Exploring the immune characteristions of CRKP pneumonia at single-cell level.

The immune dysregulation associated with carbapenem-resistant Klebsiella pneumoniae (CRKP) severity was investigated through single-cell RNA sequencing (scRNA-seq) of 5 peripheral blood samples from 3 patients with moderate and severe CRKP pneumonia. Additionally, scRNA-seq datasets from two individuals with COVID-19 were included for comparative analysis. The dynamic characterization and functional properties of each immune cell type were examined by delineating the transcriptional profiles of immune cells throughout the transition from moderate to severe conditions. Overall, most immune cells in CRKP patients exhibited a robust interferon-α response and inflammatory reaction compared to healthy controls, mirroring observations in COVID-19 patients. Furthermore, cell signatures associated with NK cells, macrophages, and monocytes were identified in CRKP progression including PTPRCAP for NK cells, C1QB for macrophages, and S100A12 for both macrophages and monocytes. In summary, this study offers a comprehensive scRNA-seq resource for illustrating the dynamic immune response patterns during CRKP progression, thereby shedding light on the associations between CRKP and COVID-19.

Machine-Learning Algorithm-Based Prediction of Diagnostic Gene Biomarkers Related to Immune Infiltration in Patients With Chronic Obstructive Pulmonary Disease.

Objective: This study aims to identify clinically relevant diagnostic biomarkers in chronic obstructive pulmonary disease (COPD) while exploring how immune cell infiltration contributes towards COPD pathogenesis. Methods: The GEO database provided two human COPD gene expression datasets (GSE38974 and GSE76925; n=134) along with the relevant controls (n=49) for differentially expressed gene (DEG) analyses. Candidate biomarkers were identified using the support vector machine recursive feature elimination (SVM-RFE) analysis and the LASSO regression model. The discriminatory ability was determined using the area under the receiver operating characteristic curve (AUC) values. These candidate biomarkers were characterized in the GSE106986 dataset (14 COPD patients and 5 controls) in terms of their respective diagnostic values and expression levels. The CIBERSORT program was used to estimate patterns of tissue infiltration of 22 types of immune cells. Furthermore, the in vivo and in vitro model of COPD was established using cigarette smoke extract (CSE) to validated the bioinformatics results. Results: 80 genes were identified via DEG analysis that were primarily involved in cellular amino acid and metabolic processes, regulation of telomerase activity and phagocytosis, antigen processing and MHC class I-mediated peptide antigen presentation, and other biological processes. LASSO and SVM-RFE were used to further characterize the candidate diagnostic markers for COPD, SLC27A3, and STAU1. SLC27A3 and STAU1 were found to be diagnostic markers of COPD in the metadata cohort (AUC=0.734, AUC=0.745). Their relevance in COPD were validated in the GSE106986 dataset (AUC=0.900 AUC=0.971). Subsequent analysis of immune cell infiltration discovered an association between SLC27A3 and STAU1 with resting NK cells, plasma cells, eosinophils, activated mast cells, memory B cells, CD8+, CD4+, and helper follicular T-cells. The expressions of SLC27A3 and STAU1 were upregulated in COPD models both in vivo and in vitro. Immune infiltration activation was observed in COPD models, accompanied by the enhanced expression of SLC27A3 and STAU1. Whereas, the knockdown of SLC27A3 or STAU1 attenuated the effect of CSE on BEAS-2B cells. Conclusion: STUA1 and SLC27A3 are valuable diagnostic biomarkers of COPD. COPD pathogenesis is heavily influenced by patterns of immune cell infiltration. This study provides a molecular biology insight into COPD occurrence and in exploring new therapeutic means useful in COPD.

K9(C4H4FN2O2)2Nd(PW11O39)2·25H2O induces apoptosis in human lung cancer A549 cells.

Lung cancer is the leading cause of cancer-associated mortality worldwide. The present study investigated the effects of K9(C4H4FN2O2)2Nd(PW11O39)2·25H2O (FNdPW), a chemically synthesized polyoxometalate that contains rare earth elements, on lung cancer growth, and explored the mechanism underlying its actions. The effects of FNdPW on the cell viability and apoptosis of human lung cancer A549 cells were measured using MTT assay, acridine orange/ethidium bromide staining and electron microscopy. The expression of apoptosis-related proteins, including B-cell lymphoma (Bcl)-2-associated death promoter (Bad), phosphorylated (p)-Bad, X-linked inhibitor of apoptosis (XIAP), apoptosis-inducing factor (AIF), Bcl-2-associated X protein (Bax) and Bcl-2, was determined by western blotting. Caspase-3 activity was measured using a caspase-3 activity kit. After 72 h of incubation, FNdPW reduced cell viability and induced apoptosis in A549 cells in a concentration- and time-dependent manner. FNdPW upregulated the pro-apoptotic Bad and Bax proteins, and downregulated the anti-apoptotic p-Bad, Bcl-2 and XIAP proteins. Furthermore, FNdPW also enhanced caspase-3 activity and increased the protein level of AIF in A549 cells, which was independent of the caspase-3 pathway. These events were associated with the regulation exerted by FNdPW on multiple targets involved in A549 cell proliferation. Therefore, FNdPW may be a novel drug for the treatment of lung cancer.

Identifying candidate agents for lung adenocarcinoma by walking the human interactome.

Despite recent advances in therapeutic strategies for lung cancer, mortality is still increasing. Therefore, there is an urgent need to identify effective novel drugs. In the present study, we implement drug repositioning for lung adenocarcinoma (LUAD) by a bioinformatics method followed by experimental validation. We first identified differentially expressed genes between LUAD tissues and nontumor tissues from RNA sequencing data obtained from The Cancer Genome Atlas database. Then, candidate small molecular drugs were ranked according to the effect of their targets on differentially expressed genes of LUAD by a random walk with restart algorithm in protein-protein interaction networks. Our method identified some potentially novel agents for LUAD besides those that had been previously reported (eg, hesperidin). Finally, we experimentally verified that atracurium, one of the potential agents, could induce A549 cells death in non-small-cell lung cancer-derived A549 cells by an MTT assay, acridine orange and ethidium bromide staining, and electron microscopy. Furthermore, Western blot assays demonstrated that atracurium upregulated the proapoptotic Bad and Bax proteins, downregulated the antiapoptotic p-Bad and Bcl-2 proteins, and enhanced caspase-3 activity. It could also reduce the expression of p53 and p21Cip1/Waf1 in A549 cells. In brief, the candidate agents identified by our approach may provide greater insights into improving the therapeutic status of LUAD.