Abstract
BackgroundMolecular 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.ResultsWe 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.ConclusionsThis 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.
Highlights
Molecular characterization of tumors has been critical for identifying important genes in cancer biology and for improving tumor classification and diagnosis
Because the 3’-end sequencing for expression quantification (3SEQ) sequence reads were from RNA fragments ranging between 200 and 300 bp in length, it was not unexpected to observe a tight distribution of exonic peaks approximately 275 bp upstream of the 3’-end of known genes (Figure 1a)
Theoretically 3SEQ provides sequence reads against all polyA+ transcripts present in the samples and we observed thousands of peaks within protein-coding genes, we focused our analysis on those peaks that overlap known long non-coding RNA (lncRNA) genes or are situated in intergenic regions and may correspond to novel transcripts
Summary
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. The differentially expressed genes from hundreds of cancer profiling studies over the last several years have yielded numerous biomarkers that have improved the subtyping, classification and diagnosis of tumors for both research and the clinic [1,2,3]. Despite the thousands of human lncRNAs predicted, few lncRNAs have been well characterized to date, so little is known about the expression patterns of most lncRNAs in more than a handful of cell types
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