A New Model of Sensorial Neuron-Like Cells for HTS of Novel Analgesics for Neuropathic Pain

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Farmacoloxía, Farmacia e Tecnoloxía Farmacéutica
dc.contributor.affiliationUniversidade de Santiago de Compostela. Centro de Investigación en Medicina Molecular e Enfermidades Crónicas (CiMUS)
dc.contributor.authorMartínez Rodríguez, Antón Leandro
dc.contributor.authorBrea Floriani, José Manuel
dc.contributor.authorMonroy, Xavier
dc.contributor.authorMerlos, Manuel
dc.contributor.authorBurgueño, Javier
dc.contributor.authorLoza García, María Isabel
dc.date.accessioned2026-01-28T11:01:45Z
dc.date.available2026-01-28T11:01:45Z
dc.date.issued2019-02
dc.description.abstractIn this study we developed a new translational phenotypic in vitro model for high-throughput screening (HTS) of novel analgesics for treating neuropathic pain, in order to address the poor translation of traditional recombinant models. The immortalized dorsal root ganglia (DRG) neuron-like F11 cell line was selected based on its phenotype after differentiation. The acquisition of neuronal characteristics was evaluated by measuring the expression of TrkA as a DRG neuron marker (p < 0.01) as well as by measuring the global neurite length (p < 0.001). The response of F11 cells to ATP and KCl was obtained by measuring intracellular calcium concentration, dynamic mass redistribution, and membrane potential. A KCl-induced increase of intracellular calcium levels was chosen as the readout because of the better signal quality, higher reproducibility, and greater compatibility with HTS assay requirements compared with other methods. The response to KCl differed significantly between differentiated and undifferentiated cells (p < 0.05), with an EC50 value of 5 mM in differentiated cells. The model was validated by screening the Prestwick Chemical Library. Five hits already proposed for neuropathic-related pain were identified, with IC50 values between 1 and 7 µM. This cell model provides a new tool for screening novel analgesics for the relief of neuropathic pain.
dc.description.peerreviewedSI
dc.description.sponsorshipThis work was supported by the Joint R&D Unit Esteve-USC (IN853A-2014-08), co-financed by the Galician Innovation Agency and the Spanish Ministry of Economy and Competitiveness (MINECO) within the framework of the Spanish Strategy of Innovation in Galicia; and by the Phenopain project (RTC-2015-4207-1) of the RETOS-COLABORACIÓN program of the MINECO, co-financed by the European Union through the European Regional Development Fund (ERDF). A. L. Martínez-Rodríguez was in receipt of a predoctoral fellowship from the FPU program (Spanish Ministry of Education, Culture and Sports).
dc.identifier.citationSLAS Discovery Volume 24, Issue 2, February 2019, Pages 158-168
dc.identifier.doi10.1177/2472555218810323
dc.identifier.urihttps://hdl.handle.net/10347/45525
dc.journal.titleSLAS Discovery
dc.language.isoeng
dc.publisherElsevier
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Programa Estatal de I+D+I Orientada a los Retos de la Sociedad/RTC-2015-4207-1Q1518001AGALICIA/ES/Desarrollo de Modelos Fenotípicos In Vitro de Dolor y su Aplicación al Cribado de Compuestos de Alto Rendimiento (High-Throughput Screening)
dc.relation.publisherversionhttps://doi.org/10.1177/2472555218810323
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectNeuropathic pain
dc.subjectF11 cells
dc.subjectDifferentiation
dc.subjectImmunofluorescence
dc.subjectNeuronal excitability
dc.subjectHTS
dc.titleA New Model of Sensorial Neuron-Like Cells for HTS of Novel Analgesics for Neuropathic Pain
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublicationefe7f464-2f77-4a92-915f-fda4128451fa
relation.isAuthorOfPublication67b19be7-64a8-45c8-a6e4-ed48a4410ef8
relation.isAuthorOfPublication7765cb9b-b630-44dc-9477-dd266a62bb3c
relation.isAuthorOfPublication.latestForDiscoveryefe7f464-2f77-4a92-915f-fda4128451fa

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