This project is focused both on career development and on the completion of a specific independent research plan related particularly to the mission of the National Cancer Institute. The career development objective of this award is to enable the transition of Dr. Nathan Price from his current position as a postdoctoral fellow at the Institute for Systems Biology to an assistant professor at the University of Illinois at Urbana-Champaign capable of competing for independent funding in cancer research. Dr. Price has an exceptionally strong track record in systems biology for his career stage, having co-authored over 20 articles for publication in his graduate studies as well as completing significant cancer-related studies during his postdoctoral training. Dr. Price accepted a faculty position at the University of Illinois at Urbana-Champaign prior to finishing graduate school, but chose to defer this position for 2-3 years for the express purpose of transitioning his career focus onto systems analysis of cancer. The mentored phase of this award will provide Dr. Price with the opportunity to receive guidance from one of the leading scientists in the world working on systems approaches to cancer, Dr. Leroy Hood, who is President of the Institute for Systems Biology, Director of the Center for Systems Biology, and Co-Director of the Nanosystems Biology Cancer Center. Dr. Price's proposed research focuses on developing a novel capability to identify causal network perturbations involved in glioblastoma through analysis of patterns in secreted protein concentrations. This work will also focus on studying the relationship between transcriptomic data (which is plentiful) with secreted protein data (which serve as ideal diagnostic markers). The associated measurements of secreted proteins will provide a wealth of candidate markers for glioblastomas, and a team of glioblastoma researchers has been assembled to assist in translating the work of this project to the clinic (to be financed elsewhere). The ultimate long-term goal of this work is to develop highly informative secreted protein marker panels for glioblastoma multiforme, the most aggressive and deadly form of glioma. The use of systems analysis of blood, coupled with computational models of interacting networks such as will be developed in this-study, has the long-term potential not only of identifying perturbed networks in vivo, but eventually of enabling a new avenue of studying human biology and disease in vivo in a non-invasive manner. The relevance of this work to public health is that specific secreted protein markers for glioblastoma, a type of brain cancer common particularly in children, will be developed where none exist today. These rnarkers will allow for the earlier diagnosis and hence better prognosis of patients, and will be far less irjvasive than the brain biopsy currently required to diagnose advanced gliomas. Also, we will identify perturbed subnetworks in the most aggressive type of glioma (glioblastoma multiforme) leading to potential drug targets for further analysis.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Transition Award (R00)
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Study Section
Subcommittee G - Education (NCI)
Program Officer
Tricoli, James
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University of Illinois Urbana-Champaign
Engineering (All Types)
Schools of Engineering
United States
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Craig, Theodore A; Zhang, Yuji; Magis, Andrew T et al. (2014) Detection of 1?,25-dihydroxyvitamin D-regulated miRNAs in zebrafish by whole transcriptome sequencing. Zebrafish 11:207-18
Ma, Shuyi; Sung, Jaeyun; Magis, Andrew T et al. (2014) Measuring the effect of inter-study variability on estimating prediction error. PLoS One 9:e110840
Sangar, Vineet; Funk, Cory C; Kusebauch, Ulrike et al. (2014) Quantitative proteomic analysis reveals effects of epidermal growth factor receptor (EGFR) on invasion-promoting proteins secreted by glioblastoma cells. Mol Cell Proteomics 13:2618-31
Wang, Chunjing; Funk, Cory C; Eddy, James A et al. (2013) Transcriptional analysis of aggressiveness and heterogeneity across grades of astrocytomas. PLoS One 8:e76694
Chandrasekaran, Sriram; Price, Nathan D (2013) Metabolic constraint-based refinement of transcriptional regulatory networks. PLoS Comput Biol 9:e1003370
Wang, Yuliang; Eddy, James A; Price, Nathan D (2012) Reconstruction of genome-scale metabolic models for 126 human tissues using mCADRE. BMC Syst Biol 6:153
Craig, Theodore A; Zhang, Yuji; McNulty, Melissa S et al. (2012) Research resource: whole transcriptome RNA sequencing detects multiple 1?,25-dihydroxyvitamin D(3)-sensitive metabolic pathways in developing zebrafish. Mol Endocrinol 26:1630-42
Bebek, Gurkan; Koyuturk, Mehmet; Price, Nathan D et al. (2012) Network biology methods integrating biological data for translational science. Brief Bioinform 13:446-59
Tian, Q; Price, N D; Hood, L (2012) Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine. J Intern Med 271:111-21
Magis, Andrew T; Price, Nathan D (2012) The top-scoring 'N' algorithm: a generalized relative expression classification method from small numbers of biomolecules. BMC Bioinformatics 13:227

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