Transcriptional profiling of long non-coding RNAs and novel transcribed regions across a diverse panel of archived human cancers
1 Department of Pathology, Stanford University School of Medicine, 269 Campus Drive, Stanford, CA 94305-5324, USA
2 Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA
3 Department of Genetics, Stanford University School of Medicine, 269 Campus Drive, Stanford, CA 94305-5120, USA
4 Department of Biostatistics, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195-7232, USA
5 Program in Cancer Biology, Stanford University School of Medicine, 269 Campus Drive, Stanford, CA 94305-5456, USA
6 Howard Hughes Medical Institute and Program in Epithelial Biology, Stanford University School of Medicine, 269 Campus Drive, Stanford, CA 94305, USA
7 Department of Statistics, Stanford University, 390 Serra Mall, Stanford, CA 94305-4065, USA
8 Department of Health Research and Policy, Stanford University School of Medicine, 269 Campus Drive, Stanford, CA 94305-5405, USA
Genome Biology 2012, 13:R75 doi:10.1186/gb-2012-13-8-r75Published: 28 August 2012
Molecular characterization of tumors has been critical for identifying important genes in cancer biology and for improving tumor classification and diagnosis. Long non-coding RNAs, as a new, relatively unstudied class of transcripts, provide a rich opportunity to identify both functional drivers and cancer-type-specific biomarkers. However, despite the potential importance of long non-coding RNAs to the cancer field, no comprehensive survey of long non-coding RNA expression across various cancers has been reported.
We performed a sequencing-based transcriptional survey of both known long non-coding RNAs and novel intergenic transcripts across a panel of 64 archival tumor samples comprising 17 diagnostic subtypes of adenocarcinomas, squamous cell carcinomas and sarcomas. We identified hundreds of transcripts from among the known 1,065 long non-coding RNAs surveyed that showed variability in transcript levels between the tumor types and are therefore potential biomarker candidates. We discovered 1,071 novel intergenic transcribed regions and demonstrate that these show similar patterns of variability between tumor types. We found that many of these differentially expressed cancer transcripts are also expressed in normal tissues. One such novel transcript specifically expressed in breast tissue was further evaluated using RNA in situ hybridization on a panel of breast tumors. It was shown to correlate with low tumor grade and estrogen receptor expression, thereby representing a potentially important new breast cancer biomarker.
This study provides the first large survey of long non-coding RNA expression within a panel of solid cancers and also identifies a number of novel transcribed regions differentially expressed across distinct cancer types that represent candidate biomarkers for future research.