Hajim School of Engineering and Applied Sciences UofR logo BME SMD logo Hajim SEAS logo

Friday, Jun 19, 2009

10:00 AM11:00 AM CSB 209

Upcoming Events

There are no upcoming events to display

Past events

BME MS Defense: Rashmi Sriram

Development of a Theoretical Model for the Detection of Antibody-Protein Interactions by Arrayed Imaging Reflectometry and its Implementation for the Sensitive Detection of FGF-2

Supervised by Prof. Ben Miller

Abstract

Prostate Cancer is the second leading cause of death in the United States. Even today, the utility of PSA (Prostate Specific Antigen) as a biomarker for screening prostate cancer is controversial, in terms of its specificity and the upper limit of normality (ULN). Meanwhile, studies have thrown light on the potential of Fibroblast Growth Factor-2 (FGF-2); an angiogenic factor, to serve as a sensitive and specific biomarker for prostate cancer. It has been observed that the levels of this protein are significantly elevated in the serum of a prostate cancer patient from its normal level of 1 pg/ml. Arrayed Imaging Reflectometry (AIR), a sensitive label-free biosensing technique, has been utilized to develop a sensitive and specific assay for FGF-2. We have successfully shown the detection of purified FGF-2 down to a level of 100 fg/ml.

In addition to the sensitive detection of purified FGF-2, a theoretical model was developed to determine the nature of behavior between the intensity of reflected light from an AIR chip as a function of protein concentration. The mathematical model revealed the presence of a sigmoidal relationship. The developed model was further validated experimentally for FGF-2 and FGF-2 antibody-protein system using spectroscopic ellipsometry and AIR. The study showed a close correlation between the theoretical and experimental results in lower concentration (pM to fM) ranges of the protein and a slight discrepancy at higher concentration ranges (nM). This is however justifiable due to the inherent assumptions of the mathematical model. Owing to a good correlation between theory and practicality at clinically relevant concentration ranges this model holds the potential to speed up data analysis while looking at few hundreds of proteins from complex biological fluids provided the strength of interaction of each of these antibody-protein pairs is known.