Introduction: Replicative senescence limits the expansion and therapeutic potential of human umbilical cord-derived mesenchymal stem cells (hUC-MSCs). This study aimed to identify passage-associated candidate genes and assess their relationships with senescence-associated phenotypes. materials and methods: 2.1 Transcriptomic Data Analysis A systematic analysis was performed based on previously generated transcriptomic datasets of hUC-MSCs cultured under planar passaging and bioreactor expansion conditions (GSE233634 - GEO DataSets - NCBI (nih.gov)). Planar culture samples included passages p3, p6, p9, and p12, while bioreactor samples comprised two batches (BioR1 and BioR3) collected at different time points during continuous operation(Wang, X., et al.,2023). As described in prior analyses, p12 samples were compared with p3, p6, and p9 samples to identify significantly upregulated and downregulated genes. The intersection of differentially expressed genes across these comparisons yielded 405 common genes, as visualized by Venn diagram analysis. To further identify genes with progressively increased expression during passaging, time-series analysis was conducted, clustering these genes into three groups. Among them, 205 genes in cluster 1 exhibited a consistent upward trend with increasing passage number (Wang, X., et al.,2023). These genes were subsequently subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Genes enriched in biological processes related to the cell cycle and cell division, as well as in pathways such as the cell cycle, p53 signaling pathway, and cellular senescence, were selected. Five genes—CDK1, CCNB1, CCNB2, RRM2, and GTSE1—were identified as key candidates. Notably, their expression levels also increased with passage number in the bioreactor system, suggesting their important roles in hUC-MSC senescence. 2.2 Isolation and Culture of hUC-MSCs Umbilical cords from three independent donors were provided by Shandong Qilu Stem Cell Biotechnology Group Co., Ltd. All procedures were approved by the Medical Ethics Committee of Shandong Provincial Third Hospital. Primary hUC-MSCs were isolated using the tissue explant adherence method [17]. Briefly, freshly obtained Wharton’s jelly tissue fragments were placed in T-flasks and cultured in a small volume of serum-free hUC-MSC medium (Applied Cell, Shanghai, China; AC-1001043 [PRF]) at 37°C in a humidified atmosphere containing 5% CO₂. Cells obtained from the first harvest were designated as passage 0 (p0) and subsequently expanded through continuous passaging up to p15, with medium changes every 2–3 days. In this study, p6 and p12 hUC-MSCs were primarily used for subsequent experiments. 2.3 Characterization of Cell Surface Markers Flow cytometry was used to characterize the phenotypes of P6 and P12 hUC-MSCs. Cells at 80–90% confluence were harvested and incubated with fluorescein isothiocyanate (FITC)-, phycoerythrin (PE)-, or allophycocyanin (APC)-conjugated monoclonal antibodies at 4°C for 30 min. The antibodies (Thermo Fisher Scientific) included CD73-FITC, CD90-PE, CD105-APC, CD34-FITC, CD45-APC, and HLA-DR-PE. Fluorescence signals were detected using a CytoFLEX flow cytometer (Beckman Coulter, USA), and data were analyzed with FlowJo V10 software. 2.4 RNA Interference and Transfection Small interfering RNAs (siRNAs) targeting the selected genes and the transfection reagents were designed and synthesized by GenePharma (Suzhou, China). When P12 hUC-MSCs reached 50–70% confluence in 6-well plates, transfection was performed according to the manufacturer’s instructions. Gene knockdown efficiency was evaluated by quantitative real-time PCR (qRT-PCR) at 48 h and by Western blotting at 72 h post-transfection. The siRNA sequences used in this study are listed in Supplementary Table (Table S1). 2.5 Cell Proliferation Assay Cell proliferation was assessed using a Cell Counting Kit-8 (CCK-8; Baisai Biotechnology, Shanghai, China). hUC-MSCs subjected to different treatments were seeded into 96-well plates at a density of 2,000 cells per well in 100 μL of serum-free medium and incubated at 37°C with 5% CO₂. Cell proliferation was measured daily at the same time point using the CCK-8 assay according to the manufacturer’s instructions. Absorbance at 450 nm was recorded using a microplate reader (CLARIOstar, Germany) over a period of five consecutive days. 2.6 Senescence-Associated β-Galactosidase and Reactive Oxygen Species Assays For senescence analysis, treated hUC-MSCs were seeded into 6-well plates at a density of 1 × 10⁵ cells per well and cultured in 2 mL of serum-free medium. Senescence-associated β-galactosidase (SA-β-Gal) staining was performed using a commercial kit (Beyotime, Nanjing, China) according to the manufacturer’s instructions. Stained cells were randomly imaged under an inverted microscope (Nikon), and the proportion of senescent cells was evaluated. Intracellular reactive oxygen species (ROS) levels were measured using a ROS detection kit (Solarbio, Beijing, China). Cells were stained with the fluorescent probe DCFH-DA according to the manufacturer’s protocol, and fluorescence intensity was analyzed by flow cytometry to assess ROS levels. 2.7 Cell Cycle Analysis Cell cycle distribution was analyzed using a cell cycle detection kit (Elabscience, Wuhan, China). hUC-MSCs from different treatment groups were fixed overnight in 70% cold ethanol at −20°C, followed by treatment with RNase at 37°C for 30 min and staining with propidium iodide (PI) at 4°C in the dark for 30 min. Samples were analyzed by flow cytometry, and data were processed using FlowJo V10 software. 2.8 RNA Extraction and Quantitative Real-Time PCR (qRT-PCR) Total RNA was extracted using the PureLink RNA Mini Kit (Invitrogen, 12183018A). cDNA was synthesized using the HiScript III RT SuperMix for qPCR (+gDNA wiper) kit (Vazyme, R323-01) according to the manufacturer’s protocol. Quantitative real-time PCR was performed using ChamQ Universal SYBR qPCR Master Mix (Bio-Rad). ALAS1 was used as the reference gene, and relative gene expression levels were calculated using the 2^−ΔΔCq method(Zheng, Z., et al.,2023). Primer sequences are provided in Supplementary Table (Table S2). 2.9 Western Blotting Cells were lysed in RIPA buffer (Beyotime) supplemented with PMSF protease inhibitor for 5 min, followed by centrifugation at 12,000 rpm for 5 min at 4°C. Protein concentrations were determined using a BCA protein assay kit (Yamei, ZJ102). Protein samples were mixed with 5× SDS loading buffer and boiled for 10 min. Proteins were separated by polyacrylamide gel electrophoresis and transferred onto polyvinylidene fluoride (PVDF) membranes (Millipore, IPVH00005). Membranes were blocked with 5% non-fat milk for 4 h and incubated with primary antibodies overnight at 4°C. After washing with Tris-buffered saline containing Tween-20 (TBST), membranes were incubated with HRP-conjugated secondary antibodies for 1 h. Protein bands were visualized using enhanced chemiluminescence (ECL) reagents (ShareBio) and detected with a chemiluminescence imaging system (Tanon). Details of primary antibodies are listed in Supplementary Table (Table S3). 2.10 Statistical Analysis Statistical analyses were performed using GraphPad Prism version 9.0.0. Data are presented as mean ± SEM. Comparisons between two groups were conducted using unpaired Student’s t-test, while comparisons among multiple groups were performed using one-way analysis of variance (ANOVA). A p-value < 0.05 was considered statistically significant. Image analysis was conducted using ImageJ software. Methods: The RNA-seq dataset GSE233634 was reanalyzed using 12 planar-culture samples from Donor 1 at p3, p6, p9, and p12. Candidate expression was examined by qRT-PCR in Donors 2-4, and siRNA experiments were performed in Donor 4-derived p12 cells. Senescence-associated features were evaluated using morphology, SA-β-galactosidase staining, CCK-8-derived metabolic activity, cell-cycle distribution, and reactive oxygen species (ROS). results: 3.1 Expression Patterns of Senescence-Associated Candidate Genes in Continuously Cultured hUC-MSCs To identify key genes associated with replicative senescence in hUC-MSCs, we analyzed previously generated transcriptomic datasets from planar serial passaging and bioreactor-based cultures. Based on population doubling level (PDL = 3.32 (logX₁ − logX₀) + S), BioR1 and BioR3 corresponded approximately to passages p9 and p12 in planar culture, respectively(Wang, X., et al.,2023). Cells representing different passages and culture conditions (p6, p12, BioR1, and BioR3) were selected for transcriptomic analysis to identify senescence-related genes. We first evaluated the expression patterns of classical senescence markers in hUC-MSCs. The results showed that P53, P21, and P16 were not consistently upregulated with increasing passage number. Specifically, P53 and P21 exhibited a decreasing trend under both culture conditions, while P16 expression decreased in planar culture but increased in the bioreactor system (Fig. S1a). These findings suggest that conventional senescence markers are not suitable for assessing the senescent state of hUC-MSCs prior to passage 12. Subsequently, by comparing transcriptomic profiles between p6 and p12 (planar culture) and between BioR1 and BioR3 (bioreactor culture), we identified candidate genes significantly upregulated in senescent passages. In planar culture, CDK1, CCNB1, CCNB2, RRM2, and GTSE1 were markedly upregulated in p12 compared with P6. Similarly, in bioreactor culture, CDK1, CCNB1, CCNB2, and GTSE1 were significantly upregulated in BioR3 compared with BioR1, while RRM2 showed an increasing trend (Fig. S1b). These genes are closely associated with cell cycle regulation, suggesting their potential involvement in replicative senescence of hUC-MSCs. 3.2 Isolation and Morphological Observation of Primary hUC-MSCs Primary hUC-MSCs were isolated using the tissue explant adherence method. Cell outgrowth during primary culture was monitored under an inverted microscope. On day 3 of culture, a small number of cells migrated out from the edges of the tissue explants, appearing as scattered dot-like structures (Fig. 1a). By day 7, the number of outgrown cells increased and displayed a radial arrangement surrounding the explants (Fig. 1b). On day 11, cell confluence further increased, and the cells exhibited a uniform morphology with a typical elongated spindle-shaped fibroblast-like appearance (Fig. 1c). These observations indicate that hUC-MSCs successfully migrated out from the tissue explants and maintained good morphology, consistent with previously reported characteristics of hUC-MSCs(Chen, Y., et al.,2015, Fan, C. G., et al.,2011). 3.3 Comparison of Phenotype and Morphology Between Early- and Late-Passage hUC-MSCs To characterize the senescence process of hUC-MSCs in this study, we evaluated the expression of cell surface markers and cellular morphology in early-passage (p6) and late-passage (p12) cells. Flow cytometry analysis showed that both p6 and p12 hUC-MSCs highly expressed mesenchymal stem cell-positive markers CD73, CD90, and CD105 (>98%), while exhibiting low expression of negative markers CD34, CD45, and HLA-DR (<1%), in accordance with the criteria defined by the International Society for Cell and Gene Therapy(Dominici, M., et al.,2006) (Fig. 2a). Bright-field microscopy revealed that, compared with p6 cells, p12 cells appeared more flattened and enlarged, with increased cellular protrusions; some cells also exhibited an elongated morphology, suggesting the presence of senescence-associated morphological changes (Fig. 2b). These results indicate that both p6 and p12 cells retained the characteristic phenotype of hUC-MSCs, while p12 cells displayed morphological features associated with cellular senescence, consistent with previously reported replicative senescence in MSCs(Zhao, Q., et al.,2019). 3.4 Comparison of Senescence-Associated Phenotypes Between P6 and P12 hUC-MSCs To further validate the senescent status of p12 cells, multiple senescence-associated indicators were assessed. SA-β-Gal staining showed a significantly higher proportion of blue-positive cells in p12 compared with p6 cells (Fig. 3a), which is a classical hallmark of cellular senescence(Campisi, J. and d'Adda di Fagagna, F.,2007). CCK-8 assays demonstrated that, at 120 h of culture, the proliferation rate of p12 cells was markedly lower than that of p6 cells (Fig. 3b), consistent with previous reports of reduced proliferative capacity in senescent MSCs(Turinetto, V., et al.,2016). Flow cytometric analysis of cell cycle distribution revealed that the proportion of cells in S phase was significantly reduced, while the proportion in G0/G1 phase was significantly increased in p12 cells compared with p6 cells (Fig. 3c), indicating cell cycle arrest at the G0/G1 phase. Reactive oxygen species (ROS) detection showed significantly increased DCFH fluorescence intensity in p12 cells, indicating elevated ROS levels (Fig. 3d); oxidative stress is a key mechanism driving cellular senescence(Campisi, J. and d'Adda di Fagagna, F.,2007). Collectively, p12 cells exhibited significant alterations across multiple senescence-related parameters, including increased SA-β-Gal positivity, reduced proliferation, cell cycle arrest, and elevated ROS levels, confirming their designation as a “senescent passage,” consistent with characteristics of replicative senescence reported in the literature(Wang, Y., et al.,2013, Zhao, Q., et al.,2019). 3.5 Expression Levels of CDK1, CCNB1, CCNB2, RRM2, and GTSE1 Increase During Replicative Senescence of hUC-MSCs To validate the upregulation of five candidate senescence-associated genes identified from transcriptomic analysis at both mRNA and protein levels, we examined their expression in hUC-MSCs derived from three additional donors during serial passaging. qRT-PCR results showed that, compared with early-passage (p6) cells, the mRNA expression levels of CDK1, CCNB1, CCNB2, RRM2, and GTSE1 were significantly upregulated in senescent passages (p12 and p15) across all three donors (Fig. 4a). These genes are closely associated with cell cycle regulation: CDK1 is a core kinase driving the G2/M transition(Santamaria, D., et al.,2007); CCNB1 and CCNB2 serve as regulatory subunits of CDK1 and play essential roles in mitosis(Bellanger, S., et al.,2007, Zou, Y., et al.,2020); RRM2 provides substrates for DNA synthesis and maintains genomic stability(Grolmusz, V. K., et al.,2016); and GTSE1 is expressed during the S/G2 phases and modulates cell survival and senescence via regulation of p53 activity(Monte, M., et al.,2003). Western blot analysis, including band visualization and densitometric quantification, demonstrated that protein expression levels of CDK1, CCNB1, CCNB2, and RRM2 were higher in p12 cells than in p6 cells, consistent with mRNA expression trends, whereas GTSE1 protein expression was inconclusive due to issues with antibody specificity (Fig. 4b). Meanwhile, qRT-PCR analysis of classical senescence markers P53, P21, and P16 revealed no significant upregulation in p12 compared with p6 cells (Fig. 4c), consistent with transcriptomic data (Fig. S1a) and previous reports(Cheng, H., et al.,2011, Tanabe, S., et al.,2008). These findings further suggest that conventional senescence markers may not be suitable for evaluating senescence in hUC-MSCs. Overall, the five candidate genes exhibited consistent upregulation at both mRNA and protein levels (except GTSE1), whereas traditional markers showed no significant changes, indicating that these genes may serve as potential regulators of replicative senescence in hUC-MSCs. 3.6 siRNA-Mediated Regulation of Senescence-Associated Genes in P12 hUC-MSCs To further investigate the roles of CDK1, CCNB1, CCNB2, RRM2, and GTSE1 in replicative senescence, siRNA-mediated knockdown of these genes was performed in p12 hUC-MSCs. Validation by qRT-PCR and Western blot demonstrated that both mRNA and protein levels of the target genes were significantly reduced following siRNA treatment (Fig. 5a–b), confirming the effectiveness of gene silencing and providing a reliable basis for subsequent functional analyses. 3.7 Knockdown of Senescence-Associated Genes Alleviates Senescence Phenotypes and Promotes Cell Proliferation We next assessed senescence-associated phenotypes in p12 hUC-MSCs following siRNA treatment. SA-β-Gal staining revealed a significant reduction in the proportion of positive cells in all siRNA-treated groups compared with the negative control (si-NC), with the CCNB1 siRNA group showing the lowest positivity rate (Fig. 6a), indicating attenuation of cellular senescence. CCK-8 assays showed that cell proliferation rates were significantly increased in the CCNB1 siRNA and GTSE1 siRNA groups, moderately increased in the CDK1 siRNA and CCNB2 siRNA groups, and slightly reduced in the RRM2 siRNA group compared with controls (Fig. 6b). Flow cytometric analysis demonstrated that all siRNA-treated groups exhibited a significantly increased proportion of S-phase cells, with the highest proportion observed in the RRM2 siRNA group; the proportion of G0/G1-phase cells was significantly reduced in all groups except the GTSE1 siRNA group (Fig. 6c). ROS measurements indicated that intracellular ROS levels were significantly decreased in all siRNA-treated groups except the CCNB2 siRNA group (Fig. 6d). Collectively, knockdown of CDK1, CCNB1, CCNB2, RRM2, and GTSE1 alleviated senescence-associated phenotypes in p12 hUC-MSCs to varying degrees, with CCNB1 showing the most pronounced effects across multiple indicators, suggesting it may be a key regulator of hUC-MSC senescence. These genes may act synergistically to regulate cellular senescence through modulation of cell cycle progression and ROS levels. Notably, although the RRM2 siRNA group exhibited a marked increase in S-phase proportion, its proliferation rate was slightly reduced. This phenomenon is consistent with the critical role of RRM2 in DNA synthesis: RRM2 knockdown leads to insufficient dNTP supply, allowing cells to enter S phase but impairing replication fork progression, thereby prolonging S phase and reducing overall proliferation rates(D'Angiolella, V., et al.,2012). 3.8 Effects of siRNA-Mediated Gene Regulation on Subsequent Cell Passages To determine whether the anti-senescence effects of gene knockdown could be sustained in subsequent passages, p12 hUC-MSCs treated with siRNAs targeting CDK1, CCNB1, CCNB2, RRM2, and GTSE1 were continuously cultured to passage 16 (p16). Cell proliferation and gene expression levels were then evaluated. CCK-8 assays showed that, compared with the si-NC group, all siRNA-treated groups except the GTSE1 siRNA group maintained higher proliferation rates at p16 (Fig. 7a). Notably, although the RRM2 siRNA group exhibited a slightly reduced proliferation rate at p12 (Fig. 6b), it showed the most pronounced proliferative advantage at p16 (Fig. 7a), suggesting a time-dependent effect of RRM2 knockdown on cell proliferation. In the short term, RRM2 depletion induces S-phase arrest, whereas over prolonged culture, cells may acquire a proliferative advantage through adaptive mechanisms, potentially related to metabolic adaptation or selective expansion of less senescent cells. Further qRT-PCR analysis of p16 hUC-MSCs revealed that, compared with the si-NC group, the expression levels of CDK1, CCNB2, and RRM2 remained significantly downregulated in their respective siRNA-treated groups, whereas the knockdown effects of CCNB1 and GTSE1 were attenuated and no longer significantly different from controls (Fig. 7b). These findings indicate that siRNA-mediated gene silencing can not only delay senescence in the current passage but also partially sustain this effect in subsequent passages. However, the long-term regulatory effects differ among genes, suggesting distinct roles in senescence regulation, with RRM2 showing particularly notable long-term effects worthy of further investigation. Results: Compared with p6 cells, p12 cells showed enlarged and flattened morphology, a higher SA- β-galactosidase-positive area fraction, lower CCK-8-derived metabolic activity, reduced S-phase representation, G0/G1 accumulation, and increased ROS. Transcriptomic screening identified 405 genes shared among three p12 comparisons, of which 205 progressively increased with passage. CDK1, CCNB1, CCNB2, RRM2, and GTSE1 were selected as senescence-associated candidates and showed consistent passage-associated mRNA increases in Donors 2-4. CDK1, CCNB1, CCNB2, and RRM2 were also supported at the protein level, whereas GTSE1 was supported at the mRNA level only. Candidate-gene knockdown was associated with differential changes in selected senescenceassociated readouts, with CCNB1 knockdown showing the broadest pattern. Discussion: These findings link the five candidates to passage-associated phenotypes but do not establish direct regulatory causality or reversal of senescence. Conclusion: The five genes represent candidates for further mechanistic investigation in hUC-MSC replicative senescence.
Introduction: Mesenchymal stem cells (MSCs) play a significant role in shaping and regulating microenvironments. The factors influencing the glycolytic metabolic reprogramming of MSCs remain unknown. Methods: MSCs were isolated from human umbilical cords and identified using flow cytometry. Glycolysis-related gene expression, glucose consumption, and ATP and lactate production were measured in MSCs with HIF1A-AS3 overexpression or knockdown. The roles of HIF1A-AS3 in the glycolytic pathway and its downstream network were revealed by high-throughput sequencing. Results: HIF1A-AS3 enhanced the glycolytic level of MSCs by increasing glucose consumption, lactate production, ATP levels, and expression of key glycolytic enzymes (GLUT1, HK2, and PKM2). The downstream signaling pathway of HIF1A-AS3 might be associated with glycosylationrelated diseases. Discussion: It was demonstrated that HIF1A-AS3, a hypoxia-induced long non‑coding RNA, acted as a critical regulator of glycolytic reprogramming in MSCs. Additionally, HIF1A-AS3 upregulated a distinct subset of interferon‑stimulated genes, suggesting a potential link between metabolic reprogramming and immunomodulation in MSCs. Further mechanistic studies are warranted to elucidate how HIF1A-AS3 regulates these processes. Conclusion: The study reveals that HIF1A-AS3 is a regulator of the metabolic reprogramming of glycolysis in MSCs. These findings provide new insights into understanding the metabolic regulatory mechanism of MSCs.
Introduction/ Objective: Neutrophils are crucial for an effective innate immune response. However, overactivation is associated with chronic inflammation, as in systemic lupus erythematosus (SLE). Gingival mesenchymal stromal cells (GMSCs) are used as anti-inflammatory therapies because they possess strong immunomodulatory properties, primarily acting through paracrine mechanisms. GMSCs exhibit immunoplasticity in response to their microenvironment and adjust their secretion profile. This study aimed to investigate the effects of conditioned media derived from human gingival mesenchymal stromal cells (hGMSC-CM) or from cells pretreated with IFNγ (hGMSCγ- CM) on neutrophil antimicrobial and proinflammatory functions. METHODS:hGMSCs were isolated to meet the criteria of the International Society for Cell & Gene Therapy (ISCT). Neutrophil intracellular reactive oxygen species (ROS) production; neutrophil elastase (NE), cathepsin G (CG), and myeloperoxidase (MPO) enzymatic activities; induction of lytic and vital neutrophil extracellular traps (NETs); and bacterial uptake and engulfment were analyzed using flow cytometry, photometric methods, and fluorescence and confocal microscopy. RESULTS:Both hGMSC-derived CMs significantly reduced intracellular ROS levels, reduced the enzymatic activities of MPO, CG, and NE by decreasing degranulation, and diminished NET formation (DNA, LL37, and PAD4) through both the lytic and vital pathways, including NET production observed in an inflammatory environment using plasma from SLE patients. DISCUSSION:These inhibitory effects were more pronounced with hGMSCγ-CM. Interestingly, hGMSCγ-CM did not impair bacterial uptake, engulfment, or neutrophil microbicidal activity against Staphylococcus aureus and Escherichia coli, thereby maintaining the functional balance of neutrophils. CONCLUSION:These findings support the use of hGMSCγ-CM as a cell-free biological product for therapies targeting inflammation driven by neutrophil overactivation.
An abdominal aortic aneurysm (AAA) is a serious vascular disease characterized by progressive dilation of the abdominal aorta, resulting in an increased risk of rupture. AAA develops through multiple pathogenic mechanisms, including chronic inflammation, extracellular matrix (ECM) degradation, oxidative stress, and vascular smooth muscle cell (VSMC) apoptosis. Surgical intervention is the primary treatment for AAA; however, no effective pharmacological therapies are currently available to halt or reverse disease progression. This review evaluates the therapeutic potential of multipotent mesenchymal stromal/stem cells (MSCs) for AAA, with particular emphasis on their immunomodulatory and regenerative properties. Preclinical studies suggest that MSCs can attenuate AAA progression in animal models by modulating the inflammatory microenvironment, reducing matrix metalloproteinase activity, and promoting tissue repair. In addition, interactions between MSCs and various immune cells decrease inflammatory responses, thereby positively impacting the structure of the aortic wall. Collectively, the available evidence highlights the broad therapeutic potential of MSCs in modulating key molecular and cellular pathways involved in AAA progression. Given their ability to modulate the immune system and promote vascular regeneration, MSCs may have significant potential for developing disease-modifying therapies for AAA. By targeting key pathogenic processes involved in AAA progression, MSCs offer the potential to complement existing surgical management and address mechanisms that are not targeted by current therapies. However, additional well-designed laboratory-based and clinical studies are needed to optimize MSC-based therapeutic strategies and to establish their long-term efficacy and safety before clinical translation.
Introduction: Mesenchymal stem cells (MSCs) possess immunomodulatory and tissuereparative properties and have shown therapeutic potential in acute lung injury (ALI). However, the mechanisms underlying their protective effects remain unclear. This study aimed to evaluate the effects of MSCs on bleomycin-induced ALI and to explore the underlying molecular mechanisms. Methods: A bleomycin-induced ALI mouse model was established, followed by human umbilical cord-derived MSC administration. Lung injury, pulmonary edema, neutrophil infiltration, and apoptosis of alveolar type II epithelial cells (AT2) were assessed. RNA-seq and molecular validation were performed using sorted AT2 cells to investigate the underlying mechanism. In vitro assays were carried out to examine the role of Ntrk2 in MSC-mediated epithelial repair. Results: MSC treatment alleviated lung injury, improved alveolar structure, reduced pulmonary edema, and decreased neutrophil infiltration and AT2 cell apoptosis. RNA-seq and molecular analyses indicated that MSCs regulated Ntrk2 expression by suppressing NF-κB signaling and enhancing STAT3 signaling, thereby promoting alveolar epithelial regeneration. In vitro, inhibition of Ntrk2 impaired the promotive effects of MSCs on A549 cell migration and alveolar organoid repair. Discussion: These findings suggest that MSCs protect against ALI by attenuating inflammatory injury and promoting alveolar epithelial repair, with the NF-κB/STAT3-Ntrk2 axis contributing to this process. Conclusion: MSC treatment ameliorated bleomycin-induced ALI and promoted alveolar epithelial regeneration, at least partly through the NF-κB/STAT3-Ntrk2 axis. These results provide further mechanistic support for MSC-based therapy in ALI.
