Systems biology of the microvasculature

Abstract

The vascular network carries blood throughout the body, delivering oxygen to tissues and providing a pathway for communication between distant organs. The network is hierarchical and structured, but also dynamic, especially at the smaller scales. Remodeling of the microvasculature occurs in response to local changes in oxygen, gene expression, cell-cell communication, and chemical and mechanical stimuli from the microenvironment. These local changes occur as a result of physiological processes such as growth and exercise, as well as acute and chronic diseases including stroke, cancer, and diabetes, and pharmacological intervention. While the vasculature is an important therapeutic target in many diseases, drugs designed to inhibit vascular growth have achieved only limited success, and no drug has yet been approved to promote therapeutic vascular remodeling. This highlights the challenges involved in identifying appropriate therapeutic targets in a system as complex as the vasculature. Systems biology approaches provide a means to bridge current understanding of the vascular system, from detailed signaling dynamics measured in vitro and pre-clinical animal models of vascular disease, to a more complete picture of vascular regulation in vivo. This will translate to an improved ability to identify multi-component biomarkers for diagnosis, prognosis, and monitoring of therapy that are easy to measure in vivo, as well as better drug targets for specific disease states. In this review, we summarize systems biology approaches that have advanced our understanding of vascular function and dysfunction in vivo, with a focus on computational modeling.

Molecular mechanism matters: Benefits of mechanistic computational models for drug development

“…Systems biology approaches have deepened our understanding of the pathways involved in cellular survival & behavior, and how cellular signaling changes in disease [10]. One particularly valuable benefit of mechanistic computational models is their ability to incorporate the specifics of different experimental protocols (e.g.…”

“…1) [13]. Detailed systems pharmacology models can be built and validated using in vitro data and pharmacokinetic studies in animals, and then converted into human- and disease-specific models [10, 24]. In order for these models to make clinically-relevant predictions, they must then be validated against human data to the maximum extent possible.…”

“…While human data is limited, levels of drug and other biomarkers in plasma can be measured with relative ease. Mechanistically-detailed systems pharmacology models can then connect predictions of important but difficult-to-measure quantities, such as drug concentration, occupancy of receptors with drug versus native ligand, and cellular signaling at the target site, to measureable biomarkers [10]. By providing a window into the site of disease, these models have great promise to improve our understanding of both disease and therapy in the human body.…”

“…A promising approach to treat ischemic disease is to promote angiogenesis by targeting one of its key regulators, vascular endothelial growth factor (VEGF). However, despite multiple clinical trials, no VEGF-based pro-angiogenic therapies have yet been approved [10, 37, 38], and success in promoting vascularization of engineered tissue constructs has also been limited [39]. This suggests that our current understanding of the underlying processes is insufficient to effectively promote vascular growth or remodeling.…”

Integrative Utilization of Microenvironments, Biomaterials and Computational Techniques for Advanced Tissue Engineering

“…While most of tissues engineering research groups employ techniques which are limited to specific areas of specialty based on the traditional categorization of science and engineering, there is an increasing demand for a multi-disciplinary and integrative approach implementing combined methodologies based on the existing requirements within this novel field. System biology approach which employs computational techniques along with experimental and analytical methods has been considered by researchers to address complex biological processes [3][4][5][6]. Considering complex mechanisms responsible for biological functions at varying spatial and temporal conditions, system biology approach takes advantage of multi-scale modelling and simulation while calibrating and comparing the results with the experimental data to study these biological phenomena [7][8][9][10].…”