Characteristics of n6-methyladenosine (m6A) regulators and role of FTO/TNC in scleroderma.

BACKGROUND: m6A regulators have important roles in a variety of autoimmune diseases, but their potential function in scleroderma, a refractory connective tissue disease, remains unclear. Tenascin C (TNC) is known to be a factor promoting collagen deposition in the development of scleroderma, but the regulatory relationship between TNC and m6A regulators is unknown. METHODS: We extracted GSE33463 data consisting of forty-one healthy controls and sixty-one patients with scleroderma, and we analyzed the expression levels of twenty-one m6A regulators as well as the associations between them. In addition, we obtained random forest (RF) and nomogram models to predict the likehood of scleroderma. Next, we categorized the m6Aclusters and geneclusters by consensus clustering, and we performed an immune cell infiltration analysis for each cluster. Finally, we injected adenoviruses into a bleomycin (BLM)-induced mouse model of scleroderma, which was used to overexpress FTO and TNC. We assess the extent of skin fibrosis in the mice samples using pathology stains and measuring their hydroxyproline content and collagen mRNA. RESULTS: We initially identified fourteen differentially expressed m6A regulators (WTAP, RBM15, CBLL1, FTO, ALKBH5, YTHDC1, YTHDC2, YTHDF1, YTHDF2, YTHDF3, RBMX, HNRNPC, IGFBP1 and IGFBP2). We found ALKBH5 to be positively associated with CBLL1 and RBM15, and FTO to be negatively associated with WTAP. In addition, we identified four m6A regulators (CBLL1, IGFBP1, YTHDF2 and IGFBP2) using a RF model, and we designed a nomogram model with those variables that proved reliable according to the calibration curve and clinical impact curve. We found that the m6Acluster A was correlated with Type 1 T helper cell infiltration and the genecluster A was correlated with regulatory T cell infiltration. Finally, we showed that FTO overexpression downregulated the m6A and mRNA levels of TNC, and alleviated skin fibrosis in the mouse model of scleroderma. Thus, our overexpression experiments provide preliminary evidence suggesting that TNC is an adverse factor in scleroderma. CONCLUSION: Our approach might be useful as a new and accurate scleroderma diagnosis method. Moreover, our results suggested that FTO/TNC might be a novel scleroderma therapeutic target.

Discovering KYNU as a feature gene in hidradenitis suppurativa.

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic auto-inflammatory skin condition characterized by nodules, abscesses, and fistulae in skin folds. The underlying pathogenesis of HS remains unclear, and effective therapeutic drugs are limited. METHODS: We acquired mRNA expression profiles from the Gene Expression Omnibus (GEO) database and conducted differential expression analysis between control and HS samples using R software. Four machine learning algorithms (SVM, RF, ANN, and lasso) and WCGNA were utilized to identify feature genes. GO, KEGG, Metascape, and GSVA were utilized for the enrichment analysis. CIBERSORT and ssGSEA were employed to analyze immune infiltration. RESULTS: A total of 29 DEGs were identified, with the majority showing up-regulation in HS. Enrichment analysis revealed their involvement in immune responses and cytokine activities. KEGG analysis highlighted pathways such as IL-17 signaling, rheumatoid arthritis, and TNF signaling in HS. Immune infiltration analysis revealed the predominant presence of neutrophils, monocytes, and CD8 T cells. Machine learning algorithms and WCGNA identified KYNU as a feature gene associated with HS. We have also identified 59 potential drugs for HS based on the DEGs. Additionally, ceRNA network analysis identified the MUC19_hsa-miR-382-5p_KYNU pathway as a potential regulatory pathway. CONCLUSIONS: KYNU emerged as a feature gene associated with HS, and the ceRNA network analysis identified the MUC19_hsa-miR-382-5p_KYNU pathway as a potential regulator.

Bioinformatics-integrated screening of systemic sclerosis-specific expressed markers to identify therapeutic targets.

Background: Systemic sclerosis (SSc) is a rare autoimmune disease characterized by extensive skin fibrosis. There are no effective treatments due to the severity, multiorgan presentation, and variable outcomes of the disease. Here, integrated bioinformatics was employed to discover tissue-specific expressed hub genes associated with SSc, determine potential competing endogenous RNAs (ceRNA) regulatory networks, and identify potential targeted drugs. Methods: In this study, four datasets of SSc were acquired. To identify the genes specific to tissues or organs, the BioGPS web database was used. For differentially expressed genes (DEGs), functional and enrichment analyses were carried out, and hub genes were screened and shown in a network of protein-protein interactions (PPI). The potential lncRNA-miRNA-mRNA ceRNA network was constructed using the online databases. The specifically expressed hub genes and ceRNA network were validated in the SSc mouse and in normal mice. We also used the receiver operating characteristic (ROC) curve to determine the diagnostic values of effective biomarkers in SSc. Finally, the Drug-Gene Interaction Database (DGIdb) identified specific medicines linked to hub genes. Results: The pooled datasets identified a total of 254 DEGs. The tissue/organ-specifically expressed genes involved in this analysis are commonly found in the hematologic/immune system and bone/muscle tissue. The enrichment analysis of DEGs revealed the significant terms such as regulation of actin cytoskeleton, immune-related processes, the VEGF signaling pathway, and metabolism. Cytoscape identified six gene cluster modules and 23 hub genes. And 4 hub genes were identified, including Serpine1, CCL2, IL6, and ISG15. Consistently, the expression of Serpine1, CCL2, IL6, and ISG15 was significantly higher in the SSc mouse model than in normal mice. Eventually, we found that MALAT1-miR-206-CCL2, let-7a-5p-IL6, and miR-196a-5p-SERPINE1 may be promising RNA regulatory pathways in SSc. Besides, ten potential therapeutic drugs associated with the hub gene were identified. Conclusions: This study revealed tissue-specific expressed genes, SERPINE1, CCL2, IL6, and ISG15, as effective biomarkers and provided new insight into the mechanisms of SSc. Potential RNA regulatory pathways, including MALAT1-miR-206-CCL2, let-7a-5p-IL6, and miR-196a-5p-SERPINE1, contribute to our knowledge of SSc. Furthermore, the analysis of drug-hub gene interactions predicted TIPLASININ, CARLUMAB and BINDARIT as candidate drugs for SSc.

Comparison of the Efficacy of EGFR-TKIs Combined with Antiangiogenic Agents between Patients with Exon 19 Deletion and Patients with Exon 21 Leu858 Arg Mutation: A Systematic Review and Meta-Analysis.

Purpose: To compare the efficacy of EGFR-TKIs combined with antiangiogenic agents between non-small cell lung cancer patients with exon 19 deletion and patients with exon 21 Leu858 Arg mutation. Methods: Electronic databases (PubMed, Embase, and the Cochrane Central Register of Controlled Trials) were systematically searched for studies published until March 2022. Randomized control trials comparing the survival of EGFR-TKIs plus antiangiogenic agents with EGFR-TKI were extracted. The primary endpoint was progression-free survival (PFS). Results: Five randomized control trials involving 1533 patients were as follows: 818 patients had exon 19 deletion, and 715 patients with exon 21 Leu858 Arg mutation. The methodological quality of the 5 randomized control trials was high. EGFR-TKIs plus antiangiogenic agents improved PFS in patients with exon 19 deletion (hazard ratio [HR] = 0.62, 95% confidence interval [CI]: 0.51-0.75) and exon 21 Leu858 Arg mutation (HR = 0.61, 95% CI: 0.50-0.75). PFS did not differ between the exon 19 deletion and exon 21 Leu858 Arg mutation groups (Z = 0.07, P=0.94). Conclusions: PFS was comparable between patients receiving EGFR-TKIs combined with antiangiogenic agents with exon 19 deletion and those with exon 21 Leu858 Arg mutation.

Innate immune responses against the fungal pathogen Candida auris.

Candida auris is a multidrug-resistant human fungal pathogen responsible for nosocomial outbreaks worldwide. Although considerable progress has increased our understanding of the biological and clinical aspects of C. auris, its interaction with the host immune system is only now beginning to be investigated in-depth. Here, we compare the innate immune responses induced by C. auris BJCA001 and Candida albicans SC5314 in vitro and in vivo. Our results indicate that C. auris BJCA001 appears to be less immunoinflammatory than C. albicans SC5314, and this differential response correlates with structural features of the cell wall.