000109410 001__ 109410
000109410 005__ 20240319080948.0
000109410 0247_ $$2doi$$a10.1115/1.4053143
000109410 0248_ $$2sideral$$a125420
000109410 037__ $$aART-2022-125420
000109410 041__ $$aeng
000109410 100__ $$0(orcid)0000-0003-2237-8859$$aJuste-Lanas, Yago$$uUniversidad de Zaragoza
000109410 245__ $$aConfined cell migration and asymmetric hydraulic environments to evaluate the metastatic potential of cancer cells
000109410 260__ $$c2022
000109410 5060_ $$aAccess copy available to the general public$$fUnrestricted
000109410 5203_ $$aMetastasis, a hallmark of cancer development, is also the leading reason for most cancer-related deaths. Furthermore, cancer cells are highly adaptable to microenvironments and can migrate along pre-existing channel-like tracks of anatomical structures. However, more representative three-dimensional models are required to reproduce the heterogeneity of metastatic cell migration in vivo to further understand the metastasis mechanism and develop novel therapeutic strategies against it. Here, we designed and fabricated different microfluidic-based devices that recreate confined migration and diverse environments with asymmetric hydraulic resistances. Our results show different migratory potential between metastatic and nonmetastatic cancer cells in confined environments. Moreover, although nonmetastatic cells have not been tested against barotaxis due to their low migration capacity, metastatic cells present an enhanced preference to migrate through the lowest resistance path, being sensitive to barotaxis. This device, approaching the study of metastasis capability based on confined cell migration and barotactic cell decisions, may pave the way for the implementation of such technology to determine and screen the metastatic potential of certain cancer cells.
000109410 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FEDER/RIS3-LMP74-18$$9info:eu-repo/grantAgreement/EC/H2020/826494/EU/PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers/PRIMAGE$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 826494-PRIMAGE$$9info:eu-repo/grantAgreement/ES/MCIU/FPU17-03867$$9info:eu-repo/grantAgreement/ES/MICINN/RTI2018-094494-B-C21
000109410 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000109410 590__ $$a1.7$$b2022
000109410 592__ $$a0.45$$b2022
000109410 591__ $$aENGINEERING, BIOMEDICAL$$b81 / 96 = 0.844$$c2022$$dQ4$$eT3
000109410 593__ $$aPhysiology (medical)$$c2022$$dQ3
000109410 591__ $$aBIOPHYSICS$$b56 / 70 = 0.8$$c2022$$dQ4$$eT3
000109410 593__ $$aBiomedical Engineering$$c2022$$dQ3
000109410 594__ $$a3.2$$b2022
000109410 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000109410 700__ $$0(orcid)0000-0003-2612-9235$$aGuerrero, Pedro E.$$uUniversidad de Zaragoza
000109410 700__ $$aCamacho-Gomez, Daniel$$uUniversidad de Zaragoza
000109410 700__ $$0(orcid)0000-0001-8324-5596$$aHervas-Raluy, Silvia$$uUniversidad de Zaragoza
000109410 700__ $$0(orcid)0000-0002-9864-7683$$aGarcía-Aznar, J.M.$$uUniversidad de Zaragoza
000109410 700__ $$0(orcid)0000-0002-1878-8997$$aGómez-Benito, María José$$uUniversidad de Zaragoza
000109410 7102_ $$11002$$2050$$aUniversidad de Zaragoza$$bDpto. Bioq.Biolog.Mol. Celular$$cÁrea Biología Celular
000109410 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000109410 773__ $$g144, 7 (2022), 074502 [29 pp.]$$pJ. biomech. eng.$$tJOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME$$x0148-0731
000109410 8564_ $$s2985472$$uhttps://zaguan.unizar.es/record/109410/files/texto_completo.pdf$$yPostprint
000109410 8564_ $$s1949326$$uhttps://zaguan.unizar.es/record/109410/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000109410 909CO $$ooai:zaguan.unizar.es:109410$$particulos$$pdriver
000109410 951__ $$a2024-03-18-12:46:55
000109410 980__ $$aARTICLE