics that target the VEGF family of proteins and receptors. We have developed a computational model of VEGF transport and kinetics in the tumor-bearing mouse, which includes three-compartments: normal tissue, blood, and tumor. The model simulates human tumor xenografts and includes human (VEGF121 and VEGF165) and mouse (VEGF120 and VEGF164) isoforms. The model incorporates molecular interactions between these VEGF isoforms and receptors (VEGFR1 and VEGFR2), as well as co-receptors (NRP1 and NRP2). We also include important soluble factors: soluble VEGFR1 (sFlt-1) and α-2-macroglobulin. The model accounts for transport via macromolecular transendothelial permeability, lymphatic flow, and plasma clearance. We have fit the model to available in vivo experimental data on the plasma concentration of free VEGF Trap and VEGF Trap bound to mouse and human VEGF in order to estimate the rates at which parenchymal cells (myocytes and tumor cells) and endothelial cells secrete VEGF. Interestingly, the predicted tumor VEGF secretion rates are significantly lower (0.007-0.023 molecules/cell/s, depending on the tumor microenvironment) than most reported in vitro measurements (0.03-2.65 molecules/cell/s). The optimized model is used to investigate the interstitial and plasma VEGF concentrations and the effect of the VEGF-neutralizing agent, VEGF Trap (aflibercept). This work complements experimental studies performed in mice and provides a framework with which to examine the effects of anti-VEGF agents, aiding in the optimization of such anti-angiogenic therapeutics as well as analysis of clinical data. The model predictions also have implications for biomarker discovery with anti-angiogenic therapies.

Genetic and pharmacologic inhibition of complement impairs endothelial cell function and ablates ovarian cancer neovascularization

Complement activation plays a critical role in controlling inflammatory responses. To assess the role of complement during ovarian cancer progression, we crossed two strains of mice with genetic complement deficiencies with transgenic mice that develop epithelial ovarian cancer (TgMISIIR-TAg). TgMISIIR-TAg mice fully or partially deficient for complement factor 3 (C3) (Tg(+)C3(KO) and Tg(+)C3(HET), respectively) or fully deficient for complement factor C5a receptor (C5aR) (Tg(+)C5aR(KO)) develop either no ovarian tumors or tumors that were small and poorly vascularized compared to wild-type littermates (Tg(+)C3(WT), Tg(+)C5aR(WT)). The percentage of tumor infiltrating immune cells in Tg(+)C3(HET) tumors compared to Tg(+)C3(WT) controls was either similar (macrophages, B cells, myeloid-derived suppressor cells), elevated (effector T cells), or decreased (regulatory T cells). Regardless of these ratios, cytokine production by immune cells taken from Tg(+)C3(HET) tumors was reduced on stimulation compared to Tg(+)C3(WT) controls. Interestingly, CD31(+) endothelial cell (EC) function in angiogenesis was significantly impaired in both C3(KO) and C5aR(KO) mice. Further, using the C5aR antagonist PMX53, tube formation of ECs was shown to be C5a-dependent, possibly through interactions with the VEGF(165) but not VEGF(121) isoform. Finally, the mouse VEGF(164) transcript was underexpressed in C3(KO) livers compare to C3(WT) livers. Thus, we conclude that complement inhibition blocks tumor outgrowth by altering EC function and VEGF(165) expression.

Effect of tumor microenvironment on tumor VEGF during anti-VEGF treatment: systems biology predictions

BACKGROUND

Vascular endothelial growth factor (VEGF) is known to be a potent promoter of angiogenesis under both physiological and pathological conditions. Given its role in regulating tumor vascularization, VEGF has been targeted in various cancer treatments, and anti-VEGF therapy has been used clinically for treatment of several types of cancer. Systems biology approaches, particularly computational models, provide insight into the complexity of tumor angiogenesis. These models complement experimental studies and aid in the development of effective therapies targeting angiogenesis.

METHODS

We developed an experiment-based, molecular-detailed compartment model of VEGF kinetics and transport to investigate the distribution of two major VEGF isoforms (VEGF121 and VEGF165) in the body. The model is applied to predict the dynamics of tumor VEGF and, importantly, to gain insight into how tumor VEGF responds to an intravenous injection of an anti-VEGF agent.

RESULTS

The model predicts that free VEGF in the tumor interstitium is seven to 13 times higher than plasma VEGF and is predominantly in the form of VEGF121 (>70%), predictions that are validated by experimental data. The model also predicts that tumor VEGF can increase or decrease with anti-VEGF treatment depending on tumor microenvironment, pointing to the importance of personalized medicine.

CONCLUSIONS

This computational study suggests that the rate of VEGF secretion by tumor cells may serve as a biomarker to predict the patient population that is likely to respond to anti-VEGF treatment. Thus, the model predictions have important clinical relevance and may aid clinicians and clinical researchers seeking interpretation of pharmacokinetic and pharmacodynamic observations and optimization of anti-VEGF therapies.

New models of pulmonary hypertension based on VEGF receptor blockade-induced endothelial cell apoptosis

In spite of treatment, severe angioproliferative pulmonary arterial hypertension (PAH) remains a disease characterized by great morbidity and shortened survival. New treatment strategies for patients with PAH are needed, and after drug development, preclinical studies are best conducted in animal models which present with pulmonary angio-obliterative disease and right heart failure. A rat model of severe pulmonary hypertension and right heart failure, described a decade ago, continues to be investigated and provide insight into the nature of the lung vascular lesions and mechanisms of cardiac adaptation to an altered lung circulation. This rat model is based on the combination of VEGF receptor blockade with Su5416 and chronic hypoxia; use of this pulmonary hypertension induction strategy led to developing the concept of apoptosis-dependent compensatory vascular cell growth. Although, often employed in experimental designs, chronic hypoxia is not necessary for the development of angio-obliterative pulmonary hypertension. Left pneumonectomy combined with Su5416 also results in severe pulmonary hypertension in normoxic conditions. Similarly, the immune insufficiency component of severe PAH can be modeled in athymic rats (lacking T-lymphocytes). In these rats housed under normoxic conditions, treatment with the VEGFR receptor blocker results in angioproliferative pulmonary hypertension; cardiopulmonary disease in these animals can be prevented by immune reconstitution of regulatory T-cells (Tregs). Finally, chronic hypoxia can be replaced with another stimulator of HIF-1α: Ovalbumin (Ova). Immunization of rats with Ova increases lung tissue HIF-1α protein expression, and in Su5416-treated rats causes lethal pulmonary hypertension. Finally, we postulate that these models may also be useful for "reverse translation"; that is, the mechanisms of lung vascular cell death and growth and the modifying influences of immune and bone marrow cells that have been identified in the Su5416 VEGFR inhibitor models can be informative about heretofore undescribed processes in human PAH.

Synthesis of 5-(ethylsulfonyl)-2-methoxyaniline: An important pharmacological fragment of VEGFR2 and other inhibitors

Background: 5-(Ethylsulfonyl)-2-methoxyaniline (5) is part of the structure in 131 compounds possessing different biological activities. In most cases, they have antitumor properties (112 compounds). Other compounds are described as cardiovascular agents, ion-channel blockers, nervous-system blockers, anti-inflammatory agents, or antidiabetic, antiosteoporotic and hypolipemic species. Compound 5 is a precursor of different protein-kinase inhibitors or enzyme modulators (EGFR, PDGFR, ckit, CDK 2 and 4, MMPs 2, 3, 9 and 13, etc.). The structure of 5 represents a fragment for several powerful inhibitors of VEGFR2, a key angiogenic receptor. Antiangiogenic inhibitors slow down or stop new blood-vessel formation from pre-existing vasculature. Some antiangiogenic drugs inhibiting the VEGFR2 receptor are successfully used in clinics for the treatment of several types of tumours in synergy with chemotherapy (e.g., Nexavar^® from Bayer, Sutent^® from Pfizer and Votrient^® from GlaxoSmithKline, approved by the FDA in 2005, 2006 and 2009, respectively). The structure of 5 is an important pharmacophoric fragment of potent VEGFR2 inhibitors (e.g., AAZ from PDB complex 1Y6A, enzymatic IC₅₀ = 22 nM). Up to now, 25 VEGFR2 inhibitors possessing a fragment of 5 can be found in the literature. Despite the high significance of 5-(ethylsulfonyl)-2-methoxyaniline (5) its preparation has not yet been described.

Results: Here we have developed a convenient synthesis of important polyheterosubstituted aniline 5 starting from commercially available 4-methoxybenzene-1-sulfonyl chloride (1) in four steps and 59% overall yield. The target 5-(ethylsulfonyl)-2-methoxyaniline (5) and its synthetic intermediates 2–4 together with a new compound 5-(ethylsulfonyl)-2-methoxy-1,3-dinitrobenzene (4a) have been precisely physicochemically characterised.