Computational Models of Anti-VEGF Therapies in Prostate Cancer
Abstract
The vascular endothelial growth factor (VEGF) family of cytokines promotes vascularization, tumorigenesis and metastasis in many cancers. Our goal is to develop computational models that combine mechanistic topological data on the VEGF protein interaction network with gene expression datasets for a large population of prostate cancers. We have assembled databases of prostate cancer gene expression data, and analyzed the data using bioinformatic techniques, identifying key VEGF-based subgroups of prostate cancer plus biomarkers that identify these groups. We have also created new computational models to simulate prostate cancer, based on the individualized gene expression data. These models will be used to simulate therapies that target the pathway. The therapies to be tested include anti-ligands such as bevacizumab but also anti-receptors and small molecules such as tyrosine kinase inhibitors. In this way, we can build on both the successes and the failures of anti-VEGF trials to date in order to develop more effective therapies for prostate cancer. This progress will continue, and we will be able to develop models of therapies including bevacizumab and other drugs, in order to design improved therapeutic approaches (both for individuals and for the population).
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2013
- Accession Number
- ADA582842
Entities
People
- Feilim Mac Gabhann
Organizations
- Johns Hopkins University