Expression profiling of long noncoding RNA identifies lnc-MMP3-1 as a prognostic biomarker in external auditory canal squamous cell carcinoma.

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Expression profiling of long noncoding RNA identifies lnc-MMP3-1 as a prognostic biomarker in external auditory canal squamous cell carcinoma.

Cancer Med. 2017 Nov;6(11):2541-2551

Authors: Liu H, Dai C, Wu Q, Liu H, Li F

Abstract
Our previous studies suggested external auditory canal squamous cell carcinoma (EACSCC) is a rare malignancy with heterogeneous outcomes. This study aimed to identify lncRNA profile of EACSCC and determine the clinical application. Differential expression genes (DEGs) were investigated in EACSCC by whole transcriptome lncRNA arrays (GPL23178). RT-PCR was used to quantify the microarray data. Bioinformatics analyses were performed to evaluate DEGs regulations in gene ontology and cellular pathways. Fluorescence in situ hybridization (FISH) was utilized to validate lncRNA expression. The overall survival was determined by Kaplan-Meier and log-rank analyses. Our microarrays data had been submitted to Gene Expression Omnibus (GSE98912). We identified 5621 DEGs (3185 mRNAs, 2436 lncRNAs) in EACSCC. Lnc-MMP3-1 was the top one upregulated lncRNA in EACSCC with fold change of 237.2 (P < 0.001). RT-PCR results showed similar expression levels as microarrays data. Bioinformatics analyses indicated development of EACSCC was involved in aberrant alternations of multiple biological processes and cellular pathways. FSIH assays also found lnc-MMP3-1 was significantly differentially overexpressed in EACSCC (P < 0.001). Tumor lnc-MMP3-1 levels were closely associated with differentiation degree (P = 0.016), tumor invasion (P = 0.015) and TNM stage (P = 0.015). Moreover, lnc-MMP3-1 expression was a significant prognostic factor in EACSCC (χ2  = 4.276, P = 0.039). The study is the first screening and analysis of lncRNAs profile in EACSCC and provides new insights into pathogenesis of this rare disease. Our findings offered convincing evidences that lnc-MMP3-1 is a novel survival predictor of EACSCC patients.

PMID: 28960885 [PubMed - indexed for MEDLINE]

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