Anti-SELE monoclonal antibody, clone 1.2B6 [FITC]

Background Coronavirus disease-2019 (COVID-19), a respiratory disease has been associated with ischemic complications, coagulation disorders, and an endotheliitis. Objectives To explore endothelial damage and activation-related biomarkers in COVID-19 patients with criteria of hospitalization for referral to intensive care unit (ICU) and/or respiratory worsening. Methods Analysis of endothelial and angiogenic soluble markers in plasma from patients at admission. Results Study enrolled 40 consecutive COVID-19 patients admitted to emergency department that fulfilled criteria for hospitalization. Half of them were admitted in conventional wards without any ICU transfer during hospitalization; whereas the 20 others were directly transferred to ICU. Patients transferred in ICU were more likely to have lymphopenia, decreased SpO2 and increased D-dimer, CRP and creatinine levels. In those patients, soluble E-selectin and angiopoietin-2 were significantly increased (p value at 0.009 and 0.003, respectively). Increase in SELE gene expression (gene coding for E-selectin protein) was confirmed in an independent cohort of 32 patients using a whole blood gene expression profile analysis. In plasma, we found a strong association between angiopoetin-2 and CRP, creatinine and D-dimers (with p value at 0.001, 0.001 and 0.003, respectively). ROC curve analysis identified an Angiopoietin-2 cut-off of 5000 pg/mL as the best predictor for ICU outcome (Se = 80.1%, Sp = 70%, PPV = 72.7%, NPV = 77%), further confirmed in multivariate analysis after adjustment for creatinine, CRP or D-dimers. Conclusion Angiopoietin-2 is a relevant predictive factor for ICU direct admission in COVID-19 patients. This result showing an endothelial activation reinforces the hypothesis of a COVID-19-associated microvascular dysfunction.

Smoking is considered the major risk factor for lung cancer, but only a small portion of female lung adenocarcinoma patients are associated with smoking. Thus, identifying crucial genes and pathways related to nonsmoking female lung cancer patients is of great importance. Gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. The R software packages were applied to screen the differentially expressed genes (DEGs). GO term enrichment and KEGG pathway analyses were carried out using DAVID tools. The protein-protein interaction (PPI) network was constructed by Cytoscape software. In total, 487 downregulated and 199 upregulated DEGs were identified. The down-regulated DEGs were mainly enriched for behavior and response to wounding, and the upregulated DEGs were significantly enriched for multicellular organismal metabolic process and cell division. The KEGG pathway analysis revealed that the downregulated DEGs were significantly enriched for cell adhesion molecules and neuroactive ligand-receptor interaction, while the upregulated DEGs were mainly enriched for cell cycle and the p53 signaling pathway. The top 10 hub genes and top 3 gene interaction modules were selected from the PPI network. Of the ten hub genes, a high expression of five genes was related to a poor OS in female lung cancer patients who never smoked, including IL6, CXCR2, FPR2, PPBP and HBA1. However, a low expression of GNG11, LRRK2, CDH5, CAV1 and SELE was associated with a worse OS for the female lung cancer patients who never smoked. In conclusion, our study provides novel insight for a better understanding of the pathogenesis of nonsmoking female lung cancer, and these identified DEGs may serve as biomarkers for diagnostics and treatment.