Agent-Based Learning Model for the Obesity Paradox in RCC - Belenchia, Matteo; Rocchetti, Giacomo; Maestri, Stefano; Cimadamore, Alessia; Montironi, Rodolfo; Santoni, Matteo; Merelli, Emanuela (Frontiers in Bioengineering and Biotechnology, 2021)
A recent study on the immunotherapy treatment of Renal Cell Carcinoma reveals better outcomes in obese patients compared to lean subjects. This enigmatic contradiction has been explained, in the context of the debated Obesity Paradox, as the effect produced by the cell interactions network on the tumour microenvironment during the immune response. To better understand this hypothesis, we provide a computational framework for the in silico study of the tumour behaviour. The starting model of the tumour, based on the cell interactions network, has been described as a multiagent system, whose simulation provides the hypothesised effects on the tumour microenvironment. The medical needs in the immunotherapy design meet the capabilities of a multiagent simulator to reproduce the dynamics of the cell interactions network, meaning a reaction to environmental changes introduced through the experimental data. Type a message