Sensitivity analysis methods have a long history and have been widely applied in different fields, such as environmental modeling, economical modeling for decision making, parameter estimation and control, chemical kinetics, and biological modeling analysis, with metabolic networks, signaling pathways and genetic circuits. Cancer immunotherapy is based on the idea of immune surveillance. Immunotherapy, also named biologic therapy, represents a type of cancer treatment that boosts the body's natural defenses to fight cancer. It uses substances made by the body or in a laboratory to improve or restore immune system function. The aim of this paper is to perform a global sensitivity analysis applied to a mathematical model for the tumor-immune interaction. Global sensitivity analysis quantifies the importance of model inputs and their interactions with respect to model output. It provides an overall view on the influence of inputs on outputs as opposed to a local view of partial derivatives as in local sensitivity analysis. The model under investigation is specialized for autologous dendritic cell transfection therapy. It consists of a system of five nonlinear ordinary differential equations which define the rates of change for the following key immune cell populations: the tumor-specific CD4 T helper cells, the tumor-specific CD8 T cells or CTLs cytotoxic cells, the cancer cells that expose the tumor-associated antigens or TAAs, the mature dendritic cells loaded with the TAAs, and the IL-2 secreted by the tumor-specific CD4 T helper cells and responsible for T cell growth. We show how to globally analyze the sensitivity of this complex system by means of several graphical objects: sensitivity heat map, singular spectrum plot, and parameter sensitivity spectrum.

cancer; immunotherapy; global sensitivity; sensitivity heat map; singular spectrum plot; parameter sensitivity spectrum.