Physics Colloquium: TGF- inhibition can overcome cancer primary resistance to PD-1 blockade

Physics Colloquium
TGF- inhibition can overcome cancer primary resistance to PD-1 blockade: a mathematical model

Dr. Nourridine Siewe
Assistant Professor
School of Mathematical Sciences, RIT

Abstract:
Primary resistance to PD-1 blockade is reported to occur under conditions of immunosuppressive tumor environment, a condition caused by myeloid derived suppressor cells (MDSCs), and by T cells​ exclusion, due to increased level of T regulatory cells (Tregs). Since TGF- activates Tregs, TGF- inhibitor may overcome primary resistance to anti-PD-1. Indeed, recent mice experiments show that combining anti-PD-1 with anti-TGF- yields significant therapeutic improvements compared to anti-TGF- alone. The present paper introduces two cancer-specific parameters and, correspondingly, develops a mathematical model which explains how primary resistance to PD-1 blockade occurs, in terms of the two cancer-specific parameters, and how, in combination with anti-TGF-, anti-PD-1 provides significant benefits. The model is represented by a system of partial differential equations and the simulations are in agreement with the recent mice experiments. In some cancer patients, treatment with anti-PD-1 results in rapid progression of the disease, known as hyperprogression disease (HPD). The mathematical model can also explain how this situation arises, and it predicts that HPD may be reversed by combining anti-TGF- to anti-PD-1. The model is used to demonstrate how the two cancer-specific parameters may serve as biomarkers in predicting the efficacy of combination therapy with PD-1 and TGF- inhibitors.

Speaker Bio:
I am a second year Assistant Professor of mathematics at Rochester Institute of Technology. I obtained by PhD from Howard University in 2016 and went on to do two postdocs: one at the National Institute for Mathematical and Biological Synthesis (NIMBioS) and the other at the University of British Columbia (in Canada). My research interests include using ordinary and partial differential equations to develop mathematical models of biological, ecological and socio-economical systems.

Intended Audience:
Beginners, undergraduates, graduates, experts. Those with interest in the topic.

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