RT Journal Article
SR Electronic
T1 Comprehensive analysis of lncRNAs reveals candidate prognostic biomarkers in multiple cancer types
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 861039
DO 10.1101/861039
A1 Isaev, Keren
A1 Jiang, Lingyan
A1 Lee, Christian A.
A1 Tsai, Ricky
A1 Coutinho, Fiona
A1 Dirks, Peter B.
A1 Schramek, Daniel
A1 Reimand, Jüri
YR 2019
UL http://biorxiv.org/content/early/2019/12/02/861039.abstract
AB Long non-coding RNAs (lncRNAs) are increasingly recognized as functional units in cancer pathways and powerful molecular biomarkers, however most lncRNAs remain uncharacterized. Here we performed a systematic discovery of prognostic lncRNAs in 9,326 patient tumors of 29 types using a proportional-hazards elastic net machine-learning framework. lncRNAs showed highly tissue-specific transcript abundance patterns. We identified 179 prognostic lncRNAs whose abundance correlated with patient risk and improved the performance of common clinical variables and molecular tumor subtypes. Pathway analysis revealed a large diversity of the high-risk tumors stratified by lncRNAs and suggested their functional associations. In lower-grade gliomas, discrete activation of HOXA10-AS indicated poor patient prognosis, neurodevelopmental pathway activation and a transcriptomic similarity to glioblastomas. HOXA10-AS knockdown in patient-derived glioblastoma cells caused decreased cell proliferation and deregulation of glioma driver genes and proliferation pathways. Our study underlines the pan-cancer potential of the non-coding transcriptome for developing molecular biomarkers and innovative therapeutic strategies.