Dataset used in research paper entitled “Design of a Magnetic Nanoplatform Based on CD26 Targeting and HSP90 Inhibition for Apoptosis and Ferroptosis-Mediated Elimination of Senescent Cells”
Date
2025-01-13
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ACS Publications
Abstract
The accumulation of senescent cells, a hallmark of aging and age-related diseases, is also considered as a side effect of anticancer therapies, promoting drug resistance and leading to treatment failure. The use of senolytics, selective inducers of cell death in senescent cells, is a promising pharmacological antiaging and anticancer approach. However, more studies are needed to overcome the limitations of first-generation senolytics by the design of targeted senolytics and nanosenolytics and the validation of their usefulness in biological systems. In the present study, we have designed a nanoplatform composed of iron oxide nanoparticles functionalized with an antibody against a cell surface marker of senescent cells (CD26), and loaded with the senolytic drug HSP90 inhibitor 17-DMAG (MNP@CD26@17D). We have documented its action against oxidative stress-induced senescent human fibroblasts, WI-38 and BJ cells, and anticancer drug-induced senescent cutaneous squamous cell carcinoma A431 cells, demonstrating for the first time that CD26 is a valid marker of senescence in cancer cells. A dual response to MNP@CD26@17D stimulation in senescent cells was revealed, namely, apoptosis-based early response (2 h treatment) and ferroptosis-based late response (24 h treatment). MNP@CD26@17D-mediated ferroptosis might be executed by ferritinophagy as judged by elevated levels of the ferritinophagy marker NCOA4 and a decreased pool of ferritin. As 24 h treatment with MNP@CD26@17D did not induce hemolysis in human erythrocytes in vitro, this newly designed nanoplatform could be considered as an optimal multifunctional tool to target and eliminate senescent cells of skin origin, overcoming their apoptosis resistance.
Description
The data presented in this study are available in the Supporting Information at https://pubs.acs.org/doi/10.1021/acsbiomaterials.4c00771
(Figure S1) Analysis of gene mutations in the functional group of surface receptors in A431 cells; (Figure S2) hysteresis curve for MNP@PMAO at 5 and 300 K; (Table S1) magnetic properties of MNP@PMAO nanoparticles; (Figure S3) TGA curves of the MNP@OA and MNP@PMAO; (Figure S4) FTIR spectra of MNP@OA and MNP@PMAO samples; (Section S1) theoretical estimation of the amount of streptavidin-conjugated on the MNP surface; (Figure S5) oxygen uptake curves of methyl linoleate emulsion with addition of MNPs/17D at 37 °C; (Table S2) rate of oxidation of LinMe (2.74 mM) in Triton-X micelles (8 mM) in PBS pH = 7.4 containing 10 mM AAPH (ABAP) with and without (blank) addition of MNPs/17D at 37 °C; (Figure S6) analysis of hemocompatibility of MNP@CD26@17D; (Figure S7) analysis of apoptosis parameters upon 17-DMAG, MNP@CD26, and MNP@CD26@17D treatment for 24 h in oxidant-induced senescent WI-38 and BJ fibroblasts; analysis of FOXO3a and ACSL4 levels in oxidant-induced senescent BJ cells upon 17-DMAG, MNP@CD26, and MNP@CD26@17D treatment for 2 and 6 h; analysis of transferrin receptor (CD71, hTfR1, TfR) levels in drug-induced senescent skin cancer A431 cells and the correlation between the levels of CD71 and senescence-associated beta-galactosidase activity; (Figure S8) analysis of gene mutations within selected functional gene groups relevant to responses to anticancer drugs such as apoptosis, autophagy, and oxidative stress; analysis of gene mutation types within apoptosis functional group of genes; (Figure S9) analysis of gene mutation types within oxidative stress functional group of genes; (Figure S10) analysis of gene mutation types within the iron metabolism functional group of genes and list of the mutated gene set in A431 skin cancer cell line (genes related to autophagy, ferroptosis, necroptosis, apoptosis, oxidative stress, cancer, surface receptors, and iron metabolism) (ZIP)
Dataset 1: Additional original data used to generate the results in the main text and in the Supporting Information files.
Keywords
CD26, HSP90 inhibitor, drug-induced senescence, iron oxide nanoparticles, senolysis, skin cells
Related publications
Wnuk M, Del Sol-Fernández S, Błoniarz D, Słaby J, Szmatoła T, Żebrowski M, Martínez-Vicente P, Litwinienko G, Moros M, Lewińska A. Design of a Magnetic Nanoplatform Based on CD26 Targeting and HSP90 Inhibition for Apoptosis and Ferroptosis-Mediated Elimination of Senescent Cells. ACS Biomater Sci Eng. 2025 Jan 13;11(1):280-297. doi: 10.1021/acsbiomaterials.4c00771. Epub 2024 Dec 4. PMID: 39631769; PMCID: PMC11733919.
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Attribution 4.0 International
Research funding institutions
This work was supported by the National Science Centre (NCN, Poland) within M-ERA.NET 3 Call 2022 grant no. 2022/04/Y/ST5/00155 and PCI2023-143448 funded by MICIU/AEI/10.13039/501100011033 and cofunded by the European Union. Maria Moros acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement no. 853468) and MCIN/AEI/10.13039/501100011033 and FSE+ (PID2021-122508NB-I00). S.D.S.-F. acknowledges financial support thanks to Marie Skłodowska-Curie Postdoctoral Fellowships (HORIZON-MSCA-2021-PF-01-01, grant agreement no. 101064735) funded by the European Union. The authors would like to acknowledge Fondo Social del Gobierno de Aragón (grupo DGA E15_23R), the use of Advanced Microscopy Laboratory (Universidad de Zaragoza), for access to their instrumentation and expertise, and the use of the Servicio General de Apoyo a la Investigación-SAI, Universidad de Zaragoza. The preliminary data that were helpful in the development of the research concept were obtained during a scientific stay of A.L. and M.W. in the Bionanosurf lab (Instituto de Nanociencia y Materiales de Aragón, Zaragoza, Spain). This article was also supported by the Polish National Agency for Academic Exchange under the NAWA STER programme - Internationalisation of Doctoral Schools No BPI/STE/2023/1/00001/DEC/01 to Julia Słaby (Open Access fee).
Type
raw dataset