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Current Bioinformatics

Editor-in-Chief

ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

Research Article

Identification of Key mRNAs, miRNAs, and mRNA-miRNA Network Involved in Papillary Thyroid Carcinoma

Author(s): Wei Han*, Dongchen Lu*, Chonggao Wang, Mengdi Cui and Kai Lu

Volume 16, Issue 1, 2021

Published on: 08 June, 2020

Page: [146 - 153] Pages: 8

DOI: 10.2174/1574893615999200608125427

Price: $65

Open Access Journals Promotions 2
Abstract

Background: In the past decades, the incidence of thyroid cancer (TC) has been gradually increasing, owing to the widespread use of ultrasound scanning devices. However, the key mRNAs, miRNAs, and mRNA-miRNA network in papillary thyroid carcinoma (PTC) has not been fully understood.

Methods: In this study, multiple bioinformatics methods were employed, including differential expression analysis, gene set enrichment analysis, and miRNA-mRNA interaction network construction.

Results: Firstly, we investigated the key miRNAs that regulated significantly more differentially expressed genes based on GSEA method. Secondly, we searched for the key miRNAs based on the mRNA-miRNA interaction subnetwork involved in PTC. We identified hsa-mir-1275, hsa-mir-1291, hsa-mir-206 and hsa-mir-375 as the key miRNAs involved in PTC pathogenesis.

Conclusion: The integrated analysis of the gene and miRNA expression data not only identified key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma, but also improved our understanding of the pathogenesis of PTC.

Keywords: microRNA, papillary thyroid carcinoma, network, pathogenesis, gene, bioinformatics.

Graphical Abstract
[1]
La Vecchia C, Negri E. Thyroid cancer: The thyroid cancer epidemic - overdiagnosis or a real increase? Nat Rev Endocrinol 2017; 13(6): 318-9.
[http://dx.doi.org/10.1038/nrendo.2017.53] [PMID: 28450748]
[2]
Lim H, Devesa SS, Sosa JA, Check D, Kitahara CM. Trends in thyroid cancer incidence and mortality in the united states, 1974-2013. JAMA 2017; 317(13): 1338-48.
[http://dx.doi.org/10.1001/jama.2017.2719] [PMID: 28362912]
[3]
Sipos JA, Mazzaferri EL. Thyroid cancer epidemiology and prognostic variables. Clin Oncol (R Coll Radiol) 2010; 22(6): 395-404.
[http://dx.doi.org/10.1016/j.clon.2010.05.004] [PMID: 20627675]
[4]
Mohamad Yusof A, Jamal R, Muhammad R, et al. Integrated characterization of microrna and mrna transcriptome in papillary thyroid carcinoma. Front Endocrinol 2018; 9: 158.
[http://dx.doi.org/10.3389/fendo.2018.00158] [PMID: 29713312]
[5]
Bartel DP. Metazoan microRNAs. Cell 2018; 173(1): 20-51.
[http://dx.doi.org/10.1016/j.cell.2018.03.006] [PMID: 29570994]
[6]
Saiselet M, Gacquer D, Spinette A, et al. New global analysis of the microRNA transcriptome of primary tumors and lymph node metastases of papillary thyroid cancer. BMC Genomics 2015; 16: 828.
[http://dx.doi.org/10.1186/s12864-015-2082-3] [PMID: 26487287]
[7]
Krek A, Grün D, Poy MN, et al. Combinatorial microRNA target predictions. Nat Genet 2005; 37(5): 495-500.
[http://dx.doi.org/10.1038/ng1536] [PMID: 15806104]
[8]
Goldman M, Craft B, Brooks A, Zhu J, Haussler D. The UCSC Xena Platform for cancer genomics data visualization and interpretation. bioRxiv 2018.326470 2018.
[9]
Noble WS. How does multiple testing correction work? Nat Biotechnol 2009; 27(12): 1135-7.
[http://dx.doi.org/10.1038/nbt1209-1135] [PMID: 20010596]
[10]
Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000; 28(1): 27-30.
[http://dx.doi.org/10.1093/nar/28.1.27] [PMID: 10592173]
[11]
Liao Y, Wang J, Jaehnig EJ, Shi Z, Zhang B. WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs. Nucleic Acids Res 2019; 47(W1): W199-205.
[http://dx.doi.org/10.1093/nar/gkz401] [PMID: 31114916]
[12]
Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 2012; 16(5): 284-7.
[http://dx.doi.org/10.1089/omi.2011.0118] [PMID: 22455463]
[13]
Sergushichev AA. An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation. bioRxiv2016060012 2016.
[14]
Chou CH, Shrestha S, Yang CD, et al. miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res 2018; 46(D1): D296-302.
[http://dx.doi.org/10.1093/nar/gkx1067] [PMID: 29126174]
[15]
Cancer Genome Atlas Research Network. Integrated genomic characterization of papillary thyroid carcinoma. Cell 2014; 159(3): 676-90.
[http://dx.doi.org/10.1016/j.cell.2014.09.050] [PMID: 25417114]
[16]
Calì G, Gentile F, Mogavero S, et al. CDH16/Ksp-cadherin is expressed in the developing thyroid gland and is strongly down-regulated in thyroid carcinomas. Endocrinology 2012; 153(1): 522-34.
[http://dx.doi.org/10.1210/en.2011-1572] [PMID: 22028439]
[17]
Chu CM, Yao CT, Chang YT, et al. Gene expression profiling of colorectal tumors and normal mucosa by microarrays meta-analysis using prediction analysis of microarray, artificial neural network, classification, and regression trees. Dis Markers 2014; 2014: 634123.
[http://dx.doi.org/10.1155/2014/634123] [PMID: 24959000]
[18]
Griffith OL, Melck A, Jones SJ, Wiseman SM. Meta-analysis and meta-review of thyroid cancer gene expression profiling studies identifies important diagnostic biomarkers. J Clin Oncol 2006; 24(31): 5043-51.
[http://dx.doi.org/10.1200/JCO.2006.06.7330] [PMID: 17075124]
[19]
Yanaihara N, Kohno T, Takakura S, et al. Physical and transcriptional map of a 311-kb segment of chromosome 18q21, a candidate lung tumor suppressor locus. Genomics 2001; 72(2): 169-79.
[http://dx.doi.org/10.1006/geno.2000.6454] [PMID: 11401430]
[20]
Kestler DP, Foster JS, Bruker CT, et al. ODAM expression inhibits human breast cancer tumorigenesis. Breast Cancer 2011; 5: 73-85.
[http://dx.doi.org/10.4137/BCBCR.S6859] [PMID: 21603257]
[21]
Degl’Innocenti D, Alberti C, Castellano G, et al. Integrated ligand-receptor bioinformatic and in vitro functional analysis identifies active TGFA/EGFR signaling loop in papillary thyroid carcinomas. PLoS One 2010; 5(9): e12701.
[http://dx.doi.org/10.1371/journal.pone.0012701] [PMID: 20877637]
[22]
Zhou Q, Han LR, Zhou YX, Li Y. MiR-195 Suppresses cervical cancer migration and invasion through targeting smad3. Int J Gynecol Cancer 2016; 26(5): 817-24.
[http://dx.doi.org/10.1097/IGC.0000000000000686] [PMID: 27206216]
[23]
Yang R, Xing L, Zheng X, Sun Y, Wang X, Chen J. The circRNA circAGFG1 acts as a sponge of miR-195-5p to promote triple-negative breast cancer progression through regulating CCNE1 expression. Mol Cancer 2019; 18(1): 4.
[http://dx.doi.org/10.1186/s12943-018-0933-7] [PMID: 30621700]
[24]
Li B, Wang S, Wang S. MiR-195 suppresses colon cancer proliferation and metastasis by targeting WNT3A. Mol Genet Genomics 2018; 293(5): 1245-53.
[http://dx.doi.org/10.1007/s00438-018-1457-y] [PMID: 29948330]
[25]
Tu MJ, Pan YZ, Qiu JX, Kim EJ, Yu AM. MicroRNA-1291 targets the FOXA2-AGR2 pathway to suppress pancreatic cancer cell proliferation and tumorigenesis. Oncotarget 2016; 7(29): 45547-61.
[http://dx.doi.org/10.18632/oncotarget.9999] [PMID: 27322206]
[26]
Sun KY, Peng T, Chen Z, Huang J, Zhou XH. MicroRNA-1275 suppresses cell growth, and retards G1/S transition in human nasopharyngeal carcinoma by down-regulation of HOXB5. J Cell Commun Signal 2016; 10(4): 305-14.
[http://dx.doi.org/10.1007/s12079-016-0351-9] [PMID: 27644407]
[27]
Radzikinas K, Aven L, Jiang Z, et al. A Shh/miR-206/BDNF cascade coordinates innervation and formation of airway smooth muscle. J Neurosci 2011; 31(43): 15407-15.
[http://dx.doi.org/10.1523/JNEUROSCI.2745-11.2011] [PMID: 22031887]
[28]
Novák J, Kružliak P, Bienertová-Vašků J, Slabý O, Novák M. MicroRNA-206: a promising theranostic marker. Theranostics 2014; 4(2): 119-33.
[http://dx.doi.org/10.7150/thno.7552] [PMID: 24465270]

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