https://orcid.org/0000-0001-8504-5926
Figures
Abstract
The immunomodulatory properties of exogenous mesenchymal stem cells (MSCs) have been the target of research in immune-mediated diseases and organ transplants. However, the altered microenvironment decrease MSCs capabilities and survival post-transplantation. This study investigated the viability, proliferation, gene expression and proteomic of canine adipose tissue-derived MSCs (cAT-MSCs) treated with deferroxyamine [DFO] (hypoxia), interferon-γ [IFN-γ] (inflammation) or both for 48h. At 24 hours, all groups exhibited fibroblastoid morphology and adhesion to plastic, with treated groups showing greater cell spacing. After 144h, cell proliferation did not differ significantly between groups, though the treated groups had higher cell concentrations compared to the control. Gene expression analysis revealed increased Casp9 expression in the IFN-γ group, in comparison to the IFN-γ + DFO group; the FGF2 gene was upregulated in the IFN-γ group, while the DKC1 and PT53 genes showed higher expression in IFN-γ than DFO. The VEGFA was more highly expressed in the groups treated with DFO. Proteomics analysis identified 256 proteins, with 70 co-expressed across all groups, and unique proteins in each treatment group: 41 in the control, 44 in DFO, 15 in IFN-γ + DFO group, and 34 for IFN-γ. Notably, 6, 5, and 4 proteins were unique to DFO, IFN-γ + DFO, and IFN-γ treatments, respectively, when compared to the control. Preconditioning modulated angiogenic and metabolic pathways, preserving immunomodulatory function and cellular integrity. Future studies with real hypoxia and multi-omics integration will be crucial for linking molecular signatures to paracrine functions and in vivo efficacy.
Citation: Ocampo-Ortiz P, Vallejo-Aristizabal V, Carvalho MG, Stuart JP, Dellaqua T, Landim e Alvarenga FdC (2026) Hypoxia- and inflammation-driven preconditioning modulates angiogenic and metabolic pathways in canine adipose-derived mesenchymal stem cells. PLoS One 21(3): e0345360. https://doi.org/10.1371/journal.pone.0345360
Editor: Nazmul Haque, TotiCell Limited, Bangladesh, BANGLADESH
Received: October 14, 2025; Accepted: March 4, 2026; Published: March 23, 2026
Copyright: © 2026 Ocampo-Ortiz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All proteomic mass spectrometry data files are available from the Mendeley database (DOI: 10.17632/gdg29rw3sr.1).
Funding: This study was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) – Brazil – Finance Code 001. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Abbreviation: Bcl2, B cell lymphoma 2; Casp3, Caspase 3; Casp8, Caspase 8; Casp9, Caspase 9; cAT-MSCs, canine adipose tissue-derived mesenchymal stem cells; DFO, Desferroxiamine; DKC1, Dyskerin 1; DNMT1, DNA methyltransferase 1; EGF, Epidermal growht factor; FGF-2, Fibroblastic growht factor 2; GAPDH, Glyceraldehyde-3-phosphate dehydrogenase; hBM-MSCs, Human bone marrow mesenchymal stem cells; HDAC1, Histone deacetylase 1; HGF, Hepatocyte growth factor; Hif1α, Hypoxia-inducible factor 1 alpha; IDO, Indoleamine 2, 3-dioxygenase; IL-10, Interleukin 10; IL-6, Interleukin 6; IFN-γ, Interferon gamma; iNOS, inducible nitric oxide synthase; ISCT, International Society for Cellular Therapy; MM, Maintenance medium; MMP2, Matrix metalloproteinase 2; MSCs, Mesenchymal stem cells; NK, Natural killer; RT- qPCR, quantitative reverse‐transcription polymerase chain reaction; PGE-2, Prostaglandin E2; VEGFA, Vascular endothelial growth factor A; TERT, Telomerase reverse transcriptase; TNFα, Tumor necrosis factor alpha; TP53, Tumor protein 53
Introduction
Mesenchymal stem cells (MSCs) stand out for their proliferation, multipotentiality, tropism, immunosuppression, and homing/migration [1–5]. By 2020, 1138 clinical trials using MSCs were registered on clinicaltrials.gov [6], positioning them as an alternative for the treatment of different clinical conditions in animals and humans [7–11]. However, efficacy is not universal, as it depends on the in vitro culture microenvironment and the clinical status of the recipient organism [11,12].
MSCs exert an immunomodulatory function at the injury site through bioactive factors that modulate the inflammatory reaction and tissue repair [13]. As clinical conditions often involve inflammatory and ischemic processes [14], the survival and function of MSCs may be affected: under hypoxia and low nutrient supply there are reports of apoptosis and autophagy [14–16], but increases in viability, proliferation, migration, differentiation, and paracrine secretions have also been described [17–19].
To potentiate beneficial effects, preconditioning under low oxygenation before transplantation has been proposed, reducing reactive oxygen species and stimulating pro-angiogenic and antiapoptotic factors [20–22]; “cytokine licensing” strategies, such as IFN-γ, are also used to reinforce immunomodulation and reduce rejection [19,23–25]. There are recent reviews systematizing these approaches [26,27], and evidence that IFN-γ increases the efficacy of MSC exosomes in infarction models [28].
Although well known, culture under hypoxia is expensive and difficult to standardize; thus, the use of mimetic agents has been proposed to stabilize culture conditions, such as deferoxamine (DFO) for hypoxia and IFN-γ for inflammation [29,30]. In dogs, preconditioning with DFO has already been shown to reprogram macrophages to an M2 phenotype via extracellular vesicles [31].
There is ample evidence of the effect of IFN-γ on immunomodulation and of the benefits of hypoxic preconditioning in ischemic lesions (myocardial infarction, renal failure, spinal cord injury, disc disease, periodontal defect, and skin wounds) [23,24,30,32–38]. Few controlled studies combine hypoxia and inflammation in domestic animals, especially in dogs [39].
Thus, we hypothesized that the use of the hypoxia mimetic DFO, with or without IFN-γ, will influence the survival, proliferation, gene expression, and protein profile of canine MSCs, in comparison with IFN-γ alone and with control conditions. The objective is to understand the immunosuppressive and regenerative abilities of canine adipose tissue MSCs exposed to DFO and/or IFN-γ, by means of proliferation, viability, gene expression, and proteomic assays.
Materials and methods
Reagents and protocols
All reagents used in the study were of high purity grade and were purchased from Thermo Fisher Scientific. Otherwise, they were cited. The protocols referenced in the study were developed by the Laboratory of Cell Therapy and Advanced Reproduction (LANÇA, School of Veterinary Medicine and Animal Science, UNESP, Botucatu, Brazil).
Ethical aspects
The study was conducted according to ethical principles in animal experimentation, in accordance with the Brazilian Society for Laboratory Animal Science (SBCAL), and all procedures were approved by the Ethics Committee on the Use of Animals (CEUA) of the School of Veterinary Medicine and Animal Science, UNESP, Botucatu, Brazil, under protocol 0026/2020.
Isolation and characterization of MSCs
Samples of adipose tissue were obtained from 6 healthy mixed-breed female dogs under 3 years of age and with a medical history free of previous diseases, submitted to elective ovariohysterectomy. As an inclusion criterion in the study, the bitches presented negative PCR for canine adenovirus type I, Babesia spp., Ehrlichia spp., Leptospira spp., Toxoplasma gondii, canine distemper virus, and Mycoplasma spp. The MSCs were maintained in liquid nitrogen at −196 °C in the cell bank of the Laboratory of Cell Therapy and Advanced Reproduction (LANÇA, School of Veterinary Medicine and Animal Science, UNESP, Botucatu, Brazil). All samples were previously characterized according to the standards of the International Society for Cellular Therapy, presenting plastic adherence during culture, fibroblast-like morphology, positive labeling for the membrane markers CD44 (abD Serotec, USA) and CD90 (Becton Dickinson and Company, USA), and negative for the membrane marker CD34 (abD Serotec, USA) and low labeling (< 5%) of the MHCII marker (abD Serotec, USA).
Samples were thawed according to Chaytor (Chaytor et al., 2012). Cells were rapidly thawed at 37 °C under gentle agitation until a small portion of ice remained. Then, the samples were transferred to centrifuge tubes previously prepared with 3 mL of maintenance medium (DMEM/F-12 (code no. 31600034/21700018) supplemented with 20% fetal bovine serum (code no. 12657029), 1% Pen-Strep (code no. 15140122), and 1% Fungizone (code no. 15290026)) at 37 °C, and kept at the same temperature for 3 minutes. Next, a further 9 mL of maintenance medium were added, totaling 12 mL (maintenance medium and thawed cells). The cells were centrifuged at 580 g/10 minutes and assessed for viability with Trypan Blue (Sigma-Aldrich Inc. St. Louis, MO, USA).
Cells (25,000 viable cells/cm²) were seeded in culture flasks for reculture and maintained in DMEM/F12 supplemented with 20% fetal bovine serum, 1% Pen-Strep, and 1% Fungizone and incubated at 37.5 °C, with 5% CO₂ in air and 100% humidity for 24 hours to ensure adherence to the flasks. Then the medium was discarded, and the flasks were washed (3×) with PBS (code no. 70011044). Next, the media and culture conditions were modified according to the experimental groups in a completely randomized design.
MSC culture and groups
The conditions of hypoxia and inflammation were mimicked using DFO (code no. D9533, Sigma-Aldrich, Saint Louis, MO, USA) and IFN-γ (code no. I3275, Sigma-Aldrich, Saint Louis, MO, USA), respectively, in DMEM/F12 culture medium (code no. 31600034/21700018) without the addition of fetal bovine serum, phenol red, and HEPES, to avoid interferences in subsequent analyses. Only flasks containing 80% cellular confluence were subjected to the different in vitro culture conditions. In the control group, the cells were maintained in base medium (DMEM/F-12 containing 1% Pen-Strep and 1% Fungizone). The DFO group comprised cells maintained in base medium plus 50 µmol DFO. In the IFN-γ group, the cells were maintained in base medium containing 50 ng/mL IFN-γ. In the IFN-γ + DFO group, the cells were maintained in base medium containing 50 µmol DFO and 50 ng/mL IFN-γ. In all groups, cultures were conducted in an incubator at 37.5 °C, with 5% CO₂ in air and 100% humidity for 48 hours (Fig 1).
Cell proliferation test
Cell proliferation was evaluated in samples obtained from 6 animals. For each animal, a total of 1 × 10⁴ cells/well were cultured in 4 six-well plates for 144 hours. The 4 plates for each animal represented the 4 experimental groups cultured under the conditions mentioned above. Every 48 hours of culture, trypsinization, counting, and determination of cell viability of one well/group were performed using Trypan blue exclusion staining (code no. T8154, Sigma-Aldrich, Saint Louis, MO, USA) in a Neubauer chamber. The data obtained were entered into a growth curve in data analysis software.
Annexin V viability assay
Cell viability was assessed by the method that evaluates Annexin V binding (eBioscience™ Annexin V-FITC Apoptosis Detection Kit. Life Technologies, Carlsbad, CA, USA) to phospholipids, exposing it on the surface of cells in the early stages of apoptosis. Propidium iodide was associated with Annexin V in order to identify necrotic cells. For the analysis, samples collected from 6 animals were used. After 48 hours of culture under the different experimental conditions (Fig 1) and removal of the medium conditioned by the MSCs, the culture flasks were washed with PBS and treated with the dissociation enzyme TrypLE (code no. 12563029, Life Technologies, Carlsbad, CA, USA) for 10 minutes at 37 °C. After this period, the content of the flask was placed into a 50 mL plastic tube containing 15 mL of culture medium supplemented with 20% fetal bovine serum to neutralize the enzymatic effect. The samples were washed 3 times by centrifugation for 10 minutes at 400 g and prepared according to the manufacturer’s recommendations. Briefly, 1 × 10⁶ cells/mL were resuspended in a labeling solution containing 5 µL of Annexin V and 10 µL of propidium iodide. Then, the samples were incubated for 15 minutes at 37 °C and analyzed on a FACSCalibur flow cytometer (Becton Dickinson® and Company, USA).
The results obtained were expressed as the percentage of the population of live, necrotic, or apoptotic cells. Live cells show no labeling. Cells in apoptosis show positive labeling for Annexin V and negative for propidium iodide (early apoptosis) or positive for Annexin V and positive for propidium iodide (late apoptosis). Necrotic cells show negative labeling for Annexin V and positive for propidium iodide.
Real-time quantitative PCR (RT-qPCR)
The investigation of the global mRNA expression patterns of MSCs collected after 48 hours of cell culture (Fig 1) was performed by RT-qPCR, using the Sybr Green™ PCR Master Mix system (Applied Biosystems™) on the StepOnePlus™ System (Applied Biosystems™). Briefly, cells from the different groups were subjected to extraction and purification of total RNA with TRIzol® (Life Technologies Corporation, Carlsbad, CA, USA) and the concentrations of total RNA were measured (NanoDrop™ 2000 Spectrophotometers, Thermo Scientific™). Next, total RNA was treated with DNase (Qiagen®) according to the manufacturer’s protocol to eliminate contamination with genomic DNA. Subsequently, the transcription of RNA into cDNA was performed using the reverse transcription kit (High-Capacity cDNA Reverse Transcription Kit, Applied Biosystems™ Thermo Fisher Scientific), following the incubation steps according to the manufacturer’s recommended times and temperatures.
The final PCR mix volume was 20 µL, in duplicate, and the cycling conditions were: 95 °C for 10 min (1 cycle), denaturation at 95 °C for 15 s followed by annealing at 60 °C for 1 min (40 cycles). The raw fluorescence data (baseline-uncorrected data) obtained at the end of the PCR were submitted to the LinRegPCR program [40] for baseline correction and obtaining threshold cycle (Ct) values. The relative abundance of target genes was calculated by the 2-ΔΔCt method. GAPDH (glyceraldehyde-3-phosphate dehydrogenase) was used as a reference for data normalization, as described by PFAFFL (2001) [6]. Table 1 describes the panel of target genes used for gene expression analysis in cAT-MSCs.
Proteomic analysis
At the end of the culture period, cell samples were washed 3× with phosphate-buffered saline (PBS), centrifuged for 10 minutes at 800 × g, and the resulting pellet was cryopreserved at −80 °C in modified radioimmunoprecipitation assay (RIPA) buffer [48] containing protease inhibitors (150 mmol NaCl, 1% Triton X-100, 1% sodium deoxycholate, 0.1% sodium dodecyl sulfate, 0.8 mmol EDTA, 1.0 μg/mL aprotinin, 1.0 μg/mL leupeptin, and 35.0 μg/mL PMSF in 50 mmol Tris-HCl pH 7.2). Samples were sonicated in an ice bath [49,50] and centrifuged at 10,000 × g for 30 minutes at 4 °C, and the supernatant was removed. Total protein concentration was determined by measuring A280 absorbance using a spectrophotometer (NanoDrop™ 2000, Thermo Fisher Scientific™, São Paulo, São Paulo, Brazil).
An aliquot of 30 μg of proteins per sample was prepared for electrophoresis in a 12% polyacrylamide gel. After the sample entered the separation gel, the run was stopped, and the gel was stained with colloidal Coomassie G-250 [51,52]. The stained fragments were excised, and tryptic digestion of the peptides was performed.
Samples were digested in-gel using the method reported by Shevchenko et al. (1996) [53] with modifications. For destaining, 50% methanol and 2.5% acetic acid in purified water were used (4x). Dehydration was performed with 100% acetonitrile. Reduction was carried out with dithiothreitol (DTT) (Bio-Rad, Lagoa Santa, SP, BR), followed by alkylation with iodoacetamide (Bio-Rad, Santo Amaro, MG, BR). Overnight, samples were digested with trypsin 20 ng/μL, at a 1:50 trypsin/substrate ratio. For extraction, 5% formic acid was used. Samples were concentrated (SPD1010 Integrated SpeedVac Systems, Thermo Fisher Scientific Inc., Waltham, MA) and cryopreserved at −80 °C for subsequent mass spectrometry (MS) analysis.
For MS analysis, samples were thawed, diluted to 0.7 μg protein/μL with 0.1% formic acid, homogenized, and centrifuged at 1,100 × g for 5 minutes. Next, 15 μL of the supernatant were deposited into specific tubes (clear glass 12 × 32 mm screw-neck total recovery vial with cap, Waters Corporation, Milford, MA).
An aliquot of 4.5 μL obtained from the peptide digestion was separated on a C18 chromatography column (100 μm × 100 mm) of RP-nano ultra performance liquid chromatography (UPLC) (Waters nanoACQUITY UPLC, Waters Corporation, Milford, MA) coupled for detection to a mass spectrometer with a hybrid quadrupole time-of-flight (QToF) analyzer (Micromass Q-ToF PREMIER mass spectrometer, Waters Corporation, Milford, MA) with nanoelectrospray ionization at a rate of 0.600 μL/min. An acetonitrile gradient (2–90%) in 0.1% formic acid was maintained for 45 min. The ionization voltage was kept at 3.5 kV, a cone voltage of 30 V, and a source temperature of 100 °C. The equipment was operated during the first three minutes, where the mass spectrum was recorded by MS/MS of the three most intense peaks detected. After tandem MS (MS/MS) fragmentation, the ion was retained on the exclusion list for 60 s, and the current exclusion time was used to analyze endogenous peptide cleavage.
Search parameters included trypsin as a protease, with a maximum allowed missed cleavage of 1, cysteine carbamidomethylation as a fixed modification, and methionine oxidation as a variable modification; a tolerance of 1 Da for precursor ions (MS) and fragments (MS/MS), and a monoisotopic molecular mass.
Spectra were acquired using MassLynx v.4.1 software (Waters Corporation, Milford, MA), and the raw data files were converted to a peak-list format (.mgf, mascot generic format) without adding the scans and searched against the UniprotSProt 10116 database (http://www.uniprot.org/) for the taxonomy Canis lupus familiaris using Mascot version 2.3.02 and Mascot Distiller MDRO version 2.4.0.0 (Matrix Science Inc., Boston, MA). The proteomic mass spectrometry data were deposited in Mendeley Data (https://doi.org/10.17632/gdg29rw3sr.1) through the repository with the data-set identifier in xml format. The results were submitted to ProteinPilot Software 4.0 (AB Sciex, Framingham) for data-set analysis to validate MS/MS-based peptides and to identify proteins. After protein identification, the data were entered into the UniProtKB (www.uniprot.org.br) and ShinyGO 0.85 (https://bioinformatics.sdstate.edu/go/) databases to obtain gene ontology (GO) annotations using the molecular function and biological process categories (S2 and S3 Fig).
The relative quantification of each protein in the mixture was determined by calculating the exponentially modified protein abundance index (emPAI) with Mascot Distiller software.
Analysis of results
All analyses except the proteomic analysis were performed using JMP statistical software (SAS Institute, Cary, NC, USA). For the different variables, the Shapiro–Wilk or Kolmogorov–Smirnov tests were implemented to verify normality and Mauchly’s test to verify sphericity. Cell proliferation in the different groups at 4 different times was analyzed by two-way repeated-measures ANOVA, with Sidak as the post hoc test. For the cell viability variable with Annexin, one-way ANOVA was performed without obtaining statistical difference. The means of the effects of IFN-γ, IFN-γ + DFO, and DFO on the relative abundance of mRNA in canine cAT-MSCs were compared with the Tukey–Kramer test (parametric data) or Kruskal–Wallis (non-parametric data). Data are presented as means ± SEM, and differences were considered significant when p ≤ 0.05. Graphs were prepared using the GraphPad Prism 9 statistical package.
For proteomics, the emPAI values obtained from MS were normalized, and proteins that were not identified in 50% of the samples of each group were excluded. To reduce outlier effects, the emPAI value of each sample was divided by the sum of the emPAI of all samples in the groups; the result was used for statistical analysis. Data processing was performed between groups (DFO, IFN-γ + DFO, and IFN-γ) separately versus the control group, by means of a non-hierarchical clustering analysis using MetaboAnalyst 6.0 software to confirm group separations based on protein abundance. Multivariate analysis (principal component analysis—PCA) was used to characterize variation among samples in the score matrix. The heatmap was constructed for visual comparison of proteins across groups. The t-test was used to determine differences between groups (P < 0.05). As a post-hoc test, Fisher’s LSD was applied. Values were considered significant when the false discovery rate (FDR) was below 0.05.
Results
Cellular morphology
At 48 hours of culture, the cells of all groups showed fibroblast-like morphology (Fig 2) and cells were adherent to plastic.
Cell proliferation test
cAT-MSCs from all groups showed a reduction in cell concentration during the first 96 hours of culture, followed by stabilization up to 144 hours. However, no significant differences were observed among groups over time (p ≤ 0.05), as illustrated in Fig 3.
Data represent means of cells harvested from 6 animals (p ≤ 0.05).
Annexin V viability assay
Cell viability remained above 90% in every group. Cells in early apoptosis, late apoptosis, and necrosis represented less than 10% of the cells evaluated in the groups. There were no differences among the parameters evaluated when comparing the experimental groups (p ≤ 0.05) (Fig 4).
Real-time quantitative reverse transcriptase-PCR
The significant effects of IFN-γ and DFO alone and combined on gene expression of canine MSCs were represented (Figs 5–10). Supporting information shows the totality of the genes evaluated (S1 Fig).
Bars represent relative mean values normalized to the reference gene GAPDH and standard error of the mean (┬ and ┴). Means denoted by a different letter indicate statistically significant differences among treatments (p < 0.05).
Bars represent relative mean values normalized to the reference gene GAPDH and standard error of the mean (┬ and ┴). Means denoted by a different letter indicate statistically significant differences among treatments (p < 0.05).
Bars represent relative mean values normalized to the reference gene GAPDH and standard error of the mean (┬ and ┴). Means denoted by a different letter indicate statistically significant differences among treatments (p < 0.05).
Bars represent relative mean values normalized to the reference gene GAPDH and standard error of the mean (┬ and ┴). Means denoted by a different letter indicate statistically significant differences among treatments (p < 0.05).
Bars represent relative mean values normalized to the reference gene GAPDH and standard error of the mean (┬ and ┴). Means denoted by a different letter indicate statistically significant differences among treatments (p < 0.05).
Bars represent relative mean values normalized to the reference gene GAPDH and standard error of the mean (┬ and ┴). Means denoted by a different letter indicate statistically significant differences among treatments (p < 0.05).
With respect to apoptosis, expression of the genes BCL2 and CASP8 did not differ among groups (p > 0.05). However, the combination of IFN-γ with DFO, as well as treatment with DFO alone, resulted in reduced expression of CASP9 (p = 0.0052), whereas the group treated with IFN-γ alone showed no significant difference relative to the control (Fig 5). Regarding genes related to cell survival, HDAC1 and DNMT1 showed no differences among groups (p > 0.05). Treatments, whether alone or combined, did not differ from the control in the expression of DKC1. However, expression of this gene was significantly lower in the group treated with DFO alone compared with the group treated with IFN-γ alone (p = 0.0250) (Fig 6). In relation to immunoregulatory genes (HGF, IDO, PGE2, and IL-6), no significant differences were observed among groups (p > 0.05). With respect to proliferation and differentiation, expression of FGF2 did not differ from the control among groups; only expression of this gene was significantly lower in the group treated with DFO alone compared with the group treated with IFN-γ alone (p = 0.0416) (Fig 7). Regarding genes related to angiogenesis, MMP2 showed no significant variation, whereas VEGFA had increased expression in the groups treated with DFO alone and with IFN-γ combined with DFO (p = 0.0017) (Fig 8). Among genes associated with the cell cycle, Cyclin-D1 showed no significant change, and TP53, although without a difference relative to the control, showed a difference between the groups treated with IFN-γ and DFO alone (p = 0.0426) (Fig 9). Finally, the gene HIF1, related to regulation of the response to hypoxia, showed increased expression in the group treated with IFN-γ alone relative to the control (p = 0.0072) (Fig 10).
Proteomics
In the PCA, distancing was observed between the control and DFO groups, and a close clustering between the control and IFN-γ + DFO group and the control with IFN-γ. The sum of the variances explained by principal components PC1 and PC2, for the control group versus treated groups, was 56.7% in DFO, 48.3% in IFN-γ + DFO, and 50.4% in IFN-γ (Fig 11), suggesting that there is a significant difference between the control group and the DFO and IFN-γ groups regarding treatment variables, although the IFN-γ + DFO group being close to 50% indicates there is consistency in the response with the control group.
Amount of proteins identified in Canis lupus familiaris MSCs (http://bioinformatics.psb.ugent.be/webtools/Venn/).
MS analysis identified 256 proteins, of which 70 were co-expressed; however, there were proteins expressed exclusively in the MSCs of the different groups (41 proteins in the CTR group, 44 in DFO, 15 in the IFN-γ + DFO group, and 34 for IFN-γ) (Fig 11), suggesting a different abundance of proteins of cAT-MSCs in each of the in vitro culture conditions, as evidenced by the heatmap (S4 Fig) that identified the protein clusters with higher or lower expression in each group. Like the PCA (Fig 12), the IFN and DFO groups exhibited reliable protein markers that differed from the control group.
(A, C and E) Dendrogram of emPAIs of proteins of the control group, versus DFO, IFN-γ + DFO e INF-γ. (B, D and F) Analysis of the components of the control group, versus DFO, IFN-γ + DFO e INF-γ.
S1, S2, S3 and S4 Table describe the results obtained for each group, including the molecular function, biological process, and cellular component of each protein. The main biological processes were the cellular, metabolism, and biological regulation process (S2 Fig); molecular functions in all groups were binding, catalytic, and structural molecular activity (S3 Fig); and the main cellular compartments were proteins located mainly in the cellular anatomical entity and protein-containing complexes (S4 Fig).
In the t-test, 6, 5, and 4 significantly representative proteins were identified in the DFO, IFN-γ + DFO, and IFN-γ groups, respectively, when compared with the control group (Figs 13–15).
The protein matrix was subjected to biomarker analysis (ROC curve) versus that of the control group. In DFO, 6 proteins were identified (S5 Fig), 1 in IFN-γ + DFO (S6 Fig), and 2 in the IFN-γ group (S7 Fig).
Discussion
Several MSC preconditioning strategies have been investigated to enhance therapeutic efficacy, post-transplant survival, and the performance of secreted products, notably hypoxia induction (physical or mimicked by DFO) and stimulation by pro-inflammatory cytokines such as IFN-γ [28,29,54,55]. In line with applications in ischemic stroke [56], as well as literature describing improvement of immunoregulation, differentiation, and angiogenesis after cytokine conditioning [57,58] we evaluated in the present study with cAT-MSCs the effects of DFO and IFN-γ, alone and combined, on proliferation, viability, transcriptional profile, and proteomics.
In the proliferative axis, a reduction in cell number was observed up to 96 hours of culture, followed by stabilization up to 144 hours in all groups. This pattern converges with reports of an antiproliferative effect of IFN-γ in MSCs [2] and proliferative suppression induced by DFO at higher concentrations. It is plausible that the absence of FBS in the clonal proliferation assay of resistant subpopulations explains the late stabilization; in any case, longer time series (greater than 6 days) would be informative to distinguish adaptive quiescence from proliferative resumption in serum-free medium. In parallel, viability after 48 hours remained ≥ 90% with a low rate of apoptosis/necrosis regardless of treatment, which is consistent with observations of minimal cytotoxicity under short-term hypoxia and inflammation.
As for gene expression, although without global statistical significance, a consistent trend (13/16 genes evaluated) of higher transcription with IFN-γ was observed, whereas classic immunoregulatory genes (HGF, IDO, PGE2, IL-6) remained stable, suggesting that the dose/time employed did not shift the tolerogenic set-point of cAT-MSCs. In contrast, the angiogenic outcome was clear: VEGFA increased in the DFO and IFN-γ + DFO groups in alignment with robust evidence for hypoxia/DFO in MSCs [17,29,59–62]. A particular finding was the increase of HIF-1α, especially with IFN-γ (vs. control), suggesting inflammation–hypoxia crosstalk; indeed, the NF-κB cell signaling pathway can transcriptionally induce HIF1A, linking innate immunity to the hypoxic response and explaining activation of survival, proliferation, and metabolic reprogramming programs even without a direct drop in O₂ [63]. The absence of a difference between control and DFO for HIF-1α, in turn, may reflect dose/time-window dependence of DFO-mediated stabilization, as described by Oses [61]. In summary, our data support that HIF-1α participates both in homeostasis under O₂ fluctuations and in inflammatory regulatory circuits in cAT-MSCs [63].
Proteomics (256 proteins) evidenced treatment-specific signatures, with significant differences CTR vs. DFO and CTR vs. IFN-γ; the IFN-γ + DFO combination approached the threshold of significance. Each condition induced a set of exclusive proteins, but diversity was lower in IFN-γ + DFO, suggesting that combined stress may contract the proteomic repertoire. This result contrasts with observations in human MSCs exposed for 48 hours to hypoxia (1% O₂), IFN-γ, or hypoxia+IFN-γ, in which increased protein/metabolic content was reported in the combined condition [64]; the discrepancy likely stems from differences in cell type, hypoxia parameters (real pO₂ vs. chemical hypoximimetics), dose, and times. Moreover, it is prudent to remember that protein abundance does not bear a linear relationship with mRNA, because layers of post-transcriptional regulation, translation, and degradation strongly modulate protein levels, which limits transcript–protein correlations [65].
At the level of molecular markers, some convergent functional signals stand out. The increase of CYP450 in treated groups suggests a mitochondrial/oxidative response to stress; although activation of this axis may, in extreme scenarios, connect to caspase-mediated apoptotic pathways, we observed a trend toward reduced CASP9 in IFN-γ + DFO, consistent with literature on hypoxic preconditioning attenuating MSC apoptosis and inducing survival factors such as Bcl-2/VEGF [66]. In parallel, the lower abundance of β-tubulin with DFO is compatible with cytoskeletal adjustment/quiescence under energy economy. Meanwhile, sGC-β (soluble guanylyl cyclase, β subunit) was higher in control vs. DFO, a pattern consistent with NO/O₂ regulation of the NO–sGC–cGMP axis and with the possibility of angiogenic rerouting via alternative pathways (HIF-1/VEGF) under hypoximimetic conditions [67]. Finally, aldolase (associated with glycolytic flux under stress/expansion) and HSPs (cytoprotection, protein folding, containment of apoptosis) were elevated in treated groups; the literature supports heat preconditioning as a strategy to reinforce immunomodulation and survival of MSCs in acute lung injury [68].
Taken together, the findings indicate that, under the conditions tested, the angiogenic axis responded more clearly to manipulations, with VEGFA increasing under DFO, alone or associated with IFN-γ [17,29,59–62], whereas the immunomodulatory axis remained stable, suggesting that the IFN-γ dose/time and culture conditions preserved the basal tolerogenic phenotype of cAT-MSCs. High viability, low apoptosis, and downregulation of pro-apoptotic transcripts reinforce that the preconditioning employed, especially when combined, preferentially modulate metabolic/angiogenic adaptations without compromising cellular integrity; still, studies with extended time series, real hypoxia (1% O₂) vs. hypoximimetic conditions, and transcriptome–proteome–secretome/EV integration will be valuable to translate molecular signatures into paracrine functions and in vivo efficacy [64,65].
Conclusion
The present study demonstrated that preconditioning of canine adipose tissue-derived mesenchymal stem cells (cAT-MSCs) with DFO, IFN-γ, or both modulated gene expression and the proteomic profile while preserving fibroblast-like morphology and proliferative capacity. Although no significant differences were observed in proliferation rate, the treated groups showed higher cell concentration over time, suggesting a positive effect of preconditioning on viability. Gene analysis indicated that DFO favored angiogenic pathways (VEGFA), whereas IFN-γ was more associated with activation of genes related to apoptosis and cellular repair (Casp9, FGF2, DKC1, and TP53). Proteomics revealed proteins exclusive to each experimental condition, indicating that different preconditioning stimuli induce distinct molecular signatures.
Our findings reinforce that preconditioning can optimize immunomodulatory properties and microenvironmental adaptation of cAT-MSCs, representing a promising strategy to increase their therapeutic efficacy in contexts of inflammation and hypoxia. Future studies using real hypoxic conditions and multi-omics approaches will be essential to establish more robust correlations among molecular signatures, paracrine functions, and in vivo performance of these cells.
Supporting information
S1 Fig. Expression of functional genes in canine MSCs after 48 h.
Expression of pro-apoptotic genes (A, B, and C) related to cell survival (D, E, and F), immunomodulation (G, H, I, and J), proliferation and differentiation (K), angiogenesis (L and M), cell cycle regulators (N and O), and the cellular regulator of adaptive response to hypoxia (P) in canine adipose tissue-derived mesenchymal stem cells cultured for 48 hours under different conditions. Bars represent mean relative values normalized to the reference gene GAPDH and standard error of the mean (┬ and ┴). Means denoted by different letters indicate statistically significant differences among treatments. (p < 0.05).
https://doi.org/10.1371/journal.pone.0345360.s001
(PDF)
S2 Fig. Gene ontology of the groups considering biological process.
https://doi.org/10.1371/journal.pone.0345360.s002
(PDF)
S3 Fig. Gene ontology of the groups considering molecular function.
https://doi.org/10.1371/journal.pone.0345360.s003
(PDF)
S4 Fig. MSC protein abundance heatmap.
(A) CTR versus DFO, (B) CTR versus IFN-γ + DFO and (C) CTR versus INF-γ.
https://doi.org/10.1371/journal.pone.0345360.s004
(PDF)
S5 Fig. AUC values found for 6 proteins from Canis lupus familiaris MSCs from the DFO group versus control.
https://doi.org/10.1371/journal.pone.0345360.s005
(PDF)
S6 Fig. AUC values found for 1 protein from Canis lupus familiaris MSCs from the IFN-g + DFO group versus control.
https://doi.org/10.1371/journal.pone.0345360.s006
(PDF)
S7 Fig. AUC values found for 2 proteins from Canis lupus familiaris MSCs from the INF-g group versus control.
https://doi.org/10.1371/journal.pone.0345360.s007
(PDF)
S1 Table. Gene ontology of proteins extracted from CTR group cAT-MSCs.
Data obtained of UniprotKB (www.uniprot.org).
https://doi.org/10.1371/journal.pone.0345360.s008
(PDF)
S2 Table. Gene ontology of proteins extracted from INF-γ group cAT-MSCs.
Data obtained of UniprotKB (www.uniprot.org).
https://doi.org/10.1371/journal.pone.0345360.s009
(PDF)
S3 Table. Gene ontology of proteins extracted from DFO group cAT-MSCs.
Data obtained of UniprotKB (www.uniprot.org).
https://doi.org/10.1371/journal.pone.0345360.s010
(PDF)
S4 Table. Gene ontology of proteins extracted from INF-γ + DFO group cAT-MSCs.
Data obtained of UniprotKB (www.uniprot.org).
https://doi.org/10.1371/journal.pone.0345360.s011
(PDF)
References
- 1. Buravkova LB, Andreeva ER, Gogvadze V, Zhivotovsky B. Mesenchymal stem cells and hypoxia: where are we?. Mitochondrion. 2014;19 Pt A:105–12. pmid:25034305
- 2. Croitoru-Lamoury J, Lamoury FMJ, Caristo M, Suzuki K, Walker D, Takikawa O, et al. Interferon-γ regulates the proliferation and differentiation of mesenchymal stem cells via activation of indoleamine 2,3 dioxygenase (IDO). PLoS One. 2011;6(2):e14698. pmid:21359206
- 3. Liu L, Gao J, Yuan Y, Chang Q, Liao Y, Lu F. Hypoxia preconditioned human adipose derived mesenchymal stem cells enhance angiogenic potential via secretion of increased VEGF and bFGF. Cell Biol Int. 2013;37(6):551–60.
- 4. Seifert M, Stolk M, Polenz D, Volk H-D. Detrimental effects of rat mesenchymal stromal cell pre-treatment in a model of acute kidney rejection. Front Immunol. 2012;3:202. pmid:22826709
- 5. Mehrabani M, Najafi M, Kamarul T, Mansouri K, Iranpour M, Nematollahi MH, et al. Deferoxamine preconditioning to restore impaired HIF-1α-mediated angiogenic mechanisms in adipose-derived stem cells from STZ-induced type 1 diabetic rats. Cell Prolif. 2015;48(5):532–49. pmid:26332145
- 6. Pfaffl MW. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res. 2001;29(9):e45. pmid:11328886
- 7. Bajada S, Mazakova I, Richardson JB, Ashammakhi N. Updates on stem cells and their applications in regenerative medicine. J Tissue Eng Regen Med. 2008;2(4):169–83. pmid:18493906
- 8. Lee S-J, Ryu M-O, Seo M-S, Park S-B, Ahn J-O, Han S-M, et al. Mesenchymal Stem Cells Contribute to Improvement of Renal Function in a Canine Kidney Injury Model. In Vivo. 2017;31(6):1115–24. pmid:29102933
- 9. Moon MH, Kim SY, Kim YJ, Kim SJ, Lee JB, Bae YC, et al. Human adipose tissue-derived mesenchymal stem cells improve postnatal neovascularization in a mouse model of hindlimb ischemia. Cell Physiol Biochem. 2006;17(5–6):279–90. pmid:16791003
- 10. Rodríguez-Fuentes DE, Fernández-Garza LE, Samia-Meza JA, Barrera-Barrera SA, Caplan AI, Barrera-Saldaña HA. Mesenchymal Stem Cells Current Clinical Applications: A Systematic Review. Arch Med Res. 2021;52(1):93–101. pmid:32977984
- 11. Wu X, Jiang J, Gu Z, Zhang J, Chen Y, Liu X. Mesenchymal stromal cell therapies: immunomodulatory properties and clinical progress. Stem Cell Res Ther. 2020;11(1):345. pmid:32771052
- 12. Carrière A, Ebrahimian TG, Dehez S, Augé N, Joffre C, André M, et al. Preconditioning by mitochondrial reactive oxygen species improves the proangiogenic potential of adipose-derived cells-based therapy. Arterioscler Thromb Vasc Biol. 2009;29(7):1093–9. pmid:19423864
- 13. Aurora AB, Olson EN. Immune modulation of stem cells and regeneration. Cell Stem Cell. 2014;15(1):14–25. pmid:24996166
- 14. Barrachina L, Remacha AR, Romero A, Vázquez FJ, Albareda J, Prades M, et al. Priming Equine Bone Marrow-Derived Mesenchymal Stem Cells with Proinflammatory Cytokines: Implications in Immunomodulation-Immunogenicity Balance, Cell Viability, and Differentiation Potential. Stem Cells Dev. 2017;26(1):15–24. pmid:27712399
- 15. Strojny C, Boyle M, Bartholomew A, Sundivakkam P, Alapati S. Interferon Gamma-treated Dental Pulp Stem Cells Promote Human Mesenchymal Stem Cell Migration In Vitro. J Endod. 2015;41(8):1259–64. pmid:26051078
- 16. Tsumanuma Y, Iwata T, Kinoshita A, Washio K, Yoshida T, Yamada A, et al. Allogeneic Transplantation of Periodontal Ligament-Derived Multipotent Mesenchymal Stromal Cell Sheets in Canine Critical-Size Supra-Alveolar Periodontal Defect Model. Biores Open Access. 2016;5(1):22–36. pmid:26862470
- 17. Choi JR, Pingguan-Murphy B, Wan Abas WAB, Yong KW, Poon CT, Noor Azmi MA, et al. In situ normoxia enhances survival and proliferation rate of human adipose tissue-derived stromal cells without increasing the risk of tumourigenesis. PLoS One. 2015;10(1):e0115034. pmid:25615717
- 18. Pittenger MF, Mackay AM, Beck SC, Jaiswal RK, Douglas R, Mosca JD, et al. Multilineage potential of adult human mesenchymal stem cells. Science. 1999;284(5411):143–7. pmid:10102814
- 19. Ryan JM, Barry F, Murphy JM, Mahon BP. Interferon-gamma does not break, but promotes the immunosuppressive capacity of adult human mesenchymal stem cells. Clin Exp Immunol. 2007;149(2):353–63. pmid:17521318
- 20. Caplan AI. Adult mesenchymal stem cells for tissue engineering versus regenerative medicine. J Cell Physiol. 2007;213(2):341–7. pmid:17620285
- 21. Ceron W, Lozada-Requena I, Ventocilla K, Jara S, Pinto M, Cabello M, et al. Células tronco mesenquimales: definiciones, cultivo y aplicaciones potenciales. Rev Peru Med Exp Salud Publica. 2016;33(4):758.
- 22. Krampera M, Cosmi L, Angeli R, Pasini A, Liotta F, Andreini A, et al. Role for Interferon-γ in the Immunomodulatory Activity of Human Bone Marrow Mesenchymal Stem Cells. Stem Cells. 2005;24(2):386–98.
- 23. Iwase T, Nagaya N, Fujii T, Itoh T, Murakami S, Matsumoto T, et al. Comparison of angiogenic potency between mesenchymal stem cells and mononuclear cells in a rat model of hindlimb ischemia. Cardiovasc Res. 2005;66(3):543–51. pmid:15914119
- 24. Kinnaird T, Stabile E, Burnett MS, Lee CW, Barr S, Fuchs S, et al. Marrow-derived stromal cells express genes encoding a broad spectrum of arteriogenic cytokines and promote in vitro and in vivo arteriogenesis through paracrine mechanisms. Circ Res. 2004;94(5):678–85. pmid:14739163
- 25. Park SH, Kim KW, Chun YS, Kim JC. Human mesenchymal stem cells differentiate into keratocyte-like cells in keratocyte-conditioned medium. Exp Eye Res. 2012;101:16–26. pmid:22683947
- 26. Li M, Jiang Y, Hou Q, Zhao Y, Zhong L, Fu X. Potential pre-activation strategies for improving therapeutic efficacy of mesenchymal stem cells: current status and future prospects. Stem Cell Res Ther. 2022;13(1):146. pmid:35379361
- 27. Zhuo H, Chen Y, Zhao G. Advances in application of hypoxia-preconditioned mesenchymal stem cell-derived exosomes. Front Cell Dev Biol. 2024;12:1446050. pmid:39239560
- 28. Zhang J, Lu Y, Mao Y, Yu Y, Wu T, Zhao W, et al. IFN-γ enhances the efficacy of mesenchymal stromal cell-derived exosomes via miR-21 in myocardial infarction rats. Stem Cell Res Ther. 2022;13(1):333. pmid:35870960
- 29. Efimenko A, Starostina E, Kalinina N, Stolzing A. Angiogenic properties of aged adipose derived mesenchymal stem cells after hypoxic conditioning. J Transl Med. 2011;9:10. pmid:21244679
- 30. Roemeling-van Rhijn M, Mensah FKF, Korevaar SS, Leijs MJ, van Osch GJVM, Ijzermans JNM, et al. Effects of Hypoxia on the Immunomodulatory Properties of Adipose Tissue-Derived Mesenchymal Stem cells. Front Immunol. 2013;4:203. pmid:23882269
- 31. Park S-M, An J-H, Lee J-H, Kim K-B, Chae H-K, Oh Y-I, et al. Extracellular vesicles derived from DFO-preconditioned canine AT-MSCs reprogram macrophages into M2 phase. PLoS One. 2021;16(7):e0254657. pmid:34310627
- 32. Al-Khaldi A, Eliopoulos N, Martineau D, Lejeune L, Lachapelle K, Galipeau J. Postnatal bone marrow stromal cells elicit a potent VEGF-dependent neoangiogenic response in vivo. Gene Ther. 2003;10(8):621–9. pmid:12692590
- 33. Hu X, Yu SP, Fraser JL, Lu Z, Ogle ME, Wang J-A, et al. Transplantation of hypoxia-preconditioned mesenchymal stem cells improves infarcted heart function via enhanced survival of implanted cells and angiogenesis. J Thorac Cardiovasc Surg. 2008;135(4):799–808. pmid:18374759
- 34. Jun EK, Zhang Q, Yoon BS, Moon J-H, Lee G, Park G, et al. Hypoxic conditioned medium from human amniotic fluid-derived mesenchymal stem cells accelerates skin wound healing through TGF-β/SMAD2 and PI3K/Akt pathways. Int J Mol Sci. 2014;15(1):605–28. pmid:24398984
- 35. Kim Y, Lee SH, Kim WH, Kweon O-K. Transplantation of adipose derived mesenchymal stem cells for acute thoracolumbar disc disease with no deep pain perception in dogs. J Vet Sci. 2016;17(1):123–6. pmid:27051350
- 36. Liu ZD, Hider RC. Design of iron chelators with therapeutic application. Coord Chem Rev. 2002;232(1–2):151–71.
- 37. Monteiro BS, Argolo Neto NM, Del Carlo RJ. Células-tronco mesenquimais. Cienc Rural. 2010;40(1):238–45.
- 38. Noone C, Kihm A, English K, O’Dea S, Mahon BP. IFN-γ stimulated human umbilical-tissue-derived cells potently suppress NK activation and resist NK-mediated cytotoxicity in vitro. Stem Cells Dev. 2013;22(22):3003–14. pmid:23795941
- 39. Oontawee S, Siriarchavatana P, Rodprasert W, Padeta I, Pamulang YV, Somparn P, et al. Small extracellular vesicles derived from sequential stimulation of canine adipose-derived mesenchymal stem cells enhance anti-inflammatory activity. BMC Vet Res. 2025;21(1):31. pmid:39838398
- 40. Ramakers C, Ruijter JM, Deprez RHL, Moorman AFM. Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neurosci Lett. 2003;339(1):62–6. pmid:12618301
- 41. Nantavisai S, Rodprasert W, Pathanachai K, Wikran P, Kitcharoenthaworn P, Smithiwong S, et al. Simvastatin enhances proliferation and pluripotent gene expression by canine bone marrow-derived mesenchymal stem cells (cBM-MSCs) in vitro. Heliyon. 2019;5(10):e02663. pmid:31687506
- 42. Lee J, Lee KS, Kim C-L, Byeon JS, Gu N-Y, Cho I-S, et al. Effect of donor age on the proliferation and multipotency of canine adipose-derived mesenchymal stem cells. J Vet Sci. 2017;18(2):141–8. pmid:27456768
- 43. de Oliveira Pinheiro A, Lara VM, Souza AF, Casals JB, Bressan FF, Fantinato Neto P, et al. Characterization and Immunomodulation of Canine Amniotic Membrane Stem Cells. Stem Cells Cloning. 2020;13:43–55. pmid:32440160
- 44. Song WJ, Li Q, Ryu MO, Ahn JO, Bhang DH, Jung YC, et al. TSG-6 released from intraperitoneally injected canine adipose tissue-derived mesenchymal stem cells ameliorate inflammatory bowel disease by inducing M2 macrophage switch in mice. Stem Cell Res Ther. 2018 Apr 6;9(1). pmid:29625582
- 45. Zhang J, Liu Z, Li Y, You Q, Yang J, Jin Y, et al. FGF-2-Induced Human Amniotic Mesenchymal Stem Cells Seeded on a Human Acellular Amniotic Membrane Scaffold Accelerated Tendon-to-Bone Healing in a Rabbit Extra-Articular Model. Stem Cells Int. 2020;2020:4701476. pmid:32399042
- 46. Teshima T, Matsumoto H, Koyama H. Soluble factors from adipose tissue-derived mesenchymal stem cells promote canine hepatocellular carcinoma cell proliferation and invasion. PLoS One. 2018;13(1):e0191539. pmid:29346427
- 47. Chung DJ, Wong A, Hayashi K, Yellowley CE. Effect of hypoxia on generation of neurospheres from adipose tissue-derived canine mesenchymal stromal cells. Vet J. 2014;199(1):123–30. pmid:24252224
- 48. Peach M, Marsh N, Macphee DJ. Protein solubilization: attend to the choice of lysis buffer. Methods Mol Biol. 2012;869:37–47. pmid:22585475
- 49. Baker SS, Cardullo RA, Thaler CD. Sonication of mouse sperm membranes reveals distinct protein domains. Biol Reprod. 2002;66(1):57–64. pmid:11751264
- 50. Souza FF, Chirinéa VH, Martins MIM, Lopes MD. Osteopontin in seminal plasma and sperm membrane of dogs. Reprod Domest Anim. 2009;44 Suppl 2:283–6. pmid:19754587
- 51. Luo S, Wehr NB, Levine RL. Quantitation of protein on gels and blots by infrared fluorescence of Coomassie blue and Fast Green. Anal Biochem. 2006;350(2):233–8. pmid:16336940
- 52. Neuhoff V, Stamm R, Eibl H. Clear background and highly sensitive protein staining with Coomassie Blue dyes in polyacrylamide gels: A systematic analysis. Electrophoresis. 1985;6(9):427–48.
- 53. Shevchenko A, Wilm M, Vorm O, Mann M. Mass spectrometric sequencing of proteins silver-stained polyacrylamide gels. Anal Chem. 1996;68(5):850–8. pmid:8779443
- 54. Lee J, Henderson K, Massidda MW, Armenta-Ochoa M, Im BG, Veith A, et al. Mechanobiological conditioning of mesenchymal stem cells for enhanced vascular regeneration. Nat Biomed Eng. 2021;5(1):89–102. pmid:33483713
- 55. Nantavisai S, Rodprasert W, Pathanachai K, Wikran P, Kitcharoenthaworn P, Smithiwong S, et al. Simvastatin enhances proliferation and pluripotent gene expression by canine bone marrow-derived mesenchymal stem cells (cBM-MSCs) in vitro. Heliyon. 2019;5(10):e02663. pmid:31687506
- 56. Davis CK, Jain SA, Bae O-N, Majid A, Rajanikant GK. Hypoxia Mimetic Agents for Ischemic Stroke. Front Cell Dev Biol. 2019;6:175. pmid:30671433
- 57. Yang K-Q, Liu Y, Huang Q-H, Mo N, Zhang Q-Y, Meng Q-G, et al. Bone marrow-derived mesenchymal stem cells induced by inflammatory cytokines produce angiogenetic factors and promote prostate cancer growth. BMC Cancer. 2017;17(1):878. pmid:29268703
- 58. Yu Y, Yoo SM, Park HH, Baek SY, Kim Y-J, Lee S, et al. Preconditioning with interleukin-1 beta and interferon-gamma enhances the efficacy of human umbilical cord blood-derived mesenchymal stem cells-based therapy via enhancing prostaglandin E2 secretion and indoleamine 2,3-dioxygenase activity in dextran sulfate sodium-induced colitis. J Tissue Eng Regen Med. 2019;13(10):1792–804. pmid:31293088
- 59. Crisostomo PR, Wang Y, Markel TA, Wang M, Lahm T, Meldrum DR. Human mesenchymal stem cells stimulated by TNF-alpha, LPS, or hypoxia produce growth factors by an NF kappa B- but not JNK-dependent mechanism. Am J Physiol Cell Physiol. 2008;294(3):C675-82. pmid:18234850
- 60. Heirani-Tabasi A, Mirahmadi M, Mishan MA, Naderi-Meshkin H, Toosi S, Matin MM, et al. Comparison the effects of hypoxia-mimicking agents on migration-related signaling pathways in mesenchymal stem cells. Cell Tissue Bank. 2020;21(4):643–53. pmid:32815062
- 61. Oses C, Olivares B, Ezquer M, Acosta C, Bosch P, Donoso M, et al. Preconditioning of adipose tissue-derived mesenchymal stem cells with deferoxamine increases the production of pro-angiogenic, neuroprotective and anti-inflammatory factors: Potential application in the treatment of diabetic neuropathy. PLoS One. 2017;12(5):e0178011. pmid:28542352
- 62. Ratajczak J, Hilkens P, Gervois P, Wolfs E, Jacobs R, Lambrichts I, et al. Angiogenic Capacity of Periodontal Ligament Stem Cells Pretreated with Deferoxamine and/or Fibroblast Growth Factor-2. PLoS One. 2016;11(12):e0167807. pmid:27936076
- 63. Rius J, Guma M, Schachtrup C, Akassoglou K, Zinkernagel AS, Nizet V, et al. NF-kappaB links innate immunity to the hypoxic response through transcriptional regulation of HIF-1alpha. Nature. 2008;453(7196):807–11. pmid:18432192
- 64. Wobma HM, Tamargo MA, Goeta S, Brown LM, Duran-Struuck R, Vunjak-Novakovic G. The influence of hypoxia and IFN-γ on the proteome and metabolome of therapeutic mesenchymal stem cells. Biomaterials. 2018;167:226–34. pmid:29574308
- 65. Vogel C, Marcotte EM. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet. 2012;13(4):227–32. pmid:22411467
- 66. Wang J, Chen T, Jiang J, Shi H, Gui C, Luo R, et al. Hypoxic preconditioning attenuates hypoxia/reoxygenation-induced apoptosis in mesenchymal stem cells. Acta Pharmacol Sin. 2008;29(1):74–82. pmid:18158868
- 67. Friebe A, Koesling D. Regulation of nitric oxide-sensitive guanylyl cyclase. Circ Res. 2003;93(2):96–105. pmid:12881475
- 68. Lv H, Yuan X, Zhang J, Lu T, Yao J, Zheng J, et al. Heat shock preconditioning mesenchymal stem cells attenuate acute lung injury via reducing NLRP3 inflammasome activation in macrophages. Stem Cell Res Ther. 2021;12(1):290. pmid:34001255