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

Rev Neurosci. 2017 May 24;28(4):375-380. doi: 10.1515/revneuro-2016-0066.

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.

Keywords: biomarker; diagnosis; glioma; long non-coding RNA; molecular classification; prognosis.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Biomarkers, Tumor / genetics*
  • Biomarkers, Tumor / metabolism
  • Brain Neoplasms / diagnosis*
  • Brain Neoplasms / genetics
  • Brain Neoplasms / metabolism
  • Glioma / diagnosis*
  • Glioma / genetics
  • Glioma / metabolism
  • Humans
  • RNA, Long Noncoding / genetics*
  • RNA, Long Noncoding / metabolism

Substances

  • Biomarkers, Tumor
  • RNA, Long Noncoding