Jiménez-Sánchez, JuanMartínez-Rubio, ÁlvaroPopov, AntonPérez-Beteta, JuliánAzimzade, YounessMolina-García, DavidBelmonte-Beitia, JuanCalvo, Gabriel F.Pérez-García, Víctor M.2022-12-052022-12-052021-02-10Jiménez-Sánchez J, Martínez-Rubio Á, Popov A, Pérez-Beteta J, Azimzade Y, Molina-García D, et al. A mesoscopic simulator to uncover heterogeneity and evolutionary dynamics in tumors. PLOS Comput Biol. 2021 Feb 10;17(2):e1008266http://hdl.handle.net/10668/4454Increasingly complex in silico modeling approaches offer a way to simultaneously access cancerous processes at different spatio-temporal scales. High-level models, such as those based on partial differential equations, are computationally affordable and allow large tumor sizes and long temporal windows to be studied, but miss the discrete nature of many key underlying cellular processes. Individual-based approaches provide a much more detailed description of tumors, but have difficulties when trying to handle full-sized real cancers. Thus, there exists a trade-off between the integration of macroscopic and microscopic information, now widely available, and the ability to attain clinical tumor sizes. In this paper we put forward a stochastic mesoscopic simulation framework that incorporates key cellular processes during tumor progression while keeping computational costs to a minimum. Our framework captures a physical scale that allows both the incorporation of microscopic information, tracking the spatio-temporal emergence of tumor heterogeneity and the underlying evolutionary dynamics, and the reconstruction of clinically sized tumors from high-resolution medical imaging data, with the additional benefit of low computational cost. We illustrate the functionality of our modeling approach for the case of glioblastoma, a paradigm of tumor heterogeneity that remains extremely challenging in the clinical setting.enAtribución 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/Genetic heterogeneityNeoplasmsBrain neoplasmsComputational biologyComputer simulationCell divisionHeterogeneidad genéticaNeoplasiasNeoplasias encefálicasBiología computacionalSimulación por ordenadorDivisión celularMedical Subject Headings::Phenomena and Processes::Mathematical Concepts::AlgorithmsMedical Subject Headings::Diseases::Neoplasms::Neoplasms by Site::Nervous System Neoplasms::Central Nervous System Neoplasms::Brain NeoplasmsMedical Subject Headings::Phenomena and Processes::Cell Physiological Phenomena::Cell Physiological Processes::Cell DeathMedical Subject Headings::Phenomena and Processes::Cell Physiological Phenomena::Cell Physiological Processes::Cell Cycle::Cell DivisionMedical Subject Headings::Phenomena and Processes::Cell Physiological Phenomena::Cell Physiological Processes::Cell MovementMedical Subject Headings::Disciplines and Occupations::Natural Science Disciplines::Biological Science Disciplines::Biology::Computational BiologyMedical Subject Headings::Information Science::Information Science::Computing Methodologies::Computer SimulationMedical Subject Headings::Diseases::Pathological Conditions, Signs and Symptoms::Pathologic Processes::Disease Attributes::Disease ProgressionMedical Subject Headings::Diseases::Neoplasms::Neoplasms by Histologic Type::Neoplasms, Nerve Tissue::Neuroectodermal Tumors::Neoplasms, Neuroepithelial::Glioma::Astrocytoma::GlioblastomaMedical Subject Headings::Phenomena and Processes::Genetic Phenomena::Genetic Variation::MutationMedical Subject Headings::Diseases::NeoplasmsMedical Subject Headings::Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Stochastic Processesresearch article33566821Acceso abierto10.1371/journal.pcbi.10082661553-7358PMC7901744