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Licensed Unlicensed Requires Authentication Published by De Gruyter January 20, 2017

Long non-coding RNAs: potential molecular biomarkers for gliomas diagnosis and prognosis

  • Lei Wang , Zhengtao Yu , Shaiqi Sun , Jun Peng , Rongjun Xiao , Shengpan Chen , Xiaokun Zuo , Quan Cheng and Ying Xia EMAIL logo

Abstract

The current grade classification system of gliomas is based on the histopathological features of these tumors and has great significance in defining groups of patients for clinical assessment. However, this classification system is also associated with a number of limitations, and as such, additional clinical assessment criteria are required. Long non-coding RNAs (lncRNAs) play a critical role in cellular functions and are currently regarded as potential biomarkers for glioma diagnosis and prognosis. Therefore, the molecular classification of glioma based on lncRNA expression may provide additional information to assist in the systematic identification of glioma. In the present paper, we review the emerging evidence indicating that specific lncRNAs may have the potential for use as key novel biomarkers and thus provide a powerful tool for the systematic diagnosis of glioma.

Award Identifier / Grant number: 81360190

Funding statement: This project was supported by grants from the National Natural Science Foundation of China (grant 81360190 to Y.X.).

Acknowledgments

This project was supported by grants from the National Natural Science Foundation of China (grant 81360190 to Y.X.).

  1. Conflict of interest statement: The authors have no conflicts of interest to disclose.

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Received: 2016-10-8
Accepted: 2016-12-1
Published Online: 2017-1-20
Published in Print: 2017-5-24

©2017 Walter de Gruyter GmbH, Berlin/Boston

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