Synaptotagmins are a class of proteins that play an important role in the secretion of neurotransmitters by synaptic vesicles. However, recent studies have shown that members of this family also have a certain function in the development of tumors. In this study, we first identified through The Cancer Genome Atlas data analyzed that a novel synaptotagmin, SYT13, was closely related to the prognosis of lung adenocarcinoma, but was not significantly correlated with the prognosis of lung squamous cell carcinoma. Then we knocked down the expression of SYT13 gene in lung adenocarcinoma cell lines A549 and H1299, and successfully induced decreased proliferation and clonality of lung adenocarcinoma cell lines, and observed cell cycle arrest and apoptosis enhancement in both cell lines. In addition, we detected the migration ability of SYT13 knockdown lung adenocarcinoma cell lines by the cell scratch test and the transwell test. Interestingly, there was a decreased migration ability of SYT13 knockdown in H1299 cells even though there was no significant difference in the migration of A549 cells. These results demonstrate that SYT13 plays an important role in the development of lung adenocarcinoma, which deepens our understanding of the mechanism of lung adenocarcinoma development and provides new possibilities for targeted therapy of lung adenocarcinoma.

Background: Dermatomyositis (DM) is a systemic autoimmune inflammatory disorder that affects primarily skin, muscle and lung, frequently associated with interstitial lung disease (ILD). The objective of this study is to investigate the association between serum cytokines and clinical severity in patients with DM-ILD. Methods: Serum samples of 30 healthy controls, 14 DM patients without ILD and 40 DM patients with ILD were collected. Serum S100A8/A9 levels were analyzed by enzyme-linked immunosorbent assay (ELISA) and levels of interleukins were measured by cytometric beads array (CBA). Then we performed multivariate logistic regression analysis to determine factors independently associated with ILD development. Results: Serum IL-4, IL-6 and S100A8/A9 levels were significantly higher in DM patients with ILD than those in healthy controls (p = 0.0013, 0.0017 and < 0.0001, respectively). Serum IL-10 level of patients was dramatically lower than that in controls (p = 0.0001).

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Objective: S100A12 is an emerging inflammatory disease biomarker. Interstitial lung disease (ILD) is a common, severe complication of dermatomyositis (DM). This study was performed to investigate the association between S100A12 and disease activity and prognosis in patients with DM-associated ILD (i.e., DM-ILD). Methods: Serum S100A12 levels were measured using enzyme-linked immunosorbent assays in patients with stable DM-ILD, patients with acute exacerbation of DM-ILD (AE DM-ILD), and healthy controls (HCs). The relationships of serum S100A12 levels with C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), ferritin, high-resolution computed tomography (HRCT) scores, and pulmonary functions were evaluated by multiple unpaired t-tests and Pearson correlation. Results: Serum S100A12 levels were higher in patients with stable DM-ILD and those with AE DM-ILD than in HCs. Serum S100A12 levels in patients with stable DM-ILD and those with AE DM-ILD were positively correlated with CRP, ESR, and ferritin. S100A12 levels were positively correlated with HRCT scores in patients with stable DM-ILD and those with AE DM-ILD, while they were negatively correlated with predicted percentages of forced vital capacity and predicted percentages of carbon monoxide diffusing capacity in those patients. Conclusion: Our findings demonstrate the usefulness of serum S100A12 levels for assessing clinical severity and prognosis of DM-ILD.

Dermatomyositis and rheumatoid arthritis are inflammatory diseases that affect the skeletal muscles and joints, respectively. A common systemic complication of these diseases is interstitial lung disease (ILD), which leads to a poor prognosis and increased mortality. However, the mechanism for the initiation and development of ILD in patients with dermatomyositis is currently unknown. In the present study, we used 16S rRNA high-throughput sequencing to profile the bacterial community composition of bronchoalveolar lavage fluid of patients with dermatomyositis associated with ILD (DM-ILD; shortened to DM below), rheumatoid arthritis associated with ILD (RA-ILD; shortened to RA below) and healthy controls (N) aiming to understand the differences in their lung microbiota and to predict gene function. We found that there were more operational taxonomic units (OTUs) in the lung microbiota of both RA and DM compared to N, although there was no significant difference in the number of OTUs between RA and DM. Similarly, the diversity in alphaproteobacteria differed between RA and DM compared to N, but not between RA and DM. The lung microbiota of RA, DM and N was mainly comprised of five phyla: Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria and Fusobacteria, with 10 dominant genera. Despite the similarity in microbiota composition, we also identified 41 OTUs of lung microbiota that differed among RA, DM and N. Additionally, linear discriminant analysis effect size and linear discriminant analysis genus scores confirmed that 31 microbial biomarkers were clearly distinguished among RA, DM and N. The functional and metabolic alterations of the lung microbiota among RA, DM and N were predicted using PICRUST, and differentially abundant KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways were identified. Research on the lung microbiota of patients with DM and RA may open new opportunities for developing biomarkers to identify high-risk patients.