Computational Models of Anti-VEGF Therapies in Prostate Cancer [report]

Feilim M. Gabhann
2013 unpublished
Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services,
more » ... torate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. SPONSOR/MONITOR'S REPORT NUMBER(S) DISTRIBUTION / AVAILABILITY STATEMENT Approved for Public Release; Distribution Unlimited SUPPLEMENTARY NOTES 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). SUBJECT TERMS
doi:10.21236/ada582842 fatcat:jjibfyv5kzckrai5fzdju3c7wy