OBJECTIVE: To screen for esophageal squamous cell carcinoma (ESCC)-associated long non-coding RNAs (lncRNA) and identify oncogenic lncRNA contributing to ESCC pathogenesis. METHODS: A lncRNA array containing 7419 lncRNA was used to detect the transcriptional profiles of lncRNA of four pairs of ESCC and matched normal esophageal tissue. Bioinformatic analysis was employed to identify differentially expressed ESCC associated lncRNA (ESCCAL). Quantitative real-time PCR was used to verify selected dysregulated lncRNA on independent ESCC samples. RESULTS: Genome-wide transcriptome profiling (coding and or noncoding RNA transcripts) was able to distinguish ESCC from normal tissue. Among these, bioinformatic analysis has identified 154 differentially expressed ESCC associated lncRNA (ESCCALs), which included 111 downregulated and 43 upregulated lncRNA in ESCC relative to the normal tissue (P< 0.01). The highest upregulated lncRNA (ESCCAL_1) and known onco-lncRNA HOTAIR was further verified in 26 paired ESCC samples. ESCCAL_1 and HOTAIR were found to be highly expressed in 17 ESCC and 18 ESCC compared with normal esophageal tissues. CONCLUSION: This investigation has revealed large scale aberrant expression of lncRNA in ESCC. About 70% of novel lncRNA-ESCCAL_1, together with a known lncRNA-HOTAIR, are highly expressed in ESSC, suggesting that ESCCAL_1 and HOTAIR may participate in the pathological process of ESCC. Furthermore, lncRNA could be potential diagnostic and prognostic biomarkers for ESCC.
OBJECTIVE: To screen for esophageal squamous cell carcinoma (ESCC)-associated long non-coding RNAs (lncRNA) and identify oncogenic lncRNA contributing to ESCC pathogenesis. METHODS: A lncRNA array containing 7419 lncRNA was used to detect the transcriptional profiles of lncRNA of four pairs of ESCC and matched normal esophageal tissue. Bioinformatic analysis was employed to identify differentially expressed ESCC associated lncRNA (ESCCAL). Quantitative real-time PCR was used to verify selected dysregulated lncRNA on independent ESCC samples. RESULTS: Genome-wide transcriptome profiling (coding and or noncoding RNA transcripts) was able to distinguish ESCC from normal tissue. Among these, bioinformatic analysis has identified 154 differentially expressed ESCC associated lncRNA (ESCCALs), which included 111 downregulated and 43 upregulated lncRNA in ESCC relative to the normal tissue (P< 0.01). The highest upregulated lncRNA (ESCCAL_1) and known onco-lncRNA HOTAIR was further verified in 26 paired ESCC samples. ESCCAL_1 and HOTAIR were found to be highly expressed in 17 ESCC and 18 ESCC compared with normal esophageal tissues. CONCLUSION: This investigation has revealed large scale aberrant expression of lncRNA in ESCC. About 70% of novel lncRNA-ESCCAL_1, together with a known lncRNA-HOTAIR, are highly expressed in ESSC, suggesting that ESCCAL_1 and HOTAIR may participate in the pathological process of ESCC. Furthermore, lncRNA could be potential diagnostic and prognostic biomarkers for ESCC.