Long non-coding RNA expression profiles predict clinical phenotypes in glioma

Glioma is the commonest form of primary brain tumor in adults with varying malignancy grades and histological subtypes. Long non-coding RNAs (lncRNAs) are a novel class of non-protein-coding transcripts that have been shown to play important roles in cancer development. To discover novel tumor-relat...

Full description

Bibliographic Details
Main Authors: Xiaoqin Zhang, Stella Sun, Jenny Kan Suen Pu, Anderson Chun On Tsang, Derek Lee, Venus On Ying Man, Wai Man Lui, Stanley Thian Sze Wong, Gilberto Ka Kit Leung
Format: Article
Language:English
Published: Elsevier 2012-10-01
Series:Neurobiology of Disease
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S0969996112002124
Description
Summary:Glioma is the commonest form of primary brain tumor in adults with varying malignancy grades and histological subtypes. Long non-coding RNAs (lncRNAs) are a novel class of non-protein-coding transcripts that have been shown to play important roles in cancer development. To discover novel tumor-related lncRNAs and determine their associations with glioma subtypes, we first applied a lncRNA classification pipeline to identify 1970 lncRNAs that were represented on Affymetrix HG-U133 Plus 2.0 array. We then analyzed the lncRNA expression patterns in a set of previously published glioma gene expression profiles of 268 clinical specimens, and identified sets of lncRNAs that were unique to different histological subtypes (astrocytic versus oligodendroglial tumors) and malignancy grades. These lncRNAs signatures were then subject to validation in another non-overlapping, independent data set that contained 157 glioma samples. This is the first reported study that correlates lncRNA expression profiles with malignancy grade and histological differentiation in human gliomas. Our findings indicate the potential roles of lncRNAs in the biogenesis, development and differentiation of gliomas, and provide an important platform for future studies.
ISSN:1095-953X