Clinical significance and prospective molecular mechanism of MALAT1 in pancreatic cancer exploration: a comprehensive study based on the GeneChip, GEO, Oncomine, and TCGA databases
Authors Xie ZC, Dang YW, Wei DM, Chen P, Tang RX, Huang Q, Liu JH, Luo DZ
Received 13 March 2017
Accepted for publication 30 May 2017
Published 10 August 2017 Volume 2017:10 Pages 3991—4005
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Colin Mak
Peer reviewer comments 4
Editor who approved publication: Dr Yao Dai
Zu-cheng Xie,1,* Yi-wu Dang,1,* Dan-ming Wei,1 Peng Chen,1 Rui-xue Tang,1 Qian Huang,1 Jiang-hua Liu,1,2,* Dian-zhong Luo1,*
1Department of Pathology, 2Department of Emergency Medicine, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China
*These authors contributed equally to this work
Purpose: Long noncoding RNAs (lncRNAs) are known to function as regulators in the development and occurrence of various tumors. MALAT1 is a highly conserved lncRNA and has vital functions in diverse tumors, including pancreatic cancer (PC). However, the underlying molecular regulatory mechanism involved in the occurrence and development of PC remains largely unknown. Thus, it is important to explore MALAT1 in PC and elucidate its function, which might offer a new perspective for clinical diagnosis and therapy.
Methods: First, we used the Gene Expression Omnibus, Oncomine, and The Cancer Genome Atlas databases to determine the clinical diagnostic and prognostic values of MALAT1. We next used our own GeneChip and The Cancer Genome Atlas database to collect the possible target genes of MALAT1 and further utilized a bioinformatics analysis to explore the underlying significant pathways that might be crucial in PC. Finally, we identified several key target genes of MALAT1 and hope to offer references for future research.
Results: We found that the expression of MALAT1 was significantly elevated in patients with PC. A receiver operating characteristics curve analysis showed a moderate diagnostic value (area under the curve =0.75, sensitivity =0.66, specificity =0.72). A total of 224 important overlapping genes were collected, and six hub genes (CCND1, MAPK8, VEGFA, FOS, CDH1, and HSP90AA1) were identified, of which CCND1, MAPK8, and VEGFA, are important genes in PC. Several pathways, including the mTOR signaling pathway, pathways in cancer, and the MAPK signaling pathway, were suggested to be the vital MALAT1 pathways in PC.
Conclusion: MALAT1 is suggested to be a promising diagnostic biomarker in PC. Six hub genes (CCND1, MAPK8, VEGFA, FOS, CDH1, and HSP90AA1), and specifically CCND1, MAPK8, and VEGFA, might be key MALAT1 target genes in PC. Due to their possible clinical significance in PC, several pathways, such as the mTOR signaling pathway, pathways in cancer, and the MAPK signaling pathway, are worthy of further study.
Keywords: MALAT1, pancreatic cancer, bioinformatics, target gene
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