Endothelial cell-derived extracellular vesicles modulate the therapeutic efficacy of mesenchymal stem cells through IDH2/TET pathway in ARDS.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe and fatal disease. Although mesenchymal stem cell (MSC)-based therapy has shown remarkable efficacy in treating ARDS in animal experiments, clinical outcomes have been unsatisfactory, which may be attributed to the influence of the lung microenvironment during MSC administration. Extracellular vesicles (EVs) derived from endothelial cells (EC-EVs) are important components of the lung microenvironment and play a crucial role in ARDS. However, the effect of EC-EVs on MSC therapy is still unclear. In this study, we established lipopolysaccharide (LPS) - induced acute lung injury model to evaluate the impact of EC-EVs on the reparative effects of bone marrow-derived MSC (BM-MSC) transplantation on lung injury and to unravel the underlying mechanisms. METHODS: EVs were isolated from bronchoalveolar lavage fluid of mice with LPS - induced acute lung injury and patients with ARDS using ultracentrifugation. and the changes of EC-EVs were analysed using nanoflow cytometry analysis. In vitro assays were performed to establish the impact of EC-EVs on MSC functions, including cell viability and migration, while in vivo studies were performed to validate the therapeutic effect of EC-EVs on MSCs. RNA-Seq analysis, small interfering RNA (siRNA), and a recombinant lentivirus were used to investigate the underlying mechanisms. RESULTS: Compared with that in non-ARDS patients, the quantity of EC-EVs in the lung microenvironment was significantly greater in patients with ARDS. EVs derived from lipopolysaccharide-stimulated endothelial cells (LPS-EVs) significantly decreased the viability and migration of BM-MSCs. Furthermore, engrafting BM-MSCs pretreated with LPS-EVs promoted the release of inflammatory cytokines and increased pulmonary microvascular permeability, aggravating lung injury. Mechanistically, LPS-EVs reduced the expression level of isocitrate dehydrogenase 2 (IDH2), which catalyses the formation of α-ketoglutarate (α-KG), an intermediate product of the tricarboxylic acid (TCA) cycle, in BM-MSCs. α-KG is a cofactor for ten-eleven translocation (TET) enzymes, which catalyse DNA hydroxymethylation in BM-MSCs. CONCLUSIONS: This study revealed that EC-EVs in the lung microenvironment during ARDS can affect the therapeutic efficacy of BM-MSCs through the IDH2/TET pathway, providing potential strategies for improving the therapeutic efficacy of MSC-based therapy in the clinic.

Development of genomic phenotype and immunophenotype of acute respiratory distress syndrome using autophagy and metabolism-related genes.

Background: Distinguishing ARDS phenotypes is of great importance for its precise treatment. In the study, we attempted to ascertain its phenotypes based on metabolic and autophagy-related genes and infiltrated immune cells. Methods: Transcription datasets of ARDS patients were obtained from Gene expression omnibus (GEO), autophagy and metabolic-related genes were from the Human Autophagy Database and the GeneCards Database, respectively. Autophagy and metabolism-related differentially expressed genes (AMRDEGs) were further identified by machine learning and processed for constructing the nomogram and the risk prediction model. Functional enrichment analyses of differentially expressed genes were performed between high- and low-risk groups. According to the protein-protein interaction network, these hub genes closely linked to increased risk of ARDS were identified with CytoHubba. ssGSEA and CIBERSORT was applied to analyze the infiltration pattern of immune cells in ARDS. Afterwards, immunologically characterized and molecular phenotypes were constructed according to infiltrated immune cells and hub genes. Results: A total of 26 AMRDEGs were obtained, and CTSB and EEF2 were identified as crucial AMRDEGs. The predictive capability of the risk score, calculated based on the expression levels of CTSB and EEF2, was robust for ARDS in both the discovery cohort (AUC = 1) and the validation cohort (AUC = 0.826). The mean risk score was determined to be 2.231332, and based on this score, patients were classified into high-risk and low-risk groups. 371 differential genes in high- and low-risk groups were analyzed. ITGAM, TYROBP, ITGB2, SPI1, PLEK, FGR, MPO, S100A12, HCK, and MYC were identified as hub genes. A total of 12 infiltrated immune cells were differentially expressed and have correlations with hub genes. According to hub genes and implanted immune cells, ARDS patients were divided into two different molecular phenotypes (Group 1: n = 38; Group 2: n = 19) and two immune phenotypes (Cluster1: n = 22; Cluster2: n = 35), respectively. Conclusion: This study picked up hub genes of ARDS related to autophagy and metabolism and clustered ARDS patients into different molecular phenotypes and immunophenotypes, providing insights into the precision medicine of treating patients with ARDS.