Integrated Analysis of lncRNAs and mRNAs Identifies a Potential Driver lncRNA FENDRR in Lung Cancer in Xuanwei, China.

This study was to screen out potential driver long non-coding RNAs (lncRNAs) in lung cancer in Xuanwei (LCXW) differently expressed mRNAs and lncRNAs were detected by gene expression microarrays in 23 paired lung adenocarcinoma and adjacent tissues. Combined bioinformatics analysis was performed to identify potential driver lncRNAs and their potential regulatory relationships. Transcriptome and clinical data in TCGA-LUAD were used as comparison and validation dataset. The comparison of LCXW and TCGA-LUAD revealed significant differences in expression of some genes, signaling pathways affected by differentially expressed genes, and the 5-year survival rate of patients. We identified 14 consistently deregulated mRNAs and 5 lncRNAs as candidate genes, which affected multiple cancer-related pathways and influenced patients' overall survival. By combined bioinformatics analysis, we further identified a potential driver lncRNA fetal-lethal non-coding developmental regulatory RNA (FENDRR) and proposed its possible regulation mechanism. The low expression of FENDRR was positively correlated with Krüppel-like factor4 (KLF4), KLF4 down-regulation may loss the activation function of cyclin-dependent kinase inhibitor 1A (CDKN1A) and cyclin-dependent kinase inhibitor 1C (CDKN1C) and the inhibition function of CyclinB1 (CCNB1), eventually cause excessive cell cycle activation and lead to lung cancer. This study revealed a potential FENDRR-KLF4-cell cycle regulation axis. These results lay an important foundation for further research on the pathogenesis of LCXW and identification of potential novel biomarkers or therapeutic targets.

Comprehensive analyses of T-UCR expression profiles and exploration of the efficacy of uc.63- and uc.280+ as biomarkers for lung cancer in Xuanwei, China.

OBJECTIVES: Lung cancer in Xuanwei (LCXW), China, is known worldwide for occurring frequently with high morbidity and mortality, which necessitates research to determine its pathogenesis. This study attempted to screen potential transcribed ultraconserved region (T-UCR) biomarkers related to LCXW. METHODS: We performed T-UCR microarrays on 26 paired lung adenocarcinoma and adjacent tissues to explore the T-UCR expression profile of LCXW. Then, bioinformatics analysis was carried out to identify potential T-UCRs, which were further validated by real-time quantitative PCR (RT-qPCR). Then, clinical relevance analysis and Kaplan-Meier tests were performed on 50 paired tissues. RESULTS: T-UCRs and RNA transcripts whose transcription units overlap UCRs (RTOUs) were significantly dysregulated in LCXW tissues compared with the corresponding noncancerous lung (NCL) tissues and presented an increasing trend from stage I to III. The expression between T-UCRs and host genes or flanking genes presented a positive or negative correlation. RT-qPCR analysis showed that uc.63- and uc.280+ were significantly up-regulated in LCXW tissues (P < 0.05). Uc.63- up-regulation was associated with tumor stage and poor prognosis of patients (P < 0.05), and uc.280+ up-regulation was associated with patient age (P < 0.05). Bioinformatics analysis of RTOUs showed that the transcripts of XPO1, uc002sbh and uc002sbg, were potentially regulated targets of uc.63-. Gene Ontology and pathway analyses showed XPO1 was involved in many important biological functions. CONCLUSION: This study depicted T-UCR and RTOU expression profiling of LCXW and revealed some potential T-UCR biomarkers that may be involved in the carcinogenesis of LCXW.