Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer
1 Department of Internal Medicine, Division of Oncology, Washington University School of Medicine, St Louis 63110, MO, USA
2 The Genome Institute, Washington University School of Medicine, St Louis 63110, MO, USA
3 Alvin J Siteman Cancer Center, Washington University School of Medicine, St Louis 63110, MO, USA
4 Department of Biomedical Engineering, Washington University School of Medicine, St Louis 63110, MO, USA
Genome Biology 2014, 15:429 doi:10.1186/s13059-014-0429-8Published: 13 August 2014
Long intergenic non-coding RNAs (lncRNAs) represent an emerging and under-studied class of transcripts that play a significant role in human cancers. Due to the tissue- and cancer-specific expression patterns observed for many lncRNAs it is believed that they could serve as ideal diagnostic biomarkers. However, until each tumor type is examined more closely, many of these lncRNAs will remain elusive.
Here we characterize the lncRNA landscape in lung cancer using publicly available transcriptome sequencing data from a cohort of 567 adenocarcinoma and squamous cell carcinoma tumors. Through this compendium we identify over 3,000 unannotated intergenic transcripts representing novel lncRNAs. Through comparison of both adenocarcinoma and squamous cell carcinomas with matched controls we discover 111 differentially expressed lncRNAs, which we term lung cancer-associated lncRNAs (LCALs). A pan-cancer analysis of 324 additional tumor and adjacent normal pairs enable us to identify a subset of lncRNAs that display enriched expression specific to lung cancer as well as a subset that appear to be broadly deregulated across human cancers. Integration of exome sequencing data reveals that expression levels of many LCALs have significant associations with the mutational status of key oncogenes in lung cancer. Functional validation, using both knockdown and overexpression, shows that the most differentially expressed lncRNA, LCAL1, plays a role in cellular proliferation.
Our systematic characterization of publicly available transcriptome data provides the foundation for future efforts to understand the role of LCALs, develop novel biomarkers, and improve knowledge of lung tumor biology.