Science at the Edge Today

11:30 a.m., Room 1400 Biomedical and Physical Sciences Building

Refreshments served at 11:00 a.m.

Spin Glass Models of Cancer Cells

Carlo Piermarocchi, Department of Physics and Astronomy

Michigan State University

Abstract: The increasing availability of gene expression data of different types of normal and cancer cells has created new opportunities for integrating these datasets into mathematical models able to make novel predictions. I will introduce a model, originally developed for the physics of spin glasses, that has the merit of capturing the multi-stable nonlinear dynamics in complex cell signaling networks. The model uses large-scale biological data, specifically genome-wide RNA-sequencing data on pooled cell samples and single cells, and predicts specific combinations of transcription factors or receptor ligands that could induce a specific cellular response. I will discuss the applications of this model to the control of angiogenesis, cell cycle, and disease progression in Multiple Myeloma. Finally, I will discuss how stochastic optimization and iterative in vitro-in silico methods can be used to optimize combinations of drugs targeting these genes, and lead to personalized therapy solutions.