RT Journal Article
T1 Selective Anticancer Therapy Based on a HA-CD44 Interaction Inhibitor Loaded on Polymeric Nanoparticles.
A1 Espejo-Roman, Jose M
A1 Rubio-Ruiz, Belen
A1 Cano-Cortes, Victoria
A1 Cruz-Lopez, Olga
A1 Gonzalez-Resines, Saul
A1 Domene, Carmen
A1 Conejo-Garcia, Ana
A1 Sanchez-Martin, Rosario M
K1 anticancer therapy
K1 cluster of differentiation 44
K1 hyaluronic acid
K1 molecular dynamics simulations
K1 nanomedicine
K1 selective release
K1 tetrahydroisoquinoline
AB Hyaluronic acid (HA), through its interactions with the cluster of differentiation 44 (CD44), acts as a potent modulator of the tumor microenvironment, creating a wide range of extracellular stimuli for tumor growth, angiogenesis, invasion, and metastasis. An innovative antitumor treatment strategy based on the development of a nanodevice for selective release of an inhibitor of the HA-CD44 interaction is presented. Computational analysis was performed to evaluate the interaction of the designed tetrahydroisoquinoline-ketone derivative (JE22) with CD44 binding site. Cell viability, efficiency, and selectivity of drug release under acidic conditions together with CD44 binding capacity, effect on cell migration, and apoptotic activity were successfully evaluated. Remarkably, the conjugation of this CD44 inhibitor to the nanodevice generated a reduction of the dosis required to achieve a significant therapeutic effect.
PB MDPI AG
SN 1999-4923
YR 2022
FD 2022-04-01
LK http://hdl.handle.net/10668/21548
UL http://hdl.handle.net/10668/21548
LA en
NO Espejo-Román JM, Rubio-Ruiz B, Cano-Cortés V, Cruz-López O, Gonzalez-Resines S, Domene C, et al.  Selective Anticancer Therapy Based on a HA-CD44 Interaction Inhibitor Loaded on Polymeric Nanoparticles. Pharmaceutics. 2022 Apr 4;14(4):788.
NO This research was funded by the Consejería de Economía, Conocimiento, Empresas y Universidad of the Junta de Andalucía (grant number Excellence Research Project P18-RT-1679) and the Research Results Transfer Office (OTRI) of the University of Granada (grant number PR/17/006 project). This work was partially supported by grants from the Spanish Ministry of Economy and Competitiveness (MINECO), grant number PID2019.110987RB.I00; the Health Institute Carlos III (ISCIII), grant number DTS18/00121 the Junta de Andalucía-FEDER, Ministry of Economy, Knowledge, Companies, and University (FEDER 2018: ref. B-FQM-475-UGR18, PAIDI2020: ref. PT18-TP-4160); and the Andalusian Regional Government, grant number PAIDI-TC-PVT-PSETC-2.0. C.D. thanks HECBioSim, the UK High End Computing Consortium for Biomolecular Simulation (hecbiosim.ac.uk), which is supported by the EPSRC (EP/L000253/1) for awarding computing time in Jade, a UK Tier-2 resource. B.R.-R. gratefully acknowledges funding from the European Union’s Horizon 2020 Research and Innovation Program under Marie Sklodowska-Curie Grant Agreement no. 754446 and UGR Research and Knowledge Transfer Fund—Athenea3i. J.M.E.-R. thanks the Spanish Ministry of Education for PhD funding (scholarship FPU 16/02061). V.C.-C. thanks the Andalusian Regional Government for her postdoctoral fellowship (POSTDOC_21_00118).
DS RISalud
RD Apr 8, 2025