Long non-coding RNA ATB promotes malignancy of esophageal squamous cell carcinoma by regulating miR-200b/Kindlin-2 axis

Zhongwen Li(Zunyi Medical University), Xiaoliang Wu(Sun Yat-sen University), Ling Gu(Sun Yat-sen University), Qi Shen(Guizhou Provincial People's Hospital), Wen Luo(Guizhou Provincial People's Hospital), Chuangzhong Deng(Sun Yat-sen University), Qianghua Zhou(Sun Yat-sen University), Xinru Chen(Sun Yat-sen University), Yanjie Li(Sun Yat-sen University), Zuan-Fu Lim(West Virginia University), Xing Wang(Sun Yat-sen University), Jiahong Wang(Sun Yat-sen University), Xianzi Yang(Sun Yat-sen University)
Cell Death and Disease
June 22, 2017
Cited by 81Open Access
Full Text

Abstract

Esophageal squamous cell carcinoma (ESCC) is one of the leading causes of cancer-related death, especially in China. In addition, the prognosis of late stage patients is extremely poor. However, the biological significance of the long non-coding RNA lnc-ATB and its potential role in ESCC remain to be documented. In this study, we investigated the role of lnc-ATB and the underlying mechanism promoting its oncogenic activity in ESCC. Expression of lnc-ATB was higher in ESCC tissues and cell lines than that in normal counterparts. Upregulated lnc-ATB served as an independent prognosis predictor of ESCC patients. Moreover, loss-of-function assays in ESCC cells showed that knockdown of lnc-ATB inhibited cell proliferation and migration both in vitro and in vivo. Mechanistic investigation indicated that lnc-ATB exerted oncogenic activities via regulating Kindlin-2, as the anti-migration role of lnc-ATB silence was attenuated by ectopic expression of Kindlin-2. Further analysis showed that lnc-ATB functions as a molecular sponge for miR-200b and Kindlin-2. Dysregulated miR-200b/Kindlin-2 signaling mediated the oncogenic activity of lnc-ATB in ESCC. Our results suggest that lnc-ATB predicts poor prognosis and may serve as a potential therapeutic target for ESCC patients.


Related Papers

No related papers found

Powered by citation graph analysis