Abstract

Abstract Despite growing appreciation of the number and importance of long non-coding RNAs (lncRNAs) in normal physiology and diseases, the knowledge on cancer-related lncRNAs is still limited. We utilized probes from array-based expression profiles that are uniquely mapped to annotated lncRNAs to investigate the expression of 10,207 lncRNAs in about 1,300 tumor samples over four different cancer types. By integrating the expression profiles of these lncRNAs with clinical outcome and somatic copy number alterations (SCNA), we identified lncRNAs that are associated with specific cancer subtypes and clinical prognosis, and predicted those that are potential drivers of cancer progression. We further validated our computational predictions by experimentally confirming the oncogenic functions of two novel lncRNAs in prostate cancer. Our results demonstrate that public genomic data contain a wealth of information on disease-relevant non-coding RNAs, and integrating orthogonal datasets and clinical information could facilitate the discovery of clinically relevant lncRNAs and help prioritize their functional studies. Citation Format: X. Shirley Liu. An integrated approach to identify clinically relevant long non-coding RNAs (lncRNAs) in cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1822. doi:10.1158/1538-7445.AM2013-1822 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.

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