Abstract:
Increasing evidence suggests subtype variability of the tumor microenvironment (TME) governs the response to immune checkpoint inhibitors (ICI) therapy for a wide range of solid tumors. We bring to bear a range of systems-theoretic tools to explain an extensive set of clinically relative phenotypes relating the subtype diversity to different ICI outcome possibilities and predict subtype-specific combination therapies for an improved therapy outcome. We derived kinetics-independent (barring the assumption of monotone, bounded kinetics) generalized rules relating to TME balances that govern the emergence of discrete attractor sets and the subsequent ICI-driven reprogramming of the TME. The analytical findings have been numerically verified with extensive simulation subtypes. Overall, we present a generalized systems formalism that translates the relevant TME phenotypes to systems requirements that can serve as the foundation for building patient-specific quantitative models. Overall, the kinetics-agnostic mapping of relevant clinical features of the solid tumor to well-defined properties of the dynamical system paves the way for patient-specific model development and validation of tumors as complex systems.
About the speaker:
Priyan Bhattacharya received his Ph.D. from the Department of Chemical Engineering at the Indian Institute of Technology Madras. His Ph.D. thesis focused on designing systems-theoretic algorithms to identify homeostatic biochemical networks. Priyan is currently a post-doctoral research fellow at the Sidney Kimmel Medical College, Thomas Jefferson University, where he is working towards the development and data-driven reconstruction of cell-state-specific network models for Head and Neck Squamous Cell Carcinoma and long-term alcoholic liver diseases. Priyan's primary research interest lies in applying systems and control theory to modeling and analyzing complex biological systems.
