Computational modeling of multiple myeloma interactions with resident bone marrow cells

Urdeitx, Pau (Universidad de Zaragoza) ; Mousavi, S. Jamaleddin ; Avril, Stephane ; Doweidar, Mohamed H. (Universidad de Zaragoza)

Resumen: 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.

Idioma: Inglés

DOI: 10.1016/j.compbiomed.2022.106458

Año: 2023

Publicado en: Computers in biology and medicine 153 (2023), 106458 [13 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 / 65 = 0.031 (2023) - Q1 - T1
Categ. JCR: ENGINEERING, BIOMEDICAL rank: 16 / 122 = 0.131 (2023) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 18 / 169 = 0.107 (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/DGA-FSE/T24-20R
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2019-106099RB-C44

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)