Background. MSC-derived extracellular vehicles (EVs) exhibit a protective functional role in renal ischemia/reperfusion injury (RIRI). Recent studies have revealed that mitophagy could be a potential target process in the treatment of RIRI. However, whether MSC-derived EVs are involved in the regulation of mitophagy in RIRI remains largely unknown to date. Methods. RIRI model was established in vivo in mice by subjecting them to renal ischemia/reperfusion. TCMK-1 cells were subjected to hypoxia/reoxygenation (H/R) stimulation to mimic RIRI in vitro. BMSCs and BMSC-derived EVs were isolated and identified. Renal injury was assessed using H&E staining. The qPCR and western blot analyses were conducted to detect the mRNA and protein levels. Apoptosis was evaluated using the TUNEL assay and flow cytometry analysis. The EVs, autophagosomes, and mitochondria were observed using TEM. The colocalization of autophagosomes with mitochondria was confirmed through the confocal assay. The direct binding of miR-223-3p to NLRP3 was validated through the dual-luciferase assay. Results. BMSCs and BMSC-derived EVs were successfully isolated from mice and identified. The protective effect of BMSC-derived EVs against RIRI was validated both in vitro and in vivo, which was indicated by a decrease in apoptosis and inflammasome activation and an increase in mitophagy. However, this protective effect was impaired in the miR-223-3p-depleted EVs, suggesting that miR-223-3p mediated this protective effect. Further mechanistic investigation revealed that miR-223-3p suppressed inflammasome activation to enhance mitophagy by directly targeting NLRP3. Conclusion. In conclusion, the protective role of BMSC-derived EVs and exosome-delivered miR-223-3p in RIRI was validated. Exogenous miR-223-3p directly targeted NLRP3 to attenuate inflammasome activation, thereby promoting mitophagy.
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.
Background: With the development of information communication technology (ICT), telemedicine has become a promising option for patients with chronic diseases who need continuous monitoring at home or in remote health care facilities. As cardiovascular disease (CVD) is responsible for an estimated 17.9 million deaths globally each year, it is appropriate to evaluate the effectiveness of telemedicine for the health care management of CVD patients. Methods:The Library of Congress, LISTA (EBSCO), PubMed (NLM), and Web of Science databases were searched with a date limitation from 1 January 2000 until 5 August 2021 for Randomized Controlled Trial (RCT) studies. Two independent researchers screened the records for inclusion and extracted the data for synthesis, supported by RevMan 5.0 software. As one of the clinical outcomes, the mean difference and standard deviation of systolic blood pressure were synthesized. For the Quality-of-life measures, EuroQol-5D (EQ-5D) scores were also synthesized and for the depression level, CESD-10 scores were synthesized. Results:We identified 23 studies for qualitative analysis and 21 studies for quantitative analysis. 21 studies included systolic blood pressure as an outcome measure and the results show a statistical difference (P<0.05) between the intervention group and the control group and a favorable inclination toward the Telemedicine enhanced health care program over the usual care. Of the six studies that included body mass index (BMI) as an outcome measure, there was no significant difference in BMI between the telemedicine and usual health care groups. A total of five studies assessed patients' quality of life using the EQ-5D instrument.After excluding one study following the sensitivity analysis, telemedicine was shown to significantly improve patients' quality of life. Three studies that investigated patients' mental health (CSE-D-10) also showed a significantly beneficial effect of telemedicine over usual health care.Discussion: This review found limited evidence to support some of the outcomes in the original study designs. Overall, our findings suggested a favorable effect of telemedicine intervention in the field of health care for CVD patients. Due to the unavoidable heterogeneity within the selected literature, a more detailed investigation and analysis of the unclear outcomes is recommended.
Background: Renal cell carcinoma (RCC) accounts for 2% to 3% of all human malignancies and is the 9th most common malignancy in Western countries. Due to the development of surgical procedures and the use of novel drugs, survival has been significantly prolonged. However, current challenges include how to diagnose RCC earlier and how to overcome drug resistance. Methods: We explored the relationship between the transcription level of IFI16 and clinical data in RCC through various online databases, including ONCOMINE, GEPIA, HPA, Timer and COEXPEDIA. Results: In comparison with corresponding normal tissues, IFI16 mRNA expression levels were higher in kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP) tissues. In KIRC, the higher expression of IFI16 was associated with lower overall survival (P = .037). In KIRP, the higher expression IFI16 was associated with lower disease-free survival and overall survival (P = .037 and P = .011). In contrast, the IFI16 expression was negatively correlated with tumor purity in kidney chromophobe, KIRC and KIRP (all P < .05). In KIRC and KIRP, the expression of IFI16 was positively correlated with tumor-infiltrating immune cells (TIICs) (all P < .05), except macrophages in KIRP. In KIRC, the main TIICs were B cells, CD4+T cells, neutrophils, and dendritic cells, while the main TIICs in the high amplification state were macrophage (all P < .0001). Functional enrichment analysis by gene ontology and Kyoto Encyclopedia of Genes and Genomes highlighted enrichment of neutrophil degranulation, phagocytosis and vesicle-mediated transport regulation, and pathways including tuberculosis, toxoplasmosis, phagosome, leishmaniasis, and Fc gamma R-mediated. Conclusions: IFI16 is overexpressed in RCC and may be an important oncogene in the progression of kidney. In addition, IFI16 may a marker for RCC diagnosis and prognosis, which may be related to immune infiltration.
Bladder cancer (BC) is a commonly occurring malignant tumor affecting the urinary tract. Zinc finger proteins (ZNFs) constitute the largest transcription factor family in the human genome and are therefore attractive biomarker candidates for BC prognosis. In this study, we profiled the expression of ZNFs in The Cancer Genome Atlas (TCGA) BC cohort and developed a novel prognostic signature based on 7 ZNF-coding genes. After external validation of the model in the GSE48276 dataset, we integrated the 7-ZNF-gene signature with patient clinicopathological data to construct a nomogram that forecasted 1-, 2-, and 3-year OS with good predictive accuracy. We then accessed The Genomics of Drug Sensitivity in Cancer database to predict the therapeutic drug responses of signature-defined high- and low-risk BC patients in the TCGA cohort. Greater sensitivity to chemotherapy was revealed in the low-risk group. Finally, we conducted gene set enrichment analysis of the signature genes and established, by applying the ESTIMATE algorithm, distinct correlations between the two risk groups and the presence of stromal and immune cell types in the tumor microenvironment. By allowing effective risk stratification of BC patients, our novel ZNF gene signature may enable tailoring more intensive treatment for high-risk patients.
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