121404 20241125101127.0 doi 10.1016/j.compbiomed.2022.106458 sideral 131615 ART-2023-131615 eng Urdeitx, Pau Universidad de Zaragoza (orcid)0000-0001-6727-563X Computational modeling of multiple myeloma interactions with resident bone marrow cells 2023 Access copy available to the general public Unrestricted The interaction of multiple myeloma with bone marrow resident cells plays a key role in tumor progression and the development of drug resistance. The tumor cell response involves contact-mediated and paracrine interactions. The heterogeneity of myeloma cells and bone marrow cells makes it difficult to reproduce this environment in in-vitro experiments. The use of in-silico established tools can help to understand these complex problems. In this article, we present a computational model based on the finite element method to define the interactions of multiple myeloma cells with resident bone marrow cells. This model includes cell migration, which is controlled by stress–strain equilibrium, and cell processes such as proliferation, differentiation, and apoptosis. A series of computational experiments were performed to validate the proposed model. Cell proliferation by the growth factor IGF-1 is studied for different concentrations ranging from 0–10 ng/mL. Cell motility is studied for different concentrations of VEGF and fibronectin in the range of 0–100 ng/mL. Finally, cells were simulated under a combination of IGF-1 and VEGF stimuli whose concentrations are considered to be dependent on the cancer-associated fibroblasts in the extracellular matrix. Results show a good agreement with previous in-vitro results. Multiple myeloma growth and migration are shown to correlate linearly to the IGF-1 stimuli. These stimuli are coupled with the mechanical environment, which also improves cell growth. Moreover, cell migration depends on the fiber and VEGF concentration in the extracellular matrix. Finally, our computational model shows myeloma cells trigger mesenchymal stem cells to differentiate into cancer-associated fibroblasts, in a dose-dependent manner. info:eu-repo/grantAgreement/ES/DGA-FSE/T24-20R info:eu-repo/grantAgreement/ES/MICINN/PID2019-106099RB-C44 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 Mousavi, S. Jamaleddin Avril, Stephane Doweidar, Mohamed H. Universidad de Zaragoza (orcid)0000-0003-0088-7222 5004 605 Universidad de Zaragoza Dpto. Ingeniería Mecánica Área Mec.Med.Cont. y Teor.Est. 153 (2023), 106458 [13 pp.] Comput. biol. med. Computers in biology and medicine 0010-4825 9265177 http://zaguan.unizar.es/record/121404/files/texto_completo.pdf Versión publicada 2486078 http://zaguan.unizar.es/record/121404/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:121404 articulos driver 2024-11-22-11:57:57 ARTICLE