Yulangsan polysaccharide inhibits epithelial-mesenchymal transition and invasion in NSCLC by attenuating the TGF-ß1/ERK signaling pathway.

Active polysaccharides have unique advantages in inhibiting cancer cell proliferation, invasion and metastasis and inducing apoptosis. Yulangsan polysaccharide (YLSPS) is derived from the root of Millettia pulchra var. laxior (Dunn) Z. Wei. Previous studies revealed that YLSPS exhibits bioactivities such as antibacterial, antidepressive, antitumor, hepatoprotective and immunomodulating activities. However, the anticancer effects of YLSPS on lung cancer have not yet been studied, and its mechanism of action remains unclear. The present study investigated the anti-migration/invasion effects of YLSPS and possible mechanisms in lung cancer cells (A549 and Lewis) in vitro and in vivo. The data suggested that YLSPS reversed epithelial-mesenchymal transition (EMT) and inhibited the invasion and migration of lung cancer cells by inhibiting the TGF-ß1-induced ERK signaling pathway. Furthermore, YLSPS reduced the levels of proteins associated with EMT, including vimentin, but increased those of E-cadherin, as determined by Western blotting. In vivo, YLSPS significantly inhibited the growth of xenograft tumors, and decreased the levels of TGF-ß1 and protein markers associated with EMT. Importantly, YLSPS had fewer toxic side effects than cisplatin. Overall, YLSPS significantly delayed non-small cell lung cancer (NSCLC) progression by modulating EMT and TGF-ß1/ERK signaling pathway. The present findings suggest that YLSPS may be a potential adjuvant therapy and drug for improving the tumor microenvironment of lung cancer.

Identification of prognostic markers by weighted gene co-expression network analysis in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is one of the fatal tumors and is associated with a poor prognosis. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify the proportions of 22 types of immune cells. Weighted gene co-expression network analysis (WGCNA) was established from the GSE37745 data, and key modules correlating most with CD8+ T cell infiltration were determined. Genes that manifested a high module connectivity in the key module were identified as hub genes. Three bioinformatics online databases were used to evaluate hub gene expression levels in tumor and normal tissues. Finally, survival analysis was conducted for these hub genes. In this study, we chose four hub genes (AURKB, CDC20, TPX2 and KIF2C) based on the comprehensive bioinformatics analyses. All hub genes were overexpressed in tumor tissue, and high expression of AURKB, CDC20, TPX2, and KIF2C correlated with the poor prognosis of these patients. In vitro experiments confirmed that CDC20 knockdown inhibited cell proliferation and growth. The above results indicated that AURKB, CDC20, TPX2, and KIF2C are potential CD8+ T cell infiltration-related biomarkers and therapeutic targets.