Anti-CLCA1 (C-terminal half) monoclonal antibody, clone 5E3.3

Lung cancer is one kind of the malignant tumor with high mortality. And non-small cell lung cancer is the main subtype of lung cancer. And the proteins of CLCA family (CLCA1, CLCA2 and CLCA4) played an inhibitory role in the occurrence and development of multiple types of tumors. However, the effect of CLCA4 on non-small cell lung cancer cells remains unclear. In our study, we used the lentivirus to establish the overexpressed CLCA4 A549 cells. Next, the CCK-8 and clone formation assays were performed to detect the changes of proliferation of A549 cells. The wound healing and transwell assays were performed to determine the changing of the migration and invasion of A549 cells. Then gemcitabine was used to treat these cells and the CCK-8, wound healing and transwell assays were carried out to detect the effect of the combination of gemcitabine and the overexpression of CLCA4 on the proliferation, migration and invasion of A549 cells. After the overexpression of CLCA4, the clone formation and mobility of A549 cells was enhanced. Furthermore, the overexpression of CLCA4 induced the apoptosis of A549 cells and promoted the expression of apoptosis related proteins. The combination of gemcitabine and the overexpression of CLCA4 further suppressed the proliferation, migration and invasion of A549 cells. CLCA4 inhibited the proliferation, migration and invasion of non-small cell lung cancer cells. CLCA4 also strengthened the sensitivity of non-small cell lung cancer cells for gemcitabine.

The goal of this study was to identify potential transcriptomic markers in developing asthma by an integrative analysis of multiple public microarray data sets. Using the R software and bioconductor packages, we performed a statistical analysis to identify differentially expressed (DE) genes in asthma, and further performed functional interpretation (enrichment analysis and co-expression network construction) and classification quality evaluation of the DE genes identified. 3 microarray datasets (192 cases and 91 controls in total) were collected for this analysis. 62 DE genes were identified in asthma, among which 43 genes were up-regulated and 19 genes were down-regulated. The up-regulated gene with the highest Log2 Fold Change (LFC) was CLCA1 (LFC = 2.81). The down-regulated gene with the highest absolute LFC was BPIFA1 (LFC = 1.45). Enrichment analysis revealed that those DE genes strongly associated with proteolysis, retina homeostasis, humoral immune response, and salivary secretion. A support vector machine classifier (asthma versus healthy control) was also trained based on DE genes. In conclusion, the consistently DE genes identified in this study are suggested as candidate transcriptomic markers for asthma diagnosis, and provide novel insights into the pathogenesis of asthma.