Therapeutic effects of sunitinib, one of the anti-angiogenetic drugs, in a murine arthritis

Explainable biology for improved therapies in precision medicine: AI is not enough

Technological advances and high-throughput bio-chemical assays are rapidly changing ways how we formulate and test biological hypotheses, and how we treat patients. Most complex diseases arise on a background of genetics, lifestyle and environment factors, and manifest themselves as a spectrum of symptoms. To fathom intricate biological processes and their changes from healthy to disease states, we need to systematically integrate and analyze multi-omics datasets, ontologies, and diverse annotations. Without proper management of such complex biological and clinical data, artificial intelligence (AI) algorithms alone cannot be effectively trained, validated, and successfully applied to provide trustworthy and patient-centric diagnosis, prognosis and treatment. Precision medicine requires to use multi-omics approaches effectively, and offers many opportunities for using AI, "big data" analytics, and integrative computational biology workflows. Advances in optical and biochemical assay technologies including sequencing, mass spectrometry and imaging modalities have transformed research by empowering us to simultaneously view all genes expressed, identify proteome-wide changes, and assess interacting partners of each individual protein within a dynamically changing biological system, at an individual cell level. While such views are already having an impact on our understanding of healthy and disease conditions, it remains challenging to extract useful information comprehensively and systematically from individual studies, ensure that signal is separated from noise, develop models, and provide hypotheses for further research. Data remain incomplete and are often poorly connected using fragmented biological networks. In addition, statistical and machine learning models are developed at a cohort level and often not validated at the individual patient level. Combining integrative computational biology and AI has the potential to improve understanding and treatment of diseases by identifying biomarkers and building explainable models characterizing individual patients. From systematic data analysis to more specific diagnostic, prognostic and predictive biomarkers, drug mechanism of action, and patient selection, such analyses influence multiple steps from prevention to disease characterization, and from prognosis to drug discovery. Data mining, machine learning, graph theory and advanced visualization may help identify diagnostic, prognostic and predictive biomarkers, and create causal models of disease. Intertwining computational prediction and modeling with biological experiments leads to faster, more biologically and clinically relevant discoveries. However, computational analysis results and models are going to be only as accurate and useful as correct and comprehensive are the networks, ontologies and datasets used to build them. High quality, curated data portals provide the necessary foundation for translational research. They help to identify better biomarkers, new drugs, precision treatments, and should lead to improved patient outcomes and their quality of life. Intertwining computational prediction and modeling with biological experiments, efficiently and effectively leads to more useful findings faster.

Endothelial cell and T-cell crosstalk: Targeting metabolism as a therapeutic approach in chronic inflammation

The role of metabolic reprogramming in the coordination of the immune response has gained increasing consideration in recent years. Indeed, it has become clear that changes in the metabolic status of immune cells can alter their functional properties. During inflammation, T cells need to generate sufficient energy and biomolecules to support growth, proliferation, and effector functions. Therefore, T cells need to rearrange their metabolism to meet these demands. A similar metabolic reprogramming has been described in endothelial cells, which have the ability to interact with and modulate the function of immune cells. In this overview, we will discuss recent insights in the complex crosstalk between endothelial cells and T cells as well as their metabolic reprogramming following activation. We highlight key components of this metabolic switch that can lead to the development of new therapeutics against chronic inflammatory disorders. LINKED ARTICLES: This article is part of a themed issue on Cellular metabolism and diseases. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v178.10/issuetoc.

Alleviation of Collagen-Induced Arthritis by Crotonoside through Modulation of Dendritic Cell Differentiation and Activation

Crotonoside, a guanosine analog originally isolated from Croton tiglium, is reported to be a potent tyrosine kinase inhibitor with immunosuppressive effects on immune cells. Due to its potential immunotherapeutic effects, we aimed to evaluate the anti-arthritic activity of crotonoside and explore its immunomodulatory properties in alleviating the severity of arthritic symptoms. To this end, we implemented the treatment of crotonoside on collagen-induced arthritic (CIA) DBA/1 mice and investigated its underlying mechanisms towards pathogenic dendritic cells (DCs). Our results suggest that crotonoside treatment remarkably improved clinical arthritic symptoms in this CIA mouse model as indicated by decreased pro-inflammatory cytokine production in the serum and suppressed expression of co-stimulatory molecules, CD40, CD80, and MHC class II, on CD11c⁺ DCs from the CIA mouse spleens. Additionally, crotonoside treatment significantly reduced the infiltration of CD11c⁺ DCs into the synovial tissues. Our in vitro study further demonstrated that bone marrow-derived DCs (BMDCs) exhibited lower yield in numbers and expressed lower levels of CD40, CD80, and MHC-II when incubated with crotonoside. Furthermore, LPS-stimulated mature DCs exhibited limited capability to prime antigen-specific CD4⁺ and T-cell proliferation, cytokine secretions, and co-stimulatory molecule expressions when treated with crotonoside. Our pioneer study highlights the immunotherapeutic role of crotonoside in the alleviation of the CIA via modulation of pathogenic DCs, thus creating possible applications of crotonoside as an immunosuppressive agent that could be utilized and further explored in treating autoimmune disorders in the future.

Receptor tyrosine kinase inhibitor Sunitinib and integrin antagonist peptide HM-3 show similar lipid raft dependent biphasic regulation of tumor angiogenesis and metastasis

BACKGROUND

Anti-angiogenesis remains an attractive strategy for cancer therapy. Some anti-angiogenic reagents have bell-shape dose-response curves with higher than the effective doses yielding lower anti-angiogenic effects. In this study, two different types of anti-angiogenic reagents, a receptor tyrosine kinase inhibitor Sunitinib and an integrin antagonist peptide HM-3, were selected and their effects on tumor angiogenesis and metastasis were compared. The involved molecular mechanisms were investigated.

METHODS

The effect of high dose Sunitinib and HM-3 on tumor angiogenesis and metastasis was investigated with two animal models: metastasis of B16F10 cells in syngeneic mice and metastasis of human MDA-MB-231 cells in nude mice. Furthermore, mechanistic studies were performed with cell migration and invasion assays and with biochemical pull-down assays of intracellular RhoGTPases. Distribution of integrin αvβ3, α5β1, VEGFR2 and the complex of integrin αvβ3 and VEGFR2 inside or outside of lipid rafts was detected with lipid raft isolation and Western-blot analysis.

RESULTS

Both Sunitinib and HM-3 showed a bell-shape dose-response curve on tumor angiogenesis and metastasis in both animal models. The effects of Sunitinib and HM-3 on endothelial cell and tumor cell proliferation and migration were characterized. Activation of intracellular RhoGTPases and actin stress fiber formation in endothelial and cancer cells following Sunitinib and HM-3 treatment correlated with cell migration analysis. Mechanistic studies confirmed that HM-3 and Sunitinib regulated distribution of integrin αvβ3, α5β1, VEGFR2 and αvβ3-VEGFR2 complexes, both inside and outside of the lipid raft regions to regulate endothelial cell migration and intracellular RhoGTPase activities.

CONCLUSIONS

These data confirmed that a general non-linear dose-effect relationship for these anti-angiogenic drugs exists and their mechanisms are correlative. It also suggests that the effective dose of an anti-angiogenic drug may have to be strictly defined to achieve its optimal clinical effects.

Sensitization and synergistic anti-cancer effects of Furanodiene identified in zebrafish models

Furanodiene is a natural terpenoid isolated from Rhizoma Curcumae, a well-known Chinese medicinal herb that presents anticancer effects in various types of cancer cell lines. In this study, we have successfully established zebrafish xenografts with 5 various human cancer cell lines; and validated these models with anti-cancer drugs used clinically for treating human cancer patients. We found that Furanodiene was therapeutically effective for human JF 305 pancreatic cancer cells and MCF-7 breast cancer cells xenotranplanted into zebrafish. Furanodiene showed a markedly synergistic anti-cancer effect when used in combination with 5-FU (5-Fluorouracil) for both human breast cancer MDA-MB-231 cells and human liver cancer BEL-7402 cells xenotransplanted into zebrafish. Unexpectedly, Furanodiene reversed multiple drug resistance in the zebrafish xenotransplanted with cis-Platinum-resistant human non-small cell lung cancer cells and Adriamycin-resistant human breast cancer cells. Furanodiene played its anti-cancer effects through anti-angiogenesis and inducing ROS production, DNA strand breaks and apoptosis. Furanodiene suppresseed efflux transporter Pgp (P-glycoprotein) function and reduced Pgp protein level, but no effect on Pgp related gene (MDR1) expression. These results suggest sensitizition and synergistic anti-cancer effects of Furanodiene that is worthy of a further investigation.

DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing

Background

The targeting of disease-related proteins is important for drug discovery, and yet target-based discovery has not been fruitful. Contextualizing overall biological processes is critical to formulating successful drug-disease hypotheses. Network pharmacology helps to overcome target-based bottlenecks through systems biology analytics, such as protein-protein interaction (PPI) networks and pathway regulation.

Results

We present a systems polypharmacology platform entitled DrugGenEx-Net (DGE-NET). DGE-NET predicts empirical drug-target (DT) interactions, integrates interaction pairs into a multi-tiered network analysis, and ultimately predicts disease-specific drug polypharmacology through systems-based gene expression analysis. Incorporation of established biological network annotations for protein target-disease, −signaling pathway, −molecular function, and protein-protein interactions enhances predicted DT effects on disease pathophysiology. Over 50 drug-disease and 100 drug-pathway predictions are validated. For example, the predicted systems pharmacology of the cholesterol-lowering agent ezetimibe corroborates its potential carcinogenicity.

When disease-specific gene expression analysis is integrated, DGE-NET prioritizes known therapeutics/experimental drugs as well as their contra-indications. Proof-of-concept is established for immune-related rheumatoid arthritis and inflammatory bowel disease, as well as neuro-degenerative Alzheimer’s and Parkinson’s diseases.

Conclusions

DGE-NET is a novel computational method that predicting drug therapeutic and counter-therapeutic indications by uniquely integrating systems pharmacology with gene expression analysis. DGE-NET correctly predicts various drug-disease indications by linking the biological activity of drugs and diseases at multiple tiers of biological action, and is therefore a useful approach to identifying drug candidates for re-purposing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1065-y) contains supplementary material, which is available to authorized users.

Targeting VEGF and Its Receptors for the Treatment of Osteoarthritis and Associated Pain

Increased vascular endothelial growth factor (VEGF) levels are associated with osteoarthritis (OA) progression. Indeed, VEGF appears to be involved in OA-specific pathologies including cartilage degeneration, osteophyte formation, subchondral bone cysts and sclerosis, synovitis, and pain. Moreover, a wide range of studies suggest that inhibition of VEGF signaling reduces OA progression. This review highlights both the potential significance of VEGF in OA pathology and pain, as well as potential benefits of inhibition of VEGF and its receptors as an OA treatment. With the emergence of the clinical use of anti-VEGF therapy outside of OA, both as high-dose systemic treatments and low-dose local treatments, these particular therapies are now more widely understood. Currently, there is no established disease-modifying drug available for patients with OA, which warrants continued study of the inhibition of VEGF signaling in OA, as stand-alone or adjuvant therapy. © 2016 American Society for Bone and Mineral Research.

Targeting of proangiogenic signalling pathways in chronic inflammation

Angiogenesis is de novo capillary outgrowth from pre-existing blood vessels. This process not only is crucial for normal development, but also has an important role in supplying oxygen and nutrients to inflamed tissues, as well as in facilitating the migration of inflammatory cells to the synovium in rheumatoid arthritis, spondyloarthritis and other systemic autoimmune diseases. Neovascularization is dependent on the balance of proangiogenic and antiangiogenic mediators, including growth factors, cytokines, chemokines, cell adhesion molecules and matrix metalloproteinases. This Review describes the various intracellular signalling pathways that govern these angiogenic processes and discusses potential approaches to interfere with pathological angiogenesis, and thereby ameliorate inflammatory disease, by targeting these pathways.