4.6 Article

The up-regulation of long non-coding RNA CCAT2 indicates a poor prognosis for prostate cancer and promotes metastasis by affecting epithelial-mesenchymal transition

Journal

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.bbrc.2016.08.120

Keywords

Long non-coding RNA; CCAT2; Prostate cancer; Prognosis

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Recently, long noncoding RNAs (lncRNAs) have been shown to have critical regulatory roles in human cancer biology. LncRNA CCAT2 is a novel identified lncRNA that was previously reported to be up regulated in different cancers, however, its role in prostate cancer remains unclear. The aim of this study was to investigate the expression and role of lncRNA CCAT2 in prostate cancer. The expression levels of lncRNA CCAT2 in PCa tissues and cell lines (DU145 and 22RV1) were evaluated by quantitative real-time PCR (qRT-PCR), and its association with prognosis of patients was analyzed by statistical analysis. Furthermore, the effect of CCAT2 on proliferation, migration, and invasion was studied in PCa cells. We found that the expression level of CCAT2 was higher in PCa tissues and cells compared to adjacent non-tumor tissues and normal prostate stromal immortalized cells WPMY-1. Kaplan-Meier survival analysis revealed that patients with high CCAT2 expression level had poorer overall survival and progression-free survival than those with low CCAT2 expression. Furthermore, multivariate analysis showed that the status of CCAT2 expression was an independent prognostic indicator for this disease. We also found that knockdown of CCAT2 could inhibit cell growth, migration, and invasion in vitro. In addition, knockdown of CCAT2 stimulated epithelial-mesenchymal transition (EMT) through abrogating N-cadherin, vimentin expression and intensifing the expression levels of E-cadherin. In conclusion, our data suggested that lncRNA CCAT2 was a novel molecule involved in PCa progression, which provided a potential prognostic biomarker and therapeutic target for new therapies in patients with prostate cancer. (C) 2016 Elsevier Inc. All rights reserved.

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