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Background Human urine-derived stem cells (USCs)-derived exosomes (USC-Exo) could improve kidney ischemia/reperfusion injury (IRI), while the underlying mechanisms of this protective effect remain unclear. Methods Human USCs and USC-Exo were isolated and verified by morphology and specific biomarkers. The effects of USC-Exo on ferroptosis and kidney injury were detected in the IRI-induced acute kidney injury (AKI) model in C57BL/6 mice. The effects of USC-Exo on ferroptosis and lncRNA taurine-upregulated gene 1 (TUG1) were detected in hypoxia/reoxygenation (H/R)-treated human proximal tubular epithelial cells (HK-2). The interaction of SRSF1 and TUG1, ACSL4 was checked via RNA pull-down/RIP and RNA stability assays. The effects of LncRNA TUG1 on SRSF1/ACSL4-mediated ferroptosis were verified in H/R-treated HK-2 cells and the IRI-induced AKI mouse models. Results USC-Exo treatment improved kidney injury and ameliorated ferroptosis in IRI-induced AKI mouse models. USC-Exo were rich in lncRNA TUG1, which suppressed ferroptosis in HK-2 cells exposed to H/R. Mechanistically, lncRNA TUG1 regulates the stability of ACSL4 mRNA by interacting with RNA-binding protein SRSF1. In addition, SRSF1 upregulation or ACSL4 downregulation partially reversed the protective effect of lncRNA TUG1 on ferroptosis in H/R-treated HK-2 cells. Further, ACSL4 upregulation partially reversed TUG1’s repression on kidney injury and ferroptosis in IRI-induced AKI mice. Conclusion Collectively, lncRNA TUG1 carried by USC-Exo regulated ASCL4-mediated ferroptosis by interacting with SRSF1 and then protected IRI-induced AKI. Potentially, USC-Exo rich in lncRNA TUG1 can serve as a promising therapeutic method for IRI-AKI.

BackgroundIschemia reperfusion injury (IRI) is an inevitable process in renal transplantation, which is closely related to serious postoperative complications such as delayed graft function (DGF), acute rejection and graft failure. Neutrophil extracellular traps (NETs) are extracellular DNA structures decorated with various protein substances released by neutrophils under strong signal stimulation. Recently, NETs have been found to play an important role in the process of IRI. This study aimed to comprehensively analyze the expression landscape of NET-related genes (NRGs) during IRI, identify clusters with different degrees of IRI and construct robust DGF and long-term graft survival predictive strategies.MethodsThe microarray and RNA-seq datasets were obtained from the GEO database. Differentially expressed NRGs (DE-NRGs) were identified by the differential expression analysis, and the NMF algorithm was used to conduct a cluster analysis of IRI samples. Machine learning algorithms were performed to screen DGF-related hub NRGs, and DGF and long-term graft survival predictive strategies were constructed based on these hub NRGs. Finally, we verified the expression of Cxcl1 and its effect on IRI and NETs generation in the mouse IRI model.ResultsThis study revealed two IRI clusters (C1 and C2 clusters) with different molecular features and clinical characteristics. Cluster C1 was characterized by active metabolism, mild inflammation and lower incidence of DGF, while Cluster C2 was inflammation activated subtype with a higher incidence of DGF. Besides, based on DGF-related hub NRGs, we successfully constructed robust DGF and long-term graft survival predictive strategies. The mouse renal IRI model verified that Cxcl1 was significantly upregulated in renal tissues after IRI, and using a CXCL8/CXCL1 inhibitor could significantly improve renal function, alleviate renal tubular necrosis, tissue inflammatory response, and NET formation.ConclusionThis study identified two distinct IRI clusters based on DE-NRGs and constructed robust prediction methods for DGF and graft survival, which can provide references for early prevention and individualized treatment of various postoperative complications after renal transplantation.

In response to strong signals, several types of immune cells release extracellular traps (ETs), which are web-like structures consisting of DNA decorated with various protein substances. This process is most commonly observed in neutrophils. Over the past two decades, ET formation has been recognized as a unique mechanism of host defense and pathogen destruction. However, the role of ETs in sterile inflammation has only been studied extensively in recent years. Ischemia reperfusion injury (IRI) is a type of sterile inflammatory injury. Several studies have reported that ETs have an important role in IRI in various organs. In this review, we describe the release of ETs by various types of immune cells and focus on the mechanism underlying the formation of neutrophil ETs (NETs). In addition, we summarize the role of ETs in IRI in different organs and their effects on tumors. Finally, we discuss the value of ETs as a potential therapeutic target for organ IRI and present possible challenges in conducting studies on IRI-related ETs as well as future research directions and prospects.

Background Renal cell carcinoma (RCC) is a third most common tumor of the urinary system. Nowadays, Immunotherapy is a hot topic in the treatment of solid tumors, especially for those tumors with pre-activated immune state. Methods In this study, we downloaded genomic and clinical data of RCC samples from The Cancer Genome Atlas (TCGA) database. Four immune-related genetic signatures were used to predict the prognosis of RCC by Cox regression analysis. Then we established a prognostic risk model consisting of the genes most related to prognosis from four signatures to value prognosis of the RCC samples via Kaplan–Meier (KM) survival analysis. An independent data from International Cancer Genome Consortium (ICGC) database were used to test the predictive stability of the model. Furthermore, we performed landscape analysis to assess the difference of gene mutant in the RCC samples from TCGA. Finally, we explored the correlation between the selected genes and the level of tumor immune infiltration via Tumor Immune Estimation Resource (TIMER) platform. Results We used four genetic signatures to construct prognostic risk models respectively and found that each of the models could divide the RCC samples into high- and low-risk groups with significantly different prognosis, especially in advanced RCC. A comprehensive prognostic risk model was constructed by 8 candidate genes from four signatures (HLA-B, HLA-A, HLA-DRA, IDO1, TAGAP, CIITA, PRF1 and CD8B) dividing the advanced RCC samples from TCGA database into high-risk and low-risk groups with a significant difference in cancer-specific survival (CSS). The stability of the model was verified by independent data from ICGC database. And the classification efficiency of the model was stable for the samples from different subgroups. Landscape analysis showed that mutation ratios of some genes were different between two risk groups. In addition, the expression levels of the selected genes were significantly correlated with the infiltration degree of immune cells in the advanced RCC. Conclusions Sum up, eight immune-related genes were screened in our study to construct prognostic risk model with great predictive value for the prognosis of advanced RCC, and the genes were associated with infiltrating immune cells in tumors which have potential to conduct personalized treatment for advanced RCC.

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IntroductionClear cell renal cell carcinoma (ccRCC) is a malignant tumor characterized by poor prognosis and difficult treatment. Ferroptosis is a relatively new form of programmed cell death that involved in cancer development and therapy resistance. Studies have shown that targeted ferroptosis may be a novel option for the treatment of ccRCC, but key genes and their roles between ferroptosis and ccRCC are limited so far. This study aims to develop a ccRCC stratified model based on ferroptosis-related genes to provide a reference for the prognosis prediction and the individualized treatment of ccRCC.Materials and MethodsThe mRNAs expression data of ccRCC and FRGs were obtained from TCGA and FerrDb database, respectively. Through multiple analysis, a 4-FRG based prognostic stratified model was constructed and its predictive performance was validated through various methods. Then, a nomogram based on the model was constructed and ccRCC patients stratified by the model were analyzed for tumor microenvironment, immune infiltration, sensitivity for immune checkpoint inhibitors (ICIs)/traditional anti-tumor therapy and tumor mutation burden (TMB). Functional enrichment analysis was performed to explore potential biological pathways. Finally, we verified our model by RT-qPCR, siRNA transfection, scratch assay and CCK-8 assay.ResultsIn this study, the stratified model and a model-based nomogram can accurately predict the prognosis of ccRCC patients in TCGA database. The patients stratified by the model showed different tumor microenvironments, immune infiltration, TMB, resistance to traditional and ICIs therapy, and sensitivity to ferroptosis. Functional enrichment analysis suggested several biological pathways related to the process and prognosis of ccRCC. RT-qPCR confirmed the differential expression of ferroptosis-related genes. Scratch assay and CCK-8 assay indicated the promotion effects of CD44 on the proliferation and migration of ccRCC.ConclusionIn this study, we established a novel ccRCC stratified model based on FRGs, which can accurately predict the prognosis of ccRCC patients and provide a reference for clinical individualized treatment.

Ferroptosis is a newly proposed programmed cell death that has great potential in limiting tumor progression and malignancies that are resistant to conventional therapies. However, recent reports have shown that ferroptosis in the tumor microenvironment can provide a favorable environment to promote tumor survival and progression, which is induced by the infiltration and polarization of pro-tumor immune cells and the dysfunction of anti-tumor immunity. In this mini-review, we introduce the mechanisms of ferroptosis, describe the crosstalk between ferroptosis and cancer, demonstrate the potential ways in which ferroptosis shapes the pro-tumor immune microenvironment, and present our thoughts on ferroptosis-based cancer therapies.