Proteomic analysis and identification reveal the anti-inflammatory mechanism of clofazimine on lipopolysaccharide-induced acute lung injury in mice.

BACKGROUND AND OBJECTIVE: Acute lung injury (ALI)/ acute respiratory distress syndrome (ARDS) was increasingly recognized as one of the most severe acute hyperimmune response of coronavirus disease 2019 (COVID-19). Clofazimine (CFZ) has attracted attention due to its anti-inflammatory property in immune diseases as well as infectious diseases. However, the role and potential molecular mechanism of CFZ in anti-inflammatory responses remain unclear. METHODS: We analyze the protein expression profiles of CFZ and LPS from Raw264.7 macrophages using quantitative proteomics. Next, the protective effect of CFZ on LPS-induced inflammatory model is assessed, and its underlying mechanism is validated by molecular biology analysis. RESULTS: LC-MS/MS-based shotgun proteomics analysis identified 4746 (LPS) and 4766 (CFZ) proteins with quantitative information. The key proteins and their critical signal transduction pathways including TLR4/NF-κB/HIF-1α signaling was highlighted, which was involved in multiple inflammatory processes. A further analysis of molecular biology revealed that CFZ could significantly inhibit the proliferation of Raw264.7 macrophages, decrease the levels of TNF-α and IL-1ß, alleviate lung histological changes and pulmonary edema, improve the survival rate, and down-regulate TLR4/NF-κB/HIF-1α signaling in LPS model. CONCLUSION: This study can provide significant insight into the proteomics-guided pharmacological mechanism study of CFZ and suggest potential therapeutic strategies for infectious disease.

Prognostic factors and survival outcome of primary pulmonary acinar cell carcinoma.

PURPOSE: The objective of our study was to investigate the epidemiologic characteristics and prognostic factors in patients with pulmonary acinar cell carcinoma (PACC). METHODS: PACC patients diagnosed between 1975 and 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The trend in PACC incidence was assessed using joinpoint regression software. Overall survival (OS) and disease-specific survival (DSS) were evaluated using the Kaplan-Meier method and log-rank test. Univariate and multivariate Cox regression analysis was performed to identify the independent prognostic factors for OS and DSS. Nomograms to predict survival possibilities were constructed based on the identified independent prognostic factors. RESULTS: A total of 2918 patients were identified with PACC. The mean age was 65.2 ± 8.95 years with a female to male of 1.6:1. The incidence of PACC steadily increased by an annual percentage change (APC) of 3.2% (95% CI 2.1-4.4, p < 0.05). Multivariate Cox regression analysis revealed that age, gender, race, stage, grade, tumor size, number of positive lymph nodes, surgery, and chemotherapy were independent prognostic factors for survival. Nomograms specifically for PACC were constructed to predict 1- and 5-year OS and DSS possibility, respectively. The concordance index (C-index) and calibration plots showed the established nomograms had robust and accurate performance. CONCLUSION: PACC was rare but the incidence has been steadily increasing over the past four decades. Survival has improved in recent years. Surgery or chemotherapy could provide better OS and DSS. The established nomograms specifically for PACC were robust and accurate in predicting 1- and 5-year OS and DSS.

Downregulation of DNMT3a expression by RNAi and its effect on NF-κBs expression of thymic epithelial cells.

OBJECTIVE: To understand the characteristics of DNA methyltransferase 3a (DNMT3a) in thymoma associated Myasthenia Gravis reveal its transcriptional regulator network as while as analyze the effect of DNMT3a on Rel/ nuclear factor-kappaB family (RelA/RelB) and its downstream autoimmune regulatory factor (Aire). METHODS: Tissues of 30 patients with thymoma, with or without myasthenia gravis (MG), were collected and the DNMT3a protein expression were evaluated through immunohistochemistry. We performed mRNA expression profiling microarray detection and analysis, and integrated the analysis by constructing protein-protein interaction networks and the integration with other database. We identified molecular difference between low and high DNMT3a in the thymoma by heatmap. We also performed PCR validation in thymoma tissues. The DNMT3a-shRNA plasmid was transfected into TEC cells, and these cells were treated with 5-aza-2-deoxycytidine, a blocker of DNMT3a. After the down-regulation of DNMT3a in TEC cells, the transcript and protein levels of RelA, RelB, Aire, and CHRNA3 were evaluated by western blotting. In addition, changes in gene expression profiles were screened through microarray technology. We performed differential gene analysis in the thymoma cohort by heatmap with R (v.4.3.0) software. RESULTS: In 30 matched tissue specimens, the expression of DNMT3a protein in thymoma with MG was lower than that in thymoma. Through mRNA expression profiling analysis, we constructed a co-expression network of DNMT3a and found direct interaction between IKZF1 and DNMT3a, and this co-expression relationship was overlappted with Cistrome DB database. We found up-regulation of 149 mRNAs and repression of 177 mRNAs in thymoma with MG compared with thymoma. Gene ontology and pathway analysis show the involvement of a multitude of genes in the mis-regulation of MG-related pathways. RNA interference significantly reduced the level of mRNA of DNMT3a, which proved that plasmid DNMT3a was effective. In comparison to the control group, the levels of DNMT3a, Aire, and CHRNA3 mRNA and protein in TEC cells transfected with DNMT3a-shRNA interference plasmid were significantly decreased, while the expression level of RelA and RelA/RelB was significantly increased. CONCLUSIONS: Our study reveals the DNMT3a-NF-κB pathway has a major effect on MG, and can be used as a marker for diagnosis as well as a target for MG treatment.