Myong-Hee Sung, Ph.D.

Biometric Research Branch

National Cancer Institute, National Institutes of Health

MODELING APPROACHES FOR OPTIMIZATION OF THERAPY AGAINST ONCOGENIC MOLECULAR NETWORKS/METHODS TO PREDICT ANTIGENIC PEPTIDES FOR T LYMPHOCYTES

Date: Tuesday, September 21, 2004

Time: 11:00 AM- 12:00 PM EST

Location: Rm. 110 Clark Hall

Videoconferenced to

Talbot Library, 709 Traylor Research Bldg.

Abstract:

In the first part of the seminar, I will present a quantitative analysis of dynamic interactions between an oncogenic pathway and a drug molecule. The extensively studied NF-?B network is chosen to illustrate the approach. NF-?B is a transcription factor and its persistent activity is associated with tumor formation, growth, metastasis, and drug resistance in many cancer types. Current therapeutic efforts for inhibiting this central "switch" include using small molecules to block a selected target in this pathway. Recognizing the regulatory network structure of the NF-?B pathway, we examine in silico the effects of inhibitors targeting various network components, using a kinetic model of the pathway. Simulations of the corresponding perturbed system dynamics show that the resulting time course of inhibition has distinct target-specific profiles. We also examine the dynamic effects of the recently approved proteasome inhibitor, Bortezomib (PS-341), and compare it with other inhibitors, taking its pharmacokinetics into consideration. Such kinetic analyses of the "drugged" molecular system will facilitate optimal drug target selection and the development of treatment protocols for a molecularly targeted therapy.

The problem of identifying potential T cell epitopes (short stimulatory peptides derived from proteins expressed by a pathogen or cancer) presents great challenges for both predictive modeling and experimental screening in the context of vaccine design and immunotherapy. In the second part of the seminar, I will explain the issues involved and describe a method that was designed to overcome some of the challenges. This prediction method had been applied to analyze HIV sequences, tumor associated antigens, and autoimmune antigens for the presence of putative T cell epitopes.

For further information on videoconferencing or disability access, contact Anne Albinak at 410-516-5310, aalbinak@jhu.edu

Tuesday, September 21, 2004
2:00pm-3:00pm

Clark Hall, Room 110

and

videocast to

Talbot Library

Traylor, Room 709