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Published on: June 7, 2016
lncRNA-mRNA Expression Patterns in Invasive Pituitary Adenomas: A Microarray Analysis
Chao Peng1, Shuaikai Wang2, Jinxiu Yu3
1Department of Neurosurgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China.
Background:
Long noncoding RNAs (lncRNAs) play important roles in the tumorigenesis and progression of various cancer types; however, their roles in the development of invasive pituitary adenomas (PAs) remain to be investigated.
Methods:
lncRNA microarray analysis was performed for three invasive and three noninvasive PAs. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed, and coexpression networks between lncRNA and mRNA were constructed. Furthermore, three differentially expressed lncRNAs were selected for validation in PA samples by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). The diagnostic values of these three lncRNAs were further evaluated by a receiver operating characteristic (ROC) curve analysis.
Results:
A total of 8872 lncRNAs were identified in invasive and paired noninvasive PAs via lncRNA microarray analysis. Among these, the differentially expressed lncRNAs included 81 that were upregulated and 165 that were downregulated. GO enrichment and KEGG pathway analysis showed that these differentially expressed lncRNAs were associated with the posttranslational modifications of proteins. Furthermore, we performed target gene prediction and coexpression analysis. The interrelationships between the significantly differentially expressed lncRNAs and mRNAs were identified. Additionally, three differentially expressed lncRNAs were selected for validation in 41 PA samples by qRT-PCR. The expression levels of FAM182B, LOC105371531, and LOC105375785 were significantly lower in the invasive PAs than in the noninvasive PAs (P < 0.05). These results were consistent with the microarray data. ROC curve analysis suggested that the expression levels of FAM182B and LOC105375785 could be used to distinguish invasive PAs from noninvasive PAs.
Conclusion:
Our findings demonstrated the expression patterns of lncRNAs in invasive PAs. FAM182B and LOC105375785 may be involved in the invasiveness of PAs and serve as new candidate biomarkers for the diagnosis of invasive PAs.
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