A mechanobiological model for tumor spheroid evolution with application to glioblastoma: A continuum multiphysics approach

Carrasco-Mantis, Ana ; Randelovic, Teodora ; Castro-Abril, Héctor ; Ochoa, Ignacio (Universidad de Zaragoza) ; Doblaré, Manuel (Universidad de Zaragoza) ; Sanz-Herrera, José A.

Resumen: 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.

Idioma: Inglés

DOI: 10.1016/j.compbiomed.2023.106897

Año: 2023

Publicado en: Computers in biology and medicine 159 (2023), 106897 [17 pp.]
ISSN: 0010-4825

Factor impacto JCR: 7.0 (2023)

Categ. JCR: BIOLOGY rank: 7 / 109 = 0.064 (2023) - Q1 - T1
Categ. JCR: MATHEMATICAL & COMPUTATIONAL BIOLOGY rank: 2 / 66 = 0.03 (2023) - Q1 - T1
Categ. JCR: ENGINEERING, BIOMEDICAL rank: 16 / 123 = 0.13 (2023) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 19 / 170 = 0.112 (2023) - Q1 - T1

Factor impacto CITESCORE: 11.7 - Health Informatics (Q1) - Computer Science Applications (Q1)

Factor impacto SCIMAGO: 1.481 - Health Informatics (Q1) - Computer Science Applications (Q1)

Financiación: info:eu-repo/grantAgreement/ES/AEI/PRE2019-090391
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PGC2018-097257-B-C31

Tipo y forma: Article (Published version)

Área (Departamento): Area Histología (Dpto. Anatom.Histolog.Humanas)
Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)