4.7 Article

Analysis of long non-coding RNA expression profiles in pancreatic ductal adenocarcinoma

Journal

SCIENTIFIC REPORTS
Volume 6, Issue -, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/srep33535

Keywords

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Funding

  1. science and technology funds of School of Medicine, Shanghai Jiao Tong University [14xJ10022]
  2. National Basic Research Program of the National Natural Science Foundation [31271366]
  3. Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning [201268]
  4. National Natural Science Foundation [81502489]
  5. National High Technology Research and Development Program of China [2014AA020609]

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Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive and lethal malignancies. Long non-coding RNAs (lncRNAs) are a novel class of non-protein-coding transcripts that have been implicated in cancer biogenesis and prognosis. By repurposing microarray probes, we herein analysed the lncRNA expression profiles in two public PDAC microarray datasets and identified 34 dysregulated lncRNAs in PDAC. In addition, the expression of 6 selected lncRNAs was confirmed in Ren Ji cohort and pancreatic cell lines, and their association with 80 PDAC patients' clinicopathological features and prognosis was investigated. Results indicated that AFAP1-AS1, UCA1 and ENSG00000218510 might be involved in PDAC progression and significantly associated with overall survival of PDAC. UCA1 and ENSG00000218510 expression status may serve as independent prognostic biomarkers for overall survival of PDAC. Gene set enrichment analysis (GSEA) analysis suggested that high AFAP1-AS1, UCA1 and low ENSG00000218510 expression were correlated with several tumorigenesis related pathways. Functional experiments demonstrated that AFAP1-AS1 and UCA1 were required for efficient invasion and/or proliferation promotion in PDAC cell lines, while ENSG00000218510 acted the opposite. Our findings provide novel information on lncRNAs expression profiles which might be beneficial to the precise diagnosis, subcategorization and ultimately, the individualized therapy of PDAC.

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