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Purpose: Previous studies have reported that miR-30d-5p gene expression can inhibit tumor proliferation, but its mechanism has not been fully elucidated. Methods: Based on previous findings, TGF-β1 was used to induce epithelial mesenchymal transformation in A549 cells. The expression levels of DUSP-1, E-cadherin and Vimentin were detected by Western blot. mRNA expression levels of DUSP-1, E-cadherin and Vimentin were determined by RT-qPCR. The expression level of miR-30d-5p was determined by RT-qPCR. Results: The induction effect of TGF-β1 could be reversed by the intervention of miR-30d-5p in A549 cells. miRNA inhibition experiment showed that miR-30d-5p inhibitor could effectively inhibit the expression of miR-30d-5p in A549 cells. After miR-30d-5p intervention, TGF-β1 was reversed on EMT-related genes (Dusp-1, E-cadherin, Vimentin). Conclusion: TGF-β1 can induce epithelial mesenchymal transformation of A549 cells, and miR-30d-5p may be a key regulatory mechanism in regulating gene and protein expression of TGF-β1-mediated DUSP-1, E-cadherin and Vimentin. This provides a new perspective for understanding the anti-tumor effect of miR-30d-5p gene.

The pathogenesis of rheumatoid arthritis (RA) remains elusive. The initiation of joint degeneration is characterized by the loss of self-tolerance in peripheral joints. Ferroptosis, a form of regulated cell death, holds significant importance in the pathophysiology of inflammatory arthritis, primarily due to iron accumulation and the subsequent lipid peroxidation.The present study investigated the association between synovial lesions and ferroptosis-related genes using previously published data from rheumatoid patients. Transcriptome differential gene analysis was employed to identify ferroptosis-related differentially expressed genes (FRDEGs). To validate FRDEGs and screen hub genes, we used weighted gene co-expression network analysis (WGCNA) and receiver operating characteristic (ROC) curves. Subsequently, immune infiltration analysis and single cell analysis were conducted to investigate the relationship between various synovial tissues cells and FRDEGs. The findings were further confirmed through reverse transcription-quantitative polymerase chain reaction (RT-qPCR), immunohistochemical staining, and immunofluorescence techniques.Upon intersecting DEGs with ferroptosis-related genes, we identified a total of 104 FRDEGs. Through the construction of a protein-protein interaction (PPI) network, we pinpointed the top 20 most highly concentrated genes as hub genes. Subsequent analyses using ROC curve and WGCNA validated eight FRDEGs: TIMP1, JUN, EGFR, SREBF1, ADIPOQ, SCD, AR, and FABP4. Immuno-infiltration analyses revealed significant infiltration of immune cell in RA synovial tissues and their correlations with the FRDEGs. Notably, TIMP1 demonstrated a positive correlation with various immune cell populations. Single-cell sequencing date of RA synovial tissue revealed predominant expression of TIMP1 is in fibroblasts. RT–qPCR, immunohistochemistry, and immunofluorescence analyses confirmed significant upregulation of TIMP1 at both mRNA and protein levels in RA synovial tissues and fibroblast-like synoviocytes (FLS).The findings provide novel insights into pathophysiology of peripheral immune tolerance deficiency in RA. The dysregulation of TIMP1, a gene associated with ferroptosis, was significantly observed in RA patients, suggesting its potential as a promising biomarker and therapeutic target.

Background: Glioma is the most frequent type of malignancy that may damage the brain with high morbidity and mortality rates and patients' prognoses are still dismal. Ferroptosis, a newly uncovered mode of programmed cell death, may be triggered to destroy glioma cells. Nevertheless, the significance of ferroptosis-related genes (FRGs) in predicting prognosis in glioma individuals is still a mystery. Methods: The CGGA (The Chinese Glioma Atlas), GEO (Gene Expression Omnibus), and TCGA (The Cancer Genome Atlas) databases were all searched to obtain the glioma expression dataset. First, TCGA was searched to identify differentially expressed genes (DEGs). This was followed by a machine learning algorithm-based screening of the glioma's most relevant genes. Additionally, these genes were subjected to Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) functional enrichment analyses. The chosen biological markers were then submitted to single-cell, immune function, and gene set enrichment analysis (GSEA). In addition, we performed functional enrichment and Mfuzz expression profile clustering on the most promising biological markers to delve deeper into their regulatory mechanisms and assess their clinical diagnostic capacities. Results: We identified 4444 DEGs via differential analysis and 564 FRGs from the FerrDb database. The two were subjected to intersection analysis, which led to the discovery of 143 overlapping genes. After that, glioma biological markers were identified in fourteen genes by the use of machine learning methods. In terms of its use for clinical diagnosis, SMG9 stands out as the most significant among these biomarkers. Conclusion: In light of these findings, the identification of SMG9 as a new biological marker has the potential to provide information on the mechanism of action and the effect of the immune milieu in glioma. The promise of SMG9 in glioma prognosis prediction warrants more study.

Background: Diabetic kidney disease (DKD) is a common and potentially fatal consequence of diabetes. Chronic renal failure or end-stage renal disease may result over time. Numerous studies have demonstrated the function of the microbiota in health and disease. The use of advanced urine culture techniques revealed the presence of resident microbiota in the urinary tract, undermining the idea of urine sterility. Studies have demonstrated that the urine microbiota is related with urological illnesses; nevertheless, the fundamental mechanisms by which the urinary microbiota influences the incidence and progression of DKD remain unclear. The purpose of this research was to describe key characteristics of the patients with DKD urinary microbiota in order to facilitate the development of diagnostic and therapeutic for DKD. Methods: We evaluated the structure and composition of the microbiota extracted from urine samples taken from DKD patients (n = 19) and matched healthy controls (n = 15) using 16S rRNA gene sequencing. Meanwhile, serum metabolite profiles were compared using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Associations between clinical characteristics, urine microbiota, and serum metabolites were also examined. Finally, the interaction between urine microbiota and serum metabolites was clarified based on differential metabolite abundance analysis. Results: The findings indicated that the DKD had a distinct urinary microbiota from the healthy controls (HC). Taxonomic investigations indicated that the DKD microbiome had less alpha diversity than a control group. Proteobacteria and Acidobacteria phyla increased in the DKD, while Firmicutes and Bacteroidetes decreased significantly (P

Among urological cancers, renal cancer has the highest fatality rate. In a previous pan-cancer study of the METTL family, we observed a stronger association between the METTL family members and the risk of renal cancer compared to other cancers. Among these members, METTL7A, a potential methyltransferase, was identified as a protective factor, although its role and mechanism in renal cancer remain unclear. In this study, we utilized public databases to examine the expression of METTL7A in renal cancer tissues and normal tissues and found that METTL7A expression was much lower in renal cancer tissues. We also noticed a link between low METTL7A expression and poor prognosis for patients. According to the results of our functional enrichment analysis, METTL7A may have a role in immunological functions in renal cancer. METTL7A expression was strongly linked with the degrees of immune cell infiltration and expression of numerous immunological components. METTL7A had significantly different effects on the survival times of renal cancer patients with high or low immune infiltration. Our findings suggest that METTL7A may be used as both a prognostic biomarker and an immunological target for kidney cancer. In conclusion, our study sheds light on the importance of METTL7A in renal cancer and emphasizes the potential of targeting METTL7A as a novel therapeutic strategy for kidney cancer.

Systemic lupus erythematous (SLE) is a complex chronic autoimmune disease with difficult early treatment and accurate diagnosis. Circulating exosomes containing proteins, lipids and nucleic acids can be ideal diagnostic biomarkers and disease management strategies for SLE. Our aim was to examine the unique expression profiles of circulating exosomal miRNAs and proteins in patients with SLE patients.Using RNA-sequencing and proteomic approaches, we compared the expression patterns of exosomal miRNAs and proteins in the plasma of SLE patients and healthy subjects, and discussed the underlying signaling network of circulating exosomes. We also summarize common molecules (miRNAs and proteins) and pathways shared by our plasma exosomes, as well as previously reported data (PBMC, T cells, B cells and plasma).We identified groups of differentially expressed exosomal miRNAs and proteins in the plasma of SLE patients and healthy controls. We obtained consensus molecules (39 miRNAs, 14 proteins) and 21 signaling pathways that are common in our current study and previous reports.Common molecules (miRNAs and proteins) and pathways shared by our plasma exosomes data and other circulating components data reported previously indicate their potential application in the clinical treatment and diagnosis of SLE disease.

Nowadays, among all urinary system cancers, the mortality of kidney cancer (KC) has risen to the first, and the incidence has been keeping on the third. Many recent studies have demonstrated that m6A modification regulated by the methyltransferases (writers) is closely related to the tumorigenesis of multiple cancers. In our previous study, we found that the methyltransferase METTL5 had a stronger association with the hazard ratio of KC more than most tumors, indicating its special function in carcinogenesis of KC. Until now, the expression, functions and mechanism of METTL5 in KC are still unclear. In this study, we analyzed the mRNA expression of METTL5 using the data sets from public databases, and revealed that the METTL5 expression was significantly up-regulated in tumor tissues of kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP) compared to normal tissues. Also, the METTL5 expression was correlated with the tumor stage and grade, indicating the potential involvement of METTL5 in tumor progression. Additionally, the higher expression of METTL5 predicted poorer prognosis of KIRC and KIRP patients. Subsequently, we revealed that the functions of METTL5 in KIRC might be related to immune modulation, because its co-expressed gene were enriched in immune-relevant pathways including Th17 cell differentiation, Th1 and Th2 cell differentiation, and phosphatidylinositol 3-kinase activity. Next, we disclosed that the METTL5 expression was correlated to the microenvironment score and immune score of KIRC and KIRP, and associated with the infiltration ratios of 25 types of immune cells. Besides, we demonstrated a wide difference of the METTL5's effect on the survival of patients with high and low immune infiltration, further suggesting METTL5 might affect tumor development via modulating the immune microenvironment. The findings of our study provide a novel potential prognostic biomarker and immune drug target for KC.