Abstract 370: Modeling signaling networks in tumor immunology

Abstract

Abstract Despite decades of successful discoveries, the overwhelming molecular complexity of cells has been a significant barrier to gain a fundamental understanding of how cells work as a whole, how they are perturbed in cancer, and how they interact with signals from the immune system. To achieve a more complete understanding, will require the assistance of network modeling. By developing computational network models we can introduce cancer mutations to simulate pharmacological perturbations, or loss-of-function and gain-of-function experiments and study the dynamics of biochemical networks change under different immune signaling states. We are developing and applying rule-base (kappa) network modeling of signaling networks to study how microenvironment immune factors influence a tumor's behavior. In particular, that of immune mediated cellular senescence in tumor cells. We have built a rule-base network model of the biochemical network regulating immune mediated cell senescence in melanomas, which carry a BRAFV600 mutation in the MAPK signaling network. Using computational methods we have characterized the crosstalk with cytokine signaling networks and the crosstalk with other growth signaling networks. The development of such a computational model may help researchers understand how BRAFV600 cells in melanomas communicate with their environment by secreting various cytokines and growth factors, as it has become clear that this immune ‘secretory phenotype’ can have pro- as well as anti-tumorigenic effects. By combining rule-based descriptions of the biochemical reactions associated to this phenotype with computer simulation we can open up new avenues for exploring such complex networks linked to melanoma progression. Citation Format: Trevor Clancy, Eivind Hovig. Modeling signaling networks in tumor immunology. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 370. doi:10.1158/1538-7445.AM2014-370