Dataset Information

Hutchinson2016 - Vascular phenotype identification and anti-angiogenic treatment recommendation

ABSTRACT: This is a spatially averaged multiscale mathematical model of tumor angiogenesis. The model describes the dynamics of VEGF, Ang1, Ang2, and PDGF, coupled with those of mature and immature endothelial cells and pericyte cells.

SUBMITTER: Johannes Meyer

PROVIDER: MODEL1911130007 | BioModels | 2019-11-13

REPOSITORIES: BioModels

ACCESS DATA

Publications

Vascular phenotype identification and anti-angiogenic treatment recommendation: A pseudo-multiscale mathematical model of angiogenesis.

Hutchinson L G LG Gaffney E A EA Maini P K PK Wagg J J Phipps A A Byrne H M HM

Journal of theoretical biology 20160314

The development of anti-angiogenic drugs for cancer therapy has yielded some promising candidates, but novel approaches for interventions to angiogenesis have led to disappointing results. In addition, there is a shortage of biomarkers that are predictive of response to anti-angiogenic treatments. Consequently, the complex biochemical and physiological basis for tumour angiogenesis remains incompletely understood. We have adopted a mathematical approach to address these issues, formulating a spa ...[more]

PMID: 26987523

Similar Datasets

Project description:Exposure to traffic-related pollutants, including diesel exhaust, is associated with increased risk of cardiopulmonary disease and mortality; however, the precise biochemical pathways underlying these effects are not known. To investigate biological response mechanisms underlying exposure to traffic related pollutants, we used an integrated molecular response approach that included high-resolution metabolomic profiling and peripheral blood gene expression to identify biological responses to diesel exhaust exposure. Plasma samples were collected from 73 non-smoking males employed in the US trucking industry between February 2009 and October 2010 and analyzed using untargeted high-resolution metabolomics to characterize association with shift- and week-averaged levels of elemental carbon (EC), organic carbon (OC) and particulate matter with diameter ≤ 2.5 μm (PM2.5). Annotated metabolites associated with exposure were then tested for relationships with the peripheral blood transcriptome using multivariate selection and network correlation. Week-averaged EC and OC levels, which were averaged across multiple shifts during the workweek, resulted in the greatest exposure-associated metabolic alterations compared to shift-averaged exposure levels. Metabolic changes associated with EC exposure suggest increased lipid peroxidation products, biomarkers of oxidative stress, thrombotic signaling lipids, and metabolites associated with endothelial dysfunction from altered nitric oxide metabolism, while OC exposures were associated with antioxidants, oxidative stress biomarkers and critical intermediates in nitric oxide production. Correlation with whole blood RNA gene expression provided additional evidence of changes in processes related to endothelial function, immune response, inflammation, and oxidative stress. We did not detect metabolic associations with PM2.5. This study provides an integrated molecular assessment of human exposure to traffic-related air pollutants that includes diesel exhaust. Metabolite and gene expression changes associated with exposure to EC and OC are consistent with increased risk of cardiovascular diseases and the adverse health effects of traffic-related air pollution.

Dataset Information

Hutchinson2016 - Vascular phenotype identification and anti-angiogenic treatment recommendation

Publications

Vascular phenotype identification and anti-angiogenic treatment recommendation: A pseudo-multiscale mathematical model of angiogenesis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure