126353 20241125101140.0 doi 10.1016/j.compbiomed.2023.106897 sideral 133798 ART-2023-133798 eng Carrasco-Mantis, Ana A mechanobiological model for tumor spheroid evolution with application to glioblastoma: A continuum multiphysics approach 2023 Access copy available to the general public Unrestricted Background: Spheroids are in vitro quasi-spherical structures of cell aggregates, eventually cultured within a hydrogel matrix, that are used, among other applications, as a technological platform to investigate tumor formation and evolution. Several interesting features can be replicated using this methodology, such as cell communication mechanisms, the effect of gradients of nutrients, or the creation of realistic 3D biological structures. The main objective of this work is to link the spheroid evolution with the mechanical activity of cells, coupled with nutrient consumption and the subsequent cell dynamics. Method: We propose a continuum mechanobiological model which accounts for the most relevant phenomena that take place in tumor spheroid evolution under in vitro suspension, namely, nutrient diffusion in the spheroid, kinetics of cellular growth and death, and mechanical interactions among the cells. The model is qualitatively validated, after calibration of the model parameters, versus in vitro experiments of spheroids of different glioblastoma cell lines. Results: Our model is able to explain in a novel way quite different setups, such as spheroid growth (up to six times the initial configuration for U-87 MG cell line) or shrinking (almost half of the initial configuration for U-251 MG cell line); as the result of the mechanical interplay of cells driven by cellular evolution. Conclusions: Glioblastoma tumor spheroid evolution is driven by mechanical interactions of the cell aggregate and the dynamical evolution of the cell population. All this information can be used to further investigate mechanistic effects in the evolution of tumors and their role in cancer disease. info:eu-repo/grantAgreement/ES/AEI/PRE2019-090391 info:eu-repo/grantAgreement/ES/MICINN/PGC2018-097257-B-C31 info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 7.0 2023 BIOLOGY 7 / 109 = 0.064 2023 Q1 T1 MATHEMATICAL & COMPUTATIONAL BIOLOGY 2 / 66 = 0.03 2023 Q1 T1 ENGINEERING, BIOMEDICAL 16 / 123 = 0.13 2023 Q1 T1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 19 / 170 = 0.112 2023 Q1 T1 1.481 2023 Health Informatics 2023 Q1 Computer Science Applications 2023 Q1 11.7 2023 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Randelovic, Teodora (orcid)0000-0001-7232-7588 Castro-Abril, Héctor Ochoa, Ignacio Universidad de Zaragoza (orcid)0000-0003-2410-5678 Doblaré, Manuel Universidad de Zaragoza (orcid)0000-0001-8741-6452 Sanz-Herrera, José A. 1003 443 Universidad de Zaragoza Dpto. Anatom.Histolog.Humanas Area Histología 5004 605 Universidad de Zaragoza Dpto. Ingeniería Mecánica Área Mec.Med.Cont. y Teor.Est. 159 (2023), 106897 [17 pp.] Comput. biol. med. Computers in biology and medicine 0010-4825 2738132 http://zaguan.unizar.es/record/126353/files/texto_completo.pdf Versión publicada 2504518 http://zaguan.unizar.es/record/126353/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:126353 articulos driver 2024-11-22-12:02:22 ARTICLE