000144627 001__ 144627
000144627 005__ 20240829125213.0
000144627 0247_ $$2doi$$a10.1016/j.cmpb.2024.108331
000144627 0248_ $$2sideral$$a139435
000144627 037__ $$aART-2024-139435
000144627 041__ $$aeng
000144627 100__ $$aCamacho-Gómez, Daniel$$uUniversidad de Zaragoza
000144627 245__ $$aAn agent-based method to estimate 3D cell migration trajectories from 2D measurements: Quantifying and comparing T vs CAR-T 3D cell migration
000144627 260__ $$c2024
000144627 5060_ $$aAccess copy available to the general public$$fUnrestricted
000144627 5203_ $$aBackground and objective: Immune cell migration is one of the key features that enable immune cells to find invading pathogens, control tissue damage, and eliminate primary developing tumors. Chimeric antigen receptor (CAR) T-cell therapy is a novel strategy in the battle against various cancers. It has been successful in treating hematological tumors, yet it still faces many challenges in the case of solid tumors. In this work, we evaluate the three-dimensional (3D) migration capacity of T and CAR-T cells within dense collagen-based hydrogels. Quantifying three-dimensional (3D) cell migration requires microscopy techniques that may not be readily accessible. Thus, we introduce a straightforward mathematical model designed to infer 3D trajectories of cells from two-dimensional (2D) cell trajectories.
Methods: We develop a 3D agent-based model (ABM) that simulates the temporal changes in the direction of migration with an inverse transform sampling method. Then, we propose an optimization procedure to accurately orient cell migration over time to reproduce cell migration from 2D experimental cell trajectories. With this model, we simulate cell migration assays of T and CAR-T cells in microfluidic devices conducted under hydrogels with different concentrations of type I collagen and validate our 3D cell migration predictions with light-sheet microscopy.
Results: Our findings indicate that CAR-T cell migration is more sensitive to collagen concentration increases than T cells, resulting in a more pronounced reduction in their invasiveness. Moreover, our computational model reveals significant differences in 3D movement patterns between T and CAR-T cells. T cells exhibit migratory behavior in 3D whereas that CAR-T cells predominantly move within the plane, with limited movement in the direction. However, upon the introduction of a CXCL12 chemical gradient, CAR-T cells present migration patterns that closely resemble those of T cells.
Conclusions: This framework demonstrates that 2D projections of 3D trajectories may not accurately represent real migration patterns. Moreover, it offers a tool to estimate 3D migration patterns from 2D experimental data, which can be easily obtained with automatic quantification algorithms. This approach helps reduce the need for sophisticated and expensive microscopy equipment required in laboratories, as well as the computational burden involved in producing and analyzing 3D experimental data.
000144627 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2020-113963RB-I00$$9info:eu-repo/grantAgreement/ES/DGA/B29-20R$$9info:eu-repo/grantAgreement/EC/H2020/101018587/EU/Individual and Collective Migration of the Immune Cellular System/ICoMICS$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 101018587-ICoMICS$$9info:eu-repo/grantAgreement/ES/ISCIII/CB21-13-00087$$9info:eu-repo/grantAgreement/ES/ISCIII/FORT23-00028$$9info:eu-repo/grantAgreement/ES/MICINN/PLEC2021-007709/AEI/10.13039/501100011033
000144627 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000144627 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000144627 700__ $$0(orcid)0000-0002-0163-8378$$aMovilla, Nieves
000144627 700__ $$0(orcid)0000-0002-3784-1140$$aBorau, Carlos
000144627 700__ $$aMartín, Alejandro$$uUniversidad de Zaragoza
000144627 700__ $$aOñate Salafranca, Carmen
000144627 700__ $$0(orcid)0000-0003-0154-0730$$aPardo, Julián$$uUniversidad de Zaragoza
000144627 700__ $$0(orcid)0000-0002-1878-8997$$aGómez-Benito, María José$$uUniversidad de Zaragoza
000144627 700__ $$0(orcid)0000-0002-9864-7683$$aGarcía-Aznar, José Manuel$$uUniversidad de Zaragoza
000144627 7102_ $$11011$$2566$$aUniversidad de Zaragoza$$bDpto. Microb.Ped.Radio.Sal.Pú.$$cÁrea Inmunología
000144627 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000144627 773__ $$g255 (2024), 108331 [9 pp.]$$pComput. methods programs biomed.$$tComputer Methods and Programs in Biomedicine$$x0169-2607
000144627 8564_ $$s11038753$$uhttps://zaguan.unizar.es/record/144627/files/texto_completo.pdf$$yVersión publicada
000144627 8564_ $$s2125561$$uhttps://zaguan.unizar.es/record/144627/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000144627 909CO $$ooai:zaguan.unizar.es:144627$$particulos$$pdriver
000144627 951__ $$a2024-08-29-10:46:04
000144627 980__ $$aARTICLE