Skip to content. Skip to main navigation.

News Archive 2001 - 2010

Disease Biomarkers Will Aid in Diagnosis and Treatment

July 31, 2006

Many diseases can be cured if detected early enough for effective treatment. Biomarkers that identify the presence of diseases aid in early detection and are also useful in the discovery of new drug targets for therapy. That’s why researchers at the University of Texas at Arlington College of Engineering are working on ways to identify and profile these biomarkers.

Assistant Professor of Computer Science and Engineering Jean Gao is the principal investigator in a project funded by a $356,000 grant from the National Science Foundation. She is teaming with two researchers at the University of Texas Southwestern Medical Center at Dallas, Assistant Professor of Pathology Dr. Kevin Rosenblatt and Associate Professor of Obstetrics/Gynecology Dr. John Schorge, to identify serum proteins closely associated with disease biomarkers. Protein/peptide abnormalities are expressed differently between diseased and healthy individuals. This project will construct a high-throughput proteomic profiling analysis toolset called a Proteomics Biomarker Information System that can provide early biomarker detection and identification for clinical proteomics healthcare.

Drs. Gao, Rosenblatt and Schorge are using two methods to identify the biomarkers: high resolution profiling to analyze the low-molecular weight end of the proteomic spectrum for more precise analysis, and an identification and sequencing of the underlying discriminatory proteins/peptides to reveal the insights of biomarkers and characterize disease pathway.

Their experiments will be driven by a series of case studies, including ovarian cancer early relapse monitoring and prostate cancer diagnosis. The solutions for these case studies will have a direct impact on individual areas. At the conclusion of the project, source code and data will be available for general dissemination over the Internet and the discoveries will be integrated into the classroom.

The results of this project will have an impact on the broad medical community that is in need of such a proteomic profiling data analysis tool. Simple, inexpensive, and minimally invasive serum proteomic methods readily lend themselves to screening-test development; their robustness and ease promise to translate into routine clinical practice.