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Towards Simulating Carcinogenesis: Modeling and Simulating Carcinogenesis, Hematopoietic Tissue Homeostasis and Leukemogenesis
Jenny Groten,
Maximilian Georg,
Oliver Worm,
Christoph Borner,
Roland Mertelsmann
Affiliation: Institut für Molekulare Medizin und Zellforschung
Keywords: Carcinogenesis, Modeling, Simulation, Tissue Homeostasis, Hematopoiesis, Leukemogenesis
Categories: Artificial Intelligence, Modeling and Simulation
DOI: 10.17160/josha.3.7.253
Languages: English
The previously identified cancer hallmarks (Groten et al. 2016, DOI: 10.17160/josha.3.7.252 ) were described by mathematical algorithms. Subsequently, a computational simulation of carcinogenesis has been developed. In the next step, the proposed algorithms and correlations have been tested, validated and adapted through the simulation (http://mertelsmann.psiori.com/). In a second model, we transferred the insights won from the first simulation to the simulation of hematopoiesis tissue homeostasis and leukemogenesis (http://hem-model.psiori.com/hema_simulation). Our findings indicate that the 10 “Hallmarks” proposed by Hanahan and Weinberg can be assigned to two major groups, “Growth/Apoptosis Balance” and “Genetic Fidelity, Immortality”. Modeling Hematopoiesis revealed one missing Hallmark, “Block of Differentiation”, which we propose to assign to the broader term “Stem Cell Features”. These two simulation models, with a focus on visualization and interactivity, depict previous assertions as well as provide novel unexpected, hypothesis generating and possibly underestimated insights. Simulation promises to contribute to a novel type of evidence and hypothesis generation in cancer research, especially in conjunction with Machine Learning tools, which allow time-lapse experiments, independent self-learning of a system and, thus, full exploitation of computational power.