Modeling a cancerous tumor development in a virtual patient suffering from a depressed state of mind: Simulation of
R Lahoz-Beltra1, R Juárez Rodriguez1
1Department of Biodiversity, Ecology and Evolution (Biomathematics), Faculty of Biological Sciences. c/ Jose Antonio Novais 2, Complutense University of Madrid, 28040, Madrid, Spain.
Abstract:
Cancer is a disease of evolutionary origin in which a group of cells in the body initiate evolutionary changes under certain circumstances that can lead to the formation of a tumor. It is currently believed that a hostile cell environment can lead to the cells of an organ or tissue initiating a whole series of physiological changes that will lead to the transformation of healthy cells into cancerous ones. During the process of transformation, cells evolve under a paradigm known as somatic evolution. In this work the first stages of the formation of a cancerous tumor have been simulated assuming that the cause of the formation is the genetic instability of the cells, being the cause of this instability the presence of chronic inflammation, phenomenon responsible for the appearance of a hostile cellular environment. The model simulates a virtual patient where an altered state of mind, whether depressive, stressed or similar, will lead to disturbed hormone levels that will eventually lead to a condition of chronic inflammation. A novelty of the work is the design of a genetic algorithm oriented to the simulation of somatic evolution, representing the cells by means of a vector that encodes the nodes of a stochastic network. These nodes represent the states of the genes, hallmarks of the cancer and genetic stability of a cell, simulating the formation of a tumor in the caverns of the colon. Another novelty of the model is the design of a virtual patient in which a chatbot for the simulation of the state of mind is hybridized with differential equations simulating both the hormones of the so-called hypothalamic-pituitary-adrenal axis and the cytokines involved in the mechanism of cellular inflammation. The work is a first step in the design of models that under a holistic vision allow the simulation and therefore a greater understanding of the different facets of a disease as complex as cancer.
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