Anti-inflammatory protein TSG-6 secreted by BMSCs attenuates silica-induced acute pulmonary inflammation by inhibiting NLRP3 inflammasome signaling in macrophages.

Silicosis is a severe occupational lung disease caused by inhalation of silica particles. Unfortunately, there are currently limited treatment options available for silicosis. Recent advances have indicated that bone marrow mesenchymal stem cells (BMSCs) have a therapeutic effect on silicosis, but their efficacy and underlying mechanisms remain largely unknown. In this study, we focused on the early phase of silica-induced lung injury to investigate the therapeutic effect of BMSCs. Our findings demonstrated that BMSCs attenuated silica-induced acute pulmonary inflammation by inhibiting NLRP3 inflammasome pathways in lung macrophages. To further understand the mechanisms involved, we utilized RNA sequencing to analyze the transcriptomes of BMSCs co-cultured with silica-stimulated bone marrow-derived macrophages (BMDMs). The results clued tumor necrosis factor-stimulated gene 6 (TSG-6) might be a potentially key paracrine secretion factor released from BMSCs, which exerts a protective effect. Furthermore, the anti-inflammatory and inflammasome pathway inhibition effects of BMSCs were attenuated when TSG-6 expression was silenced, both in vivo and in vitro. Additionally, treatment with exogenous recombinant mouse TSG-6 (rmTSG-6) demonstrated similar effects to BMSCs in attenuating silica-induced inflammation. Overall, our findings suggested that BMSCs can regulate the activation of inflammasome in macrophages by secreting TSG-6, thereby protecting against silica-induced acute pulmonary inflammation both in vivo and in vitro.

Carbon Ion Irradiation Enhances the Anti-tumor Efficiency in Tongue Squamous Cell Carcinoma via Modulating the FAK Signaling.

Oral cancer is a very aggressive disease with high rates of recurrence and metastasis. This study aimed at addressing how efficiently tongue cancer is suppressed after carbon ion irradiation. Here, the close relationship between upregulated expression of focal adhesion kinase (FAK) and high metastatic status in tongue squamous cell carcinoma patients was validated using bioinformatics and immunohistochemical analyses. Our data indicated that FAK suppression significantly enhanced the killing effect induced by irradiation in the tongue cancer cell line CAL27, as evidenced by increased apoptotic induction and reduced colony formation. More importantly, in FAK-deficient cells, carbon ion irradiation was shown to remarkably inhibit migration and invasion by delaying wound healing and slowing down motility. Further studies revealed that irradiation exposure caused disorganization of the actin cytoskeleton and reduced cell adhesive energy in FAK-deficient cells. Moreover, carbon ion treatment, in combination with FAK silencing, markedly blocked the phosphorylation levels of FAK, and paxillin, which partly contributed to the reduced motility of tongue squamous cell carcinoma CAL27 cells. Collectively, these results suggest that the prominent obstructing role of carbon ion irradiation in the growth inhibition and metastatic behavior of tumors, including attenuation of cell adhesiveness, motility, and invasiveness, could be distinctly modulated by FAK-mediated downstream pathways.

Identification and validation of seven prognostic long non-coding RNAs in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is one of the most common malignancies worldwide, due to poor diagnosis and treatment. There is increasing evidence that demonstrates the involvement of long non-coding RNAs (lncRNAs) in carcinogenesis and cancer progression. Therefore, the aim of the present study was to explore potential lncRNA-associated features of patients with OSCC as a valuable and independent prognostic biomarker. A total of 268 lncRNA expression profiles and clinical patient information on OSCC were downloaded from The Cancer Genome Atlas database. The clinical information was exploited for prescreening, using Cox regression analysis, and differentially expressed lncRNAs (DElncRNAs) were identified using edgeR software. Using the 'caret' package, the datasets were categorized into test datasets and training datasets, respectively. Through bioinformatics, seven prognostic DElncRNAs were selected. Using the regression coefficients, a risk score based on the seven-DElncRNA signature was developed to assess the prognostic function of key DElncRNAs. According to the median risk score, patients were classified into high-risk and low-risk groups in the training and test datasets. Additionally, receiver operating characteristic (ROC) curve analysis was conducted to evaluate the sensitivity and specificity of the prognostic DElncRNAs, and the optimal cut-off point was obtained from ROC analysis. Based on the optimal cut-off point, the patients were also categorized into high-risk and low-risk groups. Notably, the optimal cut-off point was more sensitive than the median risk score, particularly in the test dataset. The Kaplan-Meier survival and log rank test analysis results indicated that the P-value, based on the optimal cut-off, was less than the median risk cut-off. Additionally, stratified analysis results revealed that the seven-DElncRNAs signature was also independent of OSCC age. Furthermore, the findings of the present study suggested that the seven-DElncRNA signature can be used as a potential prognostic indicator and may have important clinical significance in OSCC.