The goal of this Mentored Patient-Oriented Research Career Development Award (K23) is to allow Dr. Ragg to become an independent, transdisciplinary researcher with the distinctive qualifications to integrate computational methods and high throughput molecular biology methods into clinical trials. This application includes both a systematic career development plan and a clinical research project. The career development plan includes: I) formal didactic training through participation in the IU Clinical Investigator Training Enhancement Program; and 2) careful mentorship by Munro Peacock, M.D., Clement McDonald, M.D., and Janet Hock B.D.S., Ph.D. as Dr. Ragg progresses into a truly independent clinical investigator. The patient-oriented research proposal describes the different approaches that can be taken to improve patient survival in osteosarcoma: clinical, molecular, and computational. The clinical strategy seeks to find a blood screening test to predict at the time of diagnosis which patients will fail standard chemotherapy. Our hypothesis is that osteosarcoma patients exhibit distinctive sets of circulating proteins (biomarkers) that predict the response to chemotherapy. This will be tested by the following specific aims. We will first establish the distinctive serum protein profiles of patients with osteosarcoma and identify the serum protein profiles predictive of chemotherapy responsiveness. These biomarkers will then be tested in a prospective clinical trial. To be able to carry out this research, we will establish a high-quality serum bank from pediatric patients at the General Clinical Research Center. The molecular approach seeks to find target genes that can be modified. The most promising is a DNA helicase, RECQL4. Our hypothesis is that this helicase is frequently mutated in osteosarcoma and we will determine the frequency of RECQL4 mutations in sporadic osteosarcomas. The computational approach seeks to integrate all the available clinical and laboratory research in osteosarcoma into a multidisciplinary, interactive data management system that will allow investigators to identify new associations, correlations, and trends through mathematical modeling, data mining, and visual exploration of the available data. We will build a database system, with the support of the investigators from the bone tumor committee of the Children's Oncology Group that will ultimately contain all the data relevant to osteosarcoma research.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Mentored Patient-Oriented Research Career Development Award (K23)
Project #
5K23RR019540-02
Application #
6945781
Study Section
National Center for Research Resources Initial Review Group (RIRG)
Program Officer
Wilde, David B
Project Start
2004-09-07
Project End
2009-07-31
Budget Start
2005-08-01
Budget End
2006-07-31
Support Year
2
Fiscal Year
2005
Total Cost
$134,139
Indirect Cost
Name
Indiana University-Purdue University at Indianapolis
Department
Pediatrics
Type
Schools of Medicine
DUNS #
603007902
City
Indianapolis
State
IN
Country
United States
Zip Code
46202
Clough, Timothy; Thaminy, Safia; Ragg, Susanne et al. (2012) Statistical protein quantification and significance analysis in label-free LC-MS experiments with complex designs. BMC Bioinformatics 13 Suppl 16:S6
Zheng, Cheng; Zhang, Shucha; Ragg, Susanne et al. (2011) Identification and quantification of metabolites in (1)H NMR spectra by Bayesian model selection. Bioinformatics 27:1637-44