Long non-coding RNA SOX21-AS1: A potential tumor oncogene in human cancers.

Emerging data have proposed that the aberrant level of long noncoding RNAs (lncRNA) is related to the onset and progression of cancer. Among them, lncRNA SOX21-AS1 was shown to upregulate and seem to be a novel oncogene in various cancer, including ovarian cancer, lung cancer, breast cancer, pancreatic cancer, osteosarcoma, and melanoma. Available data indicated that SRY-box transcription factor 21 antisense divergent transcript 1 (SOX21-AS1) mostly acts as a competing endogenous RNA (ceRNA) to inhibit the level of its target microRNAs (miRNAs), leading to upregulation of their targets. In addition, SOX21-AS1 is engaged in various signaling pathways like transforming growth factor-ß (TGF-ß) signaling, Wnt signaling, and phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling. Moreover, this lncRNA was revealed to be correlated with the clinicopathological features of affected patients. SOX21-AS1 was also proved to enhance the resistance of ovarian cancer cells to cisplatin chemotherapy. SOX21-AS1 is markedly associated with poor prognosis and low survival of patients, proposing that it may be a prognostic and diagnostic biomarker in cancer. Overexpression of SOX21-AS1 is related to various cancer-related pathways, like epithelial mesenchymal transition (EMT), invasion, migration, apoptosis, and cell cycle arrest. In this work, we aimed to discuss the biogenesis, function, and underlying molecular mechanism of SOX21-AS1 in cancer progression as well as its potential as a prognostic and diagnostic biomarker in human cancers.

Screening and identification of susceptibility genes for osteosarcoma based on bioinformatics analysis.

Background: Gene play an important role in malignant tumors. However, there is still insufficient research on genetic variations in osteosarcoma (OS) patients. Therefore, we aimed to analyze the gene expression profile of OS using bioinformatics and to explore the pathogenesis of OS at the molecular level. Methods: The gene chip dataset of OS samples was downloaded from the Gene Expression Omnibus (GEO) database for screening differentially expressed genes (DEGs). The R language clusterProfiler software package was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs. The central node proteins of the protein interaction network were analyzed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, Cytoscape, and its plug-ins cytoHubba and NetworkAnalyzer to find the key genes. Results: A total of 631 DEGs were obtained, including 362 upregulated genes and 269 downregulated genes. DEGs were mainly involved in the regulation of leukocyte chemotaxis and migration, vascular development, and other biological processes (BPs); mediation of receptor ligand activity, growth factor binding, growth factor activity, integrin binding, and other molecular functions (MFs); and were enriched in the extracellular matrix (ECM). Conclusions: DEGs in the ECM and growth factors play a key role in the development of OS. The leukocyte transendothelial migration pathway and the PI3K-AKT pathway are closely related to OS, and the related molecular mechanism is worthy of further study.