Research ArticleIdentification of Differentially Expressed miRNAs and mRNAsin Vestibular Schwannoma by Integrated Analysis

Yanhua Lei, Ping Guo , Xiuguo Li, Yuanyuan Zhang, and Ting Du

Department of Otolaryngology, Jining No. 1 People’s Hospital, China

Correspondence should be addressed to Ping Guo; guoping doctor@163.com

Received 26 March 2019; Accepted 22 May 2019; Published 11 June 2019

Academic Editor: Alfredo Conti

Copyright © 2019 Yanhua Lei et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background.Vestibular schwannoma (VS) is benign, slow-growing brain tumor that negatively impacts patient quality of life, whichmay cause even death. This study aimed to explore key genes and microRNAs (miRNAs) associated with VS.Methods.ThemRNAand miRNA expression profiles of VS downloaded from Gene Expression Omnibus (GEO) database were included in this studyto perform an integrated analysis. The differentially expressed mRNAs (DEmRNAs) and miRNAs (DEmiRNAs) were identified.Then, functional annotation and protein-protein interaction networks (PPI) of DEmRNAs were constructed. DEmiRNA-targetDEmRNAs analysis and functional annotation of DEmiRNA-target DEmRNAswere performed. Results.A total of 2627DEmRNAs(1194 upregulated and 1433 downregulated DEmRNAs) and 21 DEmiRNAs (12 upregulated and 9 downregulated DEmiRNAs) wereidentified. ISG15, TLE1, and XPC were three hub proteins of VS-specific PPI network. A total of 2970 DEmiRNAs-DEmRNAspairs were obtained. Among which, hsa-miR-181a-5p, hsa-miR-106-5p, and hsa-miR-34a-5p were the top three DEmiRNAsthat covered most DEmRNAs. The functional annotation of DEmiRNA-target DEmRNAs revealed that the DEmiRNA-targetDEmRNAs were significantly enriched in cGMP-PKG signaling pathway, adrenergic signaling in cardiomyocytes, and pathwaysin cancer. Conclusion.The results of this present study may provide a comprehensive understanding for the roles of DEmRNAs andDEmiRNAs in the pathogenesis of VS and developing potential biomarkers of VS.

1. Introduction

Vestibular schwannoma (VS), commonly termed acousticneuromas, arise from the vestibular branch of the eighthcranial nerve and is benign, slow-growing brain tumors thatnegatively impact patients’ quality of life, which may causehearing loss, tinnitus, facial palsy, and when large enough,brain stem compression, and even death [1, 2]. VSmay appearunilaterally but may also appear bilaterally when associatedwith neurofibromatosis type 2 syndrome (NF2) [2]. To date,the identification of the NF2 gene is the most importantfinding to our understanding of VS biology [3]. Current treat-ment modalities of VS are various, including observation,also known as wait-and-scan or watchful waiting, radiationtherapy (RT) and microsurgical resection (MS), based onassorted factors, such as size at diagnosis, significant tumorgrowth on serial imaging, or patient symptoms [4].

Recent efforts to define the associated genes and molec-ular pathways involved in tumorigenesis and expansion

have been met with some success. Welling et al. identifieda number of deregulated genes in tumor tissue by usingcDNAmicroarray analysis of tissue samples from 1 vestibularnerve versus 3 cystic sporadic, 3 solid sporadic, and 1 NF2-associated vestibular schwannoma [5]. Caye-Thomasen etal. examined the gene expression in tissue samples from 3human vestibular nerves versus 16 solid, sporadic vestibularschwannomas using a microarray chip and identified morethan 20,000 genes [6]. Aarhus et al. studied 25VSs and 3 tibialnerves (controls) with the ABI 1700 microarray platform andobtained 1650 differentially expressed genes [7]. However,the molecular events involved in the development of thiscondition are not well understood.There is an urgent need toinvestigate new therapeutic targets for VS and develop noveltreatment options.

MicroRNA (miRNA) is a new class of noncoding RNAmolecules, which is short (∼21-23 nucleotides long), single-stranded RNA molecules and later shown to be a keypart of posttranscriptional regulatory mechanisms of gene

HindawiBioMed Research InternationalVolume 2019, Article ID 7267816, 10 pageshttps://doi.org/10.1155/2019/7267816

2 BioMed Research International

expression in diverse organisms [8, 9]. MiRNAs broadlyparticipates in the regulation of protein translation andmRNA stability and are believed to play pivotal roles in awidearray of biological processes, including tumor development[10–12]. As alterations in miRNA expression levels have beenlinked with a variety of disease processes, focus on aberrantexpression in pathological states has increased [13].

This present study performed an integrated analysisof miRNAs and mRNAs expression profiles of VS down-loaded fromGene ExpressionOmnibus (GEO) database.Thedifferentially expressed mRNAs (DEmRNAs) and miRNAs(DEmiRNAs) were identified. In addition, protein-proteininteraction (PPI) network of DEmRNAs was conducted.DEmiRNA-target DEmRNAs analysis and functional anno-tation of DEmiRNA-target DEmRNAs were performed. Indoing so, we hope this study could represent a new avenuefor understanding the pathogenesis and developing potentialbiomarkers of VS.

2. Materials and Methods

2.1. Microarray Expression Profiling in GEO. The mRNAand miRNA expression profiles of patients with VS weredownloaded from GEO database (http://www.ncbi.nlm.nih.gov/geo). The search strategy in the GEO datasets wasas follows: (1) selected datasets should be mRNA/miRNAtranscriptome data of the whole genome; (2) these datawere derived from tumor tissues and adjacent nontumortissues of patients with VS; (3) datasets were standardized orraw datasets. Three datasets of mRNA expression profiles,including GSE108524, GSE56597, and GSE39645, and twodatasets of miRNA expression profiles, including GSE43571and GSE24390, were included in this study (Tables 1 and 2).

2.2. Identification of DEmRNAs and DEmiRNAs in Patientswith VS Compared with Normal Controls. MetaMA, an Rpackage, is used to combine data from multiple microar-ray datasets, and we obtained the individual P-values. TheBenjamini & Hochberg method was used to obtain multiplecomparison correction false discovery rate (FDR). DEmR-NAs and DEmiRNAs in VS compared to normal controlswere obtained with FDR < 0.05 and FDR < 0.01, respectively.Hierarchical clustering analysis of DEmRNAs was conductedby using R package “pheatmap”.

2.3. Functional Annotation of DEmRNAs between Patientswith VS and Normal Controls. Functional annotation,including Gene Ontology (GO) function and KyotoEncyclopedia of Genes and Genomes (KEGG) pathwayenrichment analyses of the DEmRNAs between patientswith VS and normal controls, were performed by CPDB(http://cpdb.molgen.mpg.de/CPDB). FDR < 0.01 was set asthe cut-off for significance.

2.4. PPI Network Construction. Top 50 up- and down-regulated DEmRNAs were scanned with the BiologicalGeneral Repository for Interaction Datasets (BioGrid,http://www.uniprot.org/database/DB-0184). In order tofurther explore the biological functions of the DEmRNAs,

PPI network was then constructed by using Cytoscapesoftware (version 3.6.1, http://www.cytoscape.org).

2.5. DEmiRNA-Target DEmRNAs Analysis. As miRNAs tendto decrease the expression of their target mRNAs, tar-get genes from DEmRNAs that expressed inversely withthat of miRNA were selected to subject to further inves-tigation [14]. Firstly, the putative targeted DEmRNAs ofDEmiRNAs were predicted by six bioinformatic algo-rithms (RNA22, miRanda, miRDB, miRWalk, PICTAR2,and Targetscan). Then, the confirmed targeted DEmRNAsof DEmiRNAs were obtained from miRWalk. Thirdly, theconfirmed DEmiRNA-DEmRNA pairs were derived frommiRWalk and the DEmiRNA-DEmRNA pairs recorded by ≥4 algorithms. Based on the obtained DEmiRNA-DEmRNApairs, DEmiRNA-DEmRNA interaction networks betweenVS and normal controls were constructed by using Cytoscapesoftware (http://www.cytoscape.org/).

2.6. Functional Annotation of DEmiRNA Targets. To furtherresearch the biological function of the target DEmRNAsof DEmiRNAs, GO and KEGG pathway analysis were per-formed by using CPDB (http://cpdb.molgen.mpg.de/CPDB).FDR < 0.01 was set as the cut-off for significance.

3. Results

3.1. DEmRNAs and DEmiRNAs between Patients with VSand Normal Controls. Compared to normal controls, a totalof 2627 DEmRNAs (1194 upregulated and 1433 downregu-lated DEmRNAs) and 21 DEmiRNAs (12 upregulated and 9downregulated DEmiRNAs) were identified. The top 10 up-and downregulated DEmRNAs and all DEmiRNAs betweenpatientswithVS andnormal controlswere displayed inTables3 and 4, respectively. Hierarchical clustering analysis of top100 up- and downregulated DEmRNAs and DEmiRNAs wasdisplayed in Figure 1.

3.2. Functional Annotation of DEmRNAs between Patientswith VS and Normal Controls. Anatomical structure devel-opment (FDR = 1.30E-33), multicellular organism devel-opment (FDR = 1.67E-33), intrinsic component of plasmamembrane (FDR = 8.06E-10) and RNA polymerase II tran-scription factor activity, and sequence-specific DNA binding(FDR = 3.72E-23) were significantly enriched GO terms inVS (Figures 2(a)–2(c)). Neuroactive ligand-receptor interac-tion (FDR = 1.49E-10), calcium signaling pathway (FDR =0.000137054), and cGMP-PKG signaling pathway (FDR =0.000853812) were significantly enriched KEGG pathways inVS (Figure 2(d)).

3.3. PPI Network Construction. The VS-specific PPI networkwas consisted of 308 nodes and 310 edges. ISG15 (degree =26), TLE1 (degree = 24), and XPC (degree = 16) were threehub proteins of VS-specific PPI network (Figure 3).

3.4. DEmiRNA-Target Interactions. A total of 2970 DEm-iRNAs-DEmRNAs pairs, including 2570 DEmiRNAs-DEmRNAs pairs which were predicted by ≥ 4 algorithms

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Table 1: List of mRNA study samples from GEO.

GEOaccession Author Platform Samples

(N:P) Year

GSE108524 Zhao Fu GPL17586 [HTA-2 0] Affymetrix Human TranscriptomeArray 2.0 [transcript (gene) version] 4 : 27 2018

GSE56597MiguelTorres-Martin

GPL10739 [HuGene-1 0-st] Affymetrix Human Gene 1.0ST Array [probe set (exon) version] 9 : 30 2014

GSE39645MiguelTorres-Martin

GPL6244 [HuGene-1 0-st] Affymetrix Human Gene 1.0ST Array [transcript (gene) version] 9 : 31 2013

Table 2: List of miRNA study samples from GEO.

GEOaccession Author Platform Samples (N:P) Year

GSE43571 MiguelTorres-Martin

GPL8786 [miRNA-1] Affymetrix MultispeciesmiRNA-1 Array 3 : 16 2014

GSE24390 Okay Saydam GPL7436 Wurdinger/Krichevsky miRNA array IV 4 : 20 2010

Table 3: Top 10 up- and downregulated DEmRNAs betweenpatients with VS and normal controls.

Gene symbol ID FDR RegulationLARP6 55323 0 downPRICKLE1 144165 0 downRAI2 10742 0 downG0S2 50486 0 downAQP1 358 0 downMEOX1 4222 0 downFOXP2 93986 0 downSOBP 55084 0 downSLC6A9 6536 0 downTACR1 6869 0 downBTK 695 0 upNLGN4X 57502 0 upZMAT3 64393 0 upATF7IP2 80063 0 upP2RY12 64805 0 upMR1 3140 0 upCHD7 55636 0 upCHPF 79586 0 upSLC15A3 51296 0 upSLC46A3 283537 0 upDEmRNAs, differentially expressed mRNAs; FDR, false discovery rate.

and 568 validated DEmiRNAs-DEmRNAs pairs derivedfrom the miRWalk, were obtained (Figure 4). Among which,hsa-miR-181a-5p (degree = 186), hsa-miR-106-5p (degree =175), and hsa-miR-34a-5p (degree = 161) were the top threeDEmiRNAs that covered most DEmRNAs.

3.5. Functional Annotation of DEmiRNA Targets. Based onGO enrichment analysis, anatomical structure development

Table 4: All DEmiRNAs between patients with VS and normalcontrols.

Symbol FDR Regulationhsa-mir-340 0.000965 downhsa-mir-10b 0.000965 downhsa-mir-625 0.002215 downhsa-mir-182 0.002215 downhsa-mir-412 0.004423 downhsa-mir-183 0.004423 downhsa-mir-181a 0.00834 downhsa-mir-206 0.008414 downhsa-mir-126 0.009816 downhsa-mir-34a 7.66E-09 uphsa-mir-30a 0.000965 uphsa-mir-9 0.000965 uphsa-mir-21 0.000965 uphsa-mir-601 0.002215 uphsa-mir-184 0.002215 uphsa-mir-628 0.00404 uphsa-mir-654 0.00404 uphsa-mir-30c 0.008414 uphsa-mir-106b 0.009057 uphsa-mir-377 0.009057 uphsa-mir-22 0.009412 upDEmiRNAs, differentially expressed miRNAs; FDR, false discovery rate.

(FDR = 1.09E-25), anatomical structure development (FDR= 3.24E-24), plasma membrane part (FDR = 1.78E-08), andRNA polymerase II transcription factor activity, sequence-specific DNA binding (FDR = 5.25E-17) were significantlyenriched GO terms in VS (Figures 5(a)–5(c)). Accordingto the KEGG pathway enrichment analysis, the DEmiRNA-target DEmRNAs were significantly enriched in cGMP-PKG

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G0S2AVPR1AS1PR1FOXP2PAK3TJP2ZBTB7CEFHD1SLITRK4TBX3MASP1MYOCDTNFSF15THRSPTACR1HAS2DCLK1SLC6A9APLNRDDIT4LCCL21FOXD1EBF1LARP6PRICKLE1RGS6KIAA1671SHISA3FIBINSHISA6SH3BGRL2RAI2PCOLCE2TNNT2GUCY1A2AQP1TSHZ2BDKRB2SOX9MEOX1FOXS1HOXA2SFRP2HSPB6SOBPINHBAPAWRPDE1CZMAT3FCGBPPROS1GFRA1CHPFPDGFCGPR83ZC4H2SERTAD2BEX1UHMK1SAMD9ISG15SLC15A3TUBB2BSTARD13NLGN4XSCN9ASCN7ATLE1RHOJP2RY12ATF7IP2USP32TSPYL4IFIT2MID1CHD7PPM1KANKRD22SPP1SLC2A5CXorf21GPR65MSR1SLC46A3BTKCSF1RRNASE6C3AR1MR1TLR3UNC93B1DIRAS2SHMT1XPCZNF28ZNF439

LabelDataset Dataset

GSE108524GSE56597GSE39645

Label

ControlCase

−2

0

2

4

(a)

mir−206mir−625mir−628mir−183mir−10bmir−126mir−106bmir−182mir−654mir−601mir−377mir−412mir−21mir−22mir−181amir−184mir−30cmir−9mir−340mir−30amir−34a

LabelDataset Dataset

GSE24390GSE43571

LabelControlCase

−4

−3

−2

−1

0

1

2

(b)

Figure 1: The heatmap of top 100 up- and downregulated DEmRNAs and DEmiRNAs between VS and normal controls. Row and columnrepresented DEmRNAs/DEmiRNAs and tissue samples, respectively. The color scale represented the expression levels.

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anatomical structure development

anatomical structure morphogenesis

animal organ development

animal organ morphogenesis

cell differentiation

cellular developmental process

epithelial cell differentiation

epithelium development

multicellular organism development

positive regulation of cellular process

positive regulation of metabolic process

regulation of developmental process

regulation of multicellular organismal process

system development

tissue development

0 250 500 750 1000

15202530

−log10(FDR)

(a)

cation channel complex

cell periphery

connexin complex

cornified envelope

integral component of plasma membrane

intermediate filament

intermediate filament cytoskeleton

intrinsic component of plasma membrane

nuclear transcription factor complex

plasma membrane

plasma membrane part

plasma membrane protein complex

transcription factor complex

transmembrane transporter complex

transporter complex

0 200 400 600 800

468

−log10(FDR)

(b)

cytokine activityDNA binding

DNA binding transcription factor activitydouble−stranded DNA binding

G−protein coupled peptide receptor activitypeptide receptor activity

receptor ligand activityreceptor regulator activity

regulatory region nucleic acid bindingRNA polymerase II transcription factor activity, sequence−specific DNA binding

sequence−specific DNA bindingtranscription factor activity, RNA polymerase II proximal promoter sequence−specific DNA binding

transcription regulatory region DNA bindingtranscriptional activator activity, RNA polymerase II proximal promoter sequence−specific DNA binding

transcriptional activator activity, RNA polymerase II transcription regulatory region sequence−specific DNA binding

0 100 200 300 400

101520

−log10(FDR)

(c)

Adrenergic signaling in cardiomyocytes

Calcium signaling pathway

cAMP signaling pathway

cGMP−PKG signaling pathway

Cytokine−cytokine receptor interaction

Neuroactive ligand−receptor interaction

Pathways in cancer

Renin secretion

Signaling pathways regulating pluripotency of stem cells

0 25 50 75 100

468

−log10(FDR)

(d)

Figure 2: Significantly enrichedGO terms andKEGGpathways ofDEmRNAsbetween patientwithVS andnormal controls. (a). BP, biologicalprocess; (b). CC, cellular component; (c). MF, molecular function; (d) KEGG pathways. The x-axis shows counts of DEmRNAs enriched inGO terms or KEGG pathways and the y-axis shows GO terms or KEGG pathways. The color scale represented -lg FDR.

6 BioMed Research International

KRTAP10-5RRAS2 HOXC13

CCNDBP1WDR55

TLE1TCF3

SOX9

TBX20

IL6ST

BARHL1

APH1A

HIST2H2AB

XPA

UBTD1CHD1L

LSM3

MED12

MDM2

HIST1H2BA

RPA4HIST1H2AG

TP53

PPP2R2DMAF

SMAD3

AQP1

MYOCD

KRTAP4-2

TCF4

HOXD13

ZBTB7A

NR2F1

EIF2S2

FOXA1

FOXA3

TLX2

CCL18GSTM4

MSX2

SERPINB9

TSPYL4

GNB3 PNMA1RGS6

SHISA3CCDC85B

GSK3B

FOXG1

FOXB1

ATF2PROP1

HLX

SIX6

ARL4D

SIX2

BARX1

ISCA1

ARL8BFOXS1

UQCRFS1

HOXB9

MYO6

FOXC1POU2F1

PBX2

NF2KRTAP10-7 ZNF439

KRTAP10-8

KRTAP10-1

SERPINB6

KRT18

USP32RNF144A

F2

CRK

VPS35MTNR1A

IGFBP5MARCKSHSPA12A

KRT8RIPK1 PSEN1SERPINB8

CC2D1BCMTM3NEU2HELZ HDAC3HHMPPED1

ZNF804A

COMMD1

GOT2KLHL22

SLC15A3

CALCOCO2DDIT4L

CCL21

TRIM27

PDE1C

PLAT

PDGFC

PDE1AEFHD1

MAP1A

GSPT2

RCHY1

ZDHHC21 SLC35F5SCKAP4 PSMA3

DMPK

HOXA2

SYNGR2RHOJ

CDC25C

KIF13B

CEP170STARD13

FOXD1

SIPA1L1

TIAM1

ZNF524

MAPKAP1

PTCH1

SKIL

SNRNP27

CHPF

MED4PARD6BTAC1 ZC4H2

GPR50

MFSD5

SLC2A5FOXD3

SLC7A2

RAB3BACAD9

ATP12ATACR1

ATP2B4

C3AR1

ATP2B3

TMEM126B

DCP1A

RPIA

PML

CDK8

PIN1

PLEKHF2

ITSN1

FOXP2

TBX3

PAK3

SDCBP

APLNR

TMEM164

GPRIN1PDS5A

CLEC2DLMBR1

PDGFRBDOLK

PCGF5

SASS6

KIAA1671

TLR3

IL17RA TRAF6SRPK1

CDK6

CLDN1 SRRM2

TJP2

SSTR3

CLDN2

KBTBD7

MAP1B

NKG7

RPL13

UBE2N

HSPB8

MSR1

HSPB1

WDFY1

HSPB6

C2orf50 SPP1

AMOTL2

UBE2W

MID1IP1

PPP2R1A

ZBTB42

TGFB1

LRRC4

PARK7

TMOD2

RBM18XPC

ZMAT3

CETN2

RPA1

HIST1H2BO

CETN3

ZNF428

SGTB

GNA13NUS1

JAK1RAP2A

CMTM6GEMIN4

P2RY12GNAI1

HTR1D

S1PR1

RAI2

LARP6 BTK

TNNT2APP

ATPAF2

RPS8

PSMA6

OLIG1

MID1

NES

EBF1

BRD7CHD7 TUBB3

ITGA4SOX2

QRICH1POU5F1TP53RK

TUBB2B

TMCM5

ATOH1

CSF1R

DCLK1

KIF1CPTPN14

CBL

NF1

TLR6

GFRA1SOCS3MEOX1

APOBATMCKS1B

VKORC1L1

TNPO3

BRI3BP

MASP1

MAPK8IP2

BEX1

PIK3CA

ERRFI1ERBB3

BAG4

RPS6KA6

THRSP

OMP

MASP2

UBAP2L

FAM120CPAWR

LDHA

HOMER3

FBXO45

SLC5A1

STK38

ARID5BMYH9

SPAG9

MX1

IFIT5

CHCHD1

DSTN

ERCC2

RBM15B

PPM1KMYB

VCP

WDR1

CALD1

PFN1

DDX17EIF2AK2ISG15

ANXA5

ZNF281

RPL24

EEF1GIFIT2

SNRPB2

PABPC4

YBX1

SNRPD3

RPLP1

IFIT3

TAGLN

SNRPC

Figure 3: VS-specific PPI network. The red and green ellipses represented proteins encoded by up- and downregulated DEmRNAs betweenVS and normal controls. Ellipses with black border were DEmRNAs derived from top 10 up- and downregulated DEmRNAs between VS andnormal controls.

signaling pathway (FDR = 7.54E-05), adrenergic signaling incardiomyocytes (FDR = 0.00029), and pathways in cancer(FDR = 0.000433) (Figure 5(d)).

4. Discussion

VS is a benign tumor originating from the nerve sheath ofone of the vestibular nerves. It is the most common extra-axial tumor in the posterior fossa of adults, comprising over80% of tumors in the cerebellopontine angle (CPA) [15]. Inthis study, we performed an integrated analysis based on thedatabases downloaded from GEO to obtain key mRNAs andmiRNAs associated with VS. To the best of our knowledge, itis the first time to conduct an integrated analysis on miRNAsand mRNAs expression profiles of VS.

ISG15, a small molecular weight protein, whose expres-sion is induced by interferon, was first identified as anubiquitin-like modified protein and was named ubiquitincross-reactive protein as its structure was similar to ubiquitin[16]. ISG15 has been postulated that it may directly orindirectly be involved in tumor development [17]. It was

demonstrated that ISG15 was differentially expressed in dif-ferent tumor cells and different cell lines from same histologicorigin [18]. Zhang et al. reported that the expression ofISG15 mRNA and protein was significantly higher in tumorsthan in adjacent control tissues [19]. Reportedly, ISG15 andUBE2L6 were identified as negative regulators of autophagyin esophageal cancer cells [20]. In this present study, ISG15was significantly upregulated and a hub gene in PPI networkin VS. It is surmised that ISG15 may involve in VS.

TLE familymember 1, transcriptional corepressor (TLE1),exhibits a well-characterized function in the regulation ofnervous systemdevelopment [21]. In particular, TLE1 exhibitsantineurogenic activity in mammalian forebrain develop-ment [21]. TLE1 is involved in diverse signaling pathwaysand has important roles in neurogenesis, sex determination,and segmentation during development [22]. Previous studiessuggest TLE1 could be used as a diagnostic marker and isa possible therapeutic target in various malignancies. Yaoet al. reported that TLE1 was overexpressed in human lungtumors and may play an important role in promoting lungtumorigenesis and then speculated it may be a putative lung-specific oncogene [21]. Bakrin et al. suggested that TLE1

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GPRC5AMYL6 BAMBIMTF1KCNV2 hsa-miR-106b-5p

HOXA11

SRPK1

NPTXR

SIAH2

USH1G

DCAF4L2

DERL2IQCC

NAT2

NUBP1DDIT4L

NCKAP5

FZD7

BMP2

FZD9

DNAJB8

GPR137C

PDE4CTRIM3

MYCT1

RAD51

GPR157

FOXC1

DNMT3BADRB1

ABRA

RYR3

PBX2

RTP1

ANKS4B

ATP12A

TNFSF9

AKAP5

BCAS4

CD34

FJX1

FCRL5

KCTD4

FOXE3OPRD1

WNT4

UROS

PGK2

CCDC62 SLC45A4

MYCNFNIP2

ZXDA FAM89A

HIC1ONECUT1

CCKBR

MYF6

SFTPBSHISA2

PLEKHA6

SGCDTBX3

ARXSOX7

ITPKCKLHL31

LSM3

HES2

MGST1C6orf15

GNAI1

ZFR2UBTD2

NOL4

FSHB

DCLK1DGKH

LYPD5SPON2

PLEKHG4B

TMEM158SLC31A2

VWC2L

HTR2A

MAP7 TTPAL

SLITRK3

FBXL7

UCN2

SLC6A9PLEKHA2

hsa-miR-30c-5p

hsa-miR-654-5p

BLOC1S3SHISA3 PAWR

ADRA1D

CLIC5

GNAO1

KCNA4

GREB1

LYRM2ZNF395

DGKETAL1

SYNPO2hsa-miR-184

ABCG4

IRF4SOCS3

JAK1SLC12A2

TCF4ADAMTS12

DHCR24hsa-miR-30a-5pSVOP

PPP3R2RASL10B

NMUR1

HIST1H4A

LRRFIP1ZNF460

CHST2

AQP1

SGSM1

SIAH3

KIAA1671

CCL22

FNBP1

HMGA2

HOXC6

KCNJ3ARHGAP29

MUC17

HMGA1

KCNJ11

CLDN3SLC18A3DIRAS1

TMEM151B

OMG

C21orf58

RPA1

FOXD1ADM2

CKAP4

SOBP

ELN

MKRN3

SYPL2HHIPL1

ATOX1

NKX3-2

GPIHBP1ZNF773

GUCA2B

SAMD10

PITX1

YBX1

GLI2

NHLH1

MXRA5STK38

FOXA1

FOXL2

GPRIN1

CALML3BAHCC1

WNT3AHTR1F

NRSN2 LENEP

PROX1 GRM5 GPR12TSHZ3PRPF4B

PCDH7SETBP1GPR88 hsa-miR-34a-5pEFNA1FGD6SIX4

RNF24RBL1

CALN1RHOV

INHBBhsa-miR-628-5p

SLITRK4

UNC5C

C9orf170

PBX1

hsa-miR-654-3p

PDE1A

SCN1A

IGFBP5

MYOCDRUNX1T1

MECP2 ELFN2ZFAND5FOXP2

NF2

PLCXD3 RAB3BKCNA1 S1PR1 PLXNA2

hsa-miR-377-3phsa-miR-22-3phsa-miR-21-3p

ZIC4

GALR1

SCN2B RIMBP2MAML1

RASGRF1 TP53TREML2SCML2

TAF5

KCNJ12

FOXL1SLC7A2LRP6 MARCKSL1

FLJ44635

C6orf132

RASD1

ERRFI1SIX1NEUROD1

IL23R

TSKU

MMP3

ICAM4

C9orf40SORCS2

WDR1

TUBB3

FIBIN PBOV1

ZSWIM3

HAS2 KCNA7

HOXD11

SLC39A8

FAM84B

SKILLMO3 SNAP47

OLIG1ZBTB7B

FOXQ1

TPM4

RNPS1KCNJ8

CIC

MARVELD3

LRRN4CLF2RL1

IGDCC3

HCN4

KLHL22

ZNF135AICDA

CXCL6

ZIM3

TNFAIP8L3

METTL8BEND4

EDNRACD93

STAC NXT1PFN1

SSTR5PROP1

GJD2

CDC20 HERC2

RPRML

DIO3 PPP1R11TLX2

KRTAP19-3

EREGHLX

CAV2

CREB1 XIRP1

PAMPARD6B

CLIC4PDGFRB

PARVA

ADRA2A

SOX9

TNFSF14 SNAI1RPIA

FAM43AADM

SARSSLC28A3

VDR

N4BP3

BDKRB2PRNDHK1

DKK2

NR5A2

YPEL2PDE3A

FOXG1

SIX5

hsa-miR-34a-3p

MYH9

ATF5 MMP2

OSR1

DCUN1D1

JPH2

PRRT2

CECR2IER5

ADAMTSL3

GLE1

ZCCHC13

POU5F1

IL1RL1TSHZ2

FUT5

THPO

TOR2AACTG1

HIST1H2BOSDR9C7

CHRNA4

VEZF1

CDC25C

HIST1H1APLN

TPBG

NAMPT

FAM83A

C15orf53

SH3BGRL3MPPED1

SHISA6UCK2

PLEKHF1HOXA13 GP9

IGSF3

COL9A3TNFSF15

ZNF281YDJC

PPP1R3D MYB

GPR26 SH3BGRL2EBF1FAM118A

CLDN2FGF18

COL19A1

hsa-miR-9-5p CSRNP3KLF8 ZNF704SLC5A1GABRA2

EYA4C1QTNF2ADAMTS5

ZNF648

NDST3

REPS2XKPTCH1PEX5L RASD2

ACVRL1

TCF21hsa-miR-30a-3p

GRPEL2PNMA5

C17orf102

hsa-miR-628-3p

hsa-miR-601PTGER2

PAK3

ID1

WFDC12

CCL13CPLX2

CACNA1ENUS1

TMEM164RNF144A

UBQLN2

FGF23

ADCYAP1R1

NEUROD4KCNA6

STC1

CACNG8

MYO6THBD

MUC1

POU4F1APCDD1L

hsa-miR-21-5p

SCN5A

TIAM1GPR55

TCF7L2

ARL4C

ZBED3LY6K MPP3NPY2R

TNIKPHLDA1

ENPEPADRA2C

NPTX1VPS53ESR1

AKR1B10

CXCL12KCNN3RAB27B

FGF5ST8SIA1

CACNA2D1

PDE11A

FUT2NOX4

ITGBL1WNT2PPP1R3F

FBXO40 TAGLNJAG1

P2RY2 ALX4PAPPA2

PNMA3KALRN

HIST1H3C

AIF1L

GDF11

FOXA3

EYA1

KRTAP10-11

USP10

EDN2

HOXC12

hsa-miR-22-5p

B3GNT7PRTGADORA2B

RASSF8LSAMPCXXC4

PHLDA2

NRARP

PDE10A

PDX1

COL6A6

HS6ST3

KCNJ15

XKR5BCL2L14

LCE2B

SCN3BATP2B4 LARP6

ATP2B3NRG2

ISLRFOXS1

SYNGR2FZD1

RASGRF2PLCXD1LRP11

LHX1MAGEA10 PPP1R3B

RIMS2

LTAFUS

PRPF19HOPX

TMEM186

CDSN ACAN

RPS6KA6ICAM1

METTL7BFAM155B

THRSPC2orf50

C15orf62

KSR2RNASE13

KCNG3

C16orf54MCPH1

LEFTY2

SLCO1B3

ADRB3

C9orf3DSTN

ZNF74

PPP1R3C

EFCAB2

CTXN3

CD209 S1PR4CCDC3

KRT8

C1QTNF7TRIM71

CGNL1

HEPH

ZDHHC22

SPTBN2ADRA1A

TNRC18SLC35E4 ZNF827

CELSR1 ITGA11

BCRSPRY1BARX2

C1orf61

TRIAP1

ASCL1DLX3

C9orf152

FAM43B

MN1KPRP

RCC2

PDHA2 BLK

SFRP2

HOXB8

RAB17

FGF9 hsa-miR-377-5p

IRX2

SPRY3

GLULRPL10

KRTAP1-1 GP5

SP7

GNG4

C11orf87GPRC5B

SDCBP

MC2R

XYLT1

KCNQ2RPL24 CACNG1

BASP1YY1SHANK3

ADAM12B3GALT5

FOXN3

CLDN1SYT13

hsa-miR-106b-3pZBTB7C

SCN4B

PDE2A HIST1H2BBNXPH3

CYS1

IMPDH1BAIAP3

LELP1MBLAC1

TAL2

PTK6

UBXN10MASP1

MAP3K9

LRRC38

ODF1CDKN1C

HIST3H3TJP2

OPN4

RHBGGAS1PPARG

SPATA12

HIST2H3DHIST1H4B

LPO HSPB6

SOX11ZCCHC2

PRICKLE1

SPOCK2

SOX12LRRC55

ZNF628

HIST1H2BA

KRTAP10-7

VASNSLC29A4

PHKG2 ADD2

OAZ2

KIAA0040

OPRL1

EIF2S3

PABPC5GREM2

UNC5B

C1orf115

ZBTB8B

EMILIN3TMEM30B

RAX

ZNF80

KLF2TFPI

CD2BP2PITPNC1

DUSP9

PELI2

RAB9B

CALML5RGS8

KCNJ13HOXD13

SLITRK1

HOXC13

PCDHB11HCN2

PDE6G MEOX1SOD3

ADAMTS1MAPK8IP2CYP8B1

WNT9BSMAD3

ZNF497RHOU

MAGEL2

CDCA4RHOQ

SLC39A2

FAM84A

MMP1

SST

F2

DEFB132

KCTD16 HRKRNF152

(a)

HUS1

C15orf40

IREB2

CENPBD1

ECE1

SLU7

MRPL49

FDXACB1

POFUT2NUP205

C20orf194

POP4

SKA2RSAD2

PAPOLB

NAT8L

KLHL9

ZBTB8OSGCSH

MRFAP1L1

ZFP36

CXorf56

CALU

LRPAP1R3HDM2

DMPKSYDE2

MFNG

CD59

SEZ6L2

TBC1D5ARID5B

LDHAUBR7

MR1

MERTK

SNX2

AXL

ZDHHC15

MRPS14 PRKAR1ACDS2 ABHD2

PTP4A2

DENND1B

API5

MEX3C

hsa-miR-126-5pFBXO45

LCOR

SPATA13

PPP1R9ABCL2

TAOK1

WNK3CBLCC2D1B

CRX

MARCKS

TNFRSF10B

TAP2

EIF4E

IRAK3

C10orf25SOX2

MYSM1

PGM3ZNF708

IDSZNF91

FRYL TPPP

ZNF154STX2AMOTL2TNRC6A

TBXA2R

VAMP4MTHFR

UBE2WTMEM127

BCAP29

KCTD12CLCN3

hsa-miR-183-3p

RAD18HIPK2

VCPIP1

MTUS1 ATM

ABL2SNX19

SNX8

JRKL

ANAPC1

CHML

hsa-miR-340-3p

DTX3L

LRRC58

COL4A4CCDC122ALDH1L2EVI2A CALCOCO2

SLC22A23

CDKN2B

MTM1

FBXL14

PPP1R15B

TMEM41B

SCN3A

PTPN12LIX1L

ZNF367TNFSF8

TRAF6

GLOD4

PSAT1

BTN2A1

N4BP2L1

CCR1 CUBN

MSR1

PDE12

CSGALNACT1

CDKN2AIPNL

PLEKHF2

FZD2INSC

ZNF174

XPC

ILDR2CAMK1DHEATR1ZNF518B

KIF1CCHD1L

SLITRK5

ZNF394

RPS29THUMPD1

CLPTM1

RAB35

WDR13 WDR55

EIF2AK2

SYT11

SURF6

PLA2G4F

MAK16TTC39C

DOK6

ZBTB38 SNX10 CSGALNACT2

HDAC9PROS1

TMEM140TP53BP1 TFB1M PRAF2CNTN1

EID2B

RABIF

FYTTD1

CBLN4

ATOH8FAM122A

THAP6CAPN1

BHLHE41

FAM120C

TRIM52

KIDINS220

TBXAS1

ZFP3

MAPRE2SERPINH1

TMEM50B

SAMD5

HELZFOSL2

SLC11A2

MGA

TNFSF4

ERBB3

ZNF90

METTL7A

NCOA4PPP1R1C

RANBP6LRRC4

USP24CXCL11 ZNF254

PSME4

DLAT

SRA1

IPP

TCF19

NIPSNAP3B

ZNF138ZNF516

ADAMTS2

IP6K1

SLC30A1

TTC33

IFIT5

MSH3

MTRF1L

TRIB2

OXR1

HSPA12A

SP3DCLRE1B

SLC35C1

NTNG1

IL17RA

LITAFZNF543

MAN2A2

MRFAP1

C4orf46CSNK1A1

SAMD9 DDR2

SUV39H2

LRRC66

XPO5

HIST3H2BBRPL37

AKT3

SERPINB9

hsa-miR-10b-3pSCN9A

PDE5ARDX

PAIP1

LZIC

TACC1CLN8

ZNF287

SLC24A2

hsa-miR-182-5p

CAMK2DCSRNP2P2RY12

GPR83

RTN4

LARP4

LYST

ABCA2

CLASP1DR1

WDR31

POU2F1

PHC3CASK

PCGF5 PURA

PPARA

ZNF445BRWD1

TOR1AIP2

MGAT4A

UBE2H

ZNF654

ZKSCAN3

SLC26A2FLT4

ANKRD40 ATF7IP2CACNB4ITPRIPL2

FBXO22

FAM3C

BAG1

NEDD4L

SCN7A

THSD7A

ARL13B

PMEPA1

ACTL6A

GJA1

RCHY1

VASH1

PRMT6

TRMT5

PSMD13

NAT1

CSF2RA ZNF519

LRCH2 hsa-miR-10b-5pSERPINB8

RHOJ

AAK1

ITGB8 SFMBT2

FGD4

GGCT

INTS6hsa-miR-412-3p

CTNNA3 KLF13

GJB2PSEN1

NF1

GRAMD1B

ITSN1

ATF6

GJC1

FSCB

RWDD2A

DMD

RAB20

GTPBP10SSBP2

GNA12 STX11

FAT1

AQP11

FUCA2

PDS5ASPTLC2

RPAP3STARD9

TERF1

CCDC25

ZNF345RASEF

ACSF3

ZNF22 ZNF440

CD48RC3H2PIGW SLC30A4

TRIM27DTYMK

RBM34

DOK1

TRIT1

NDRG3NARS2 SOX4ZC4H2PSPH

SNX5

ZNF619TNFRSF21

RHOG

TADA2B

CETN3

ATG2BGPRIN3

NHLRC2

BRCC3

BNIP3

IGSF9B PLATTHRAP3

TYW3

PABPC4VDAC2LPAR5

IP6K2 PLEKHG3

RAPGEF1

ABHD15NAIF1

RIF1

DCAF8L1

CCDC142

KNTC1

PPP2CB

TBPPIAS2

CCDC121

LMBR1

GYS1

DDX17

SLC46A3

LRRC28

RPP25

CXCR4

CLEC2D FBXO10

PTPRJ

ZNF770 MEF2ATMEM150A

SH3D19TIGD2

PPIE

PDP2

FBP1

TGFBR2RNF41

SCAMP5ZNF605

DIRAS2 UBE2NMARVELD1

CEP170

MYO1E ZNF514

PPARGC1B

MYO5A

ZSCAN29

SERTAD2

TOPBP1TMLHE

NPATH2AFJ

CALD1SOCS6

APOL6 ZADH2

YTHDF2CNR1BAZ2B

PRKCD CBLL1

ARL6IP6

COX11

LRRN1

SPP1

S100A10

ATRX

DCAF11

BBS9

TTC31

TLE1

ZSCAN21SPTBN1PML

PDE1C

hsa-miR-181a-5p

BCL10

YIPF6

STRBPLRP12

GGCX

LUZP1ZNF681

NHLH2GCNT1

ZNF148

TMOD2

SOX6

EXOC8

RAP1A

STARD13

ENDOD1

C8orf59

KLF3

THAP2

ZDHHC21

RAB2B

SBNO1CDK6

DCBLD2

TGFBRAP1

TMEM86A

CD4

ZNF28TUSC1

RBPJ

TUSC3ANKRD44

DPY19L4PIN1

ADAM23SHMT2 GPR153

USP51

AK2RAB18

PTPRS

TRAPPC10VCP

GSPT1

VGLL4FBXL20 ZNF501

LPIN2SNX12

UBAP2LPRR23CFAM172A

KATNAL1

PHYHZBTB39

GNASSTK3

MAP7D1

P2RY13

ZBTB7A

SAMD4BPHLDA3

P2RX4

WDR5B

MAP1A

BICD1

MYO9B

KIF2AB2M

CDADC1

ABCD4

RNASEH2C

KIF5A

GOT2

ZNF124

ZNF544

HIGD2AGTF2H5

WDYHV1

DDX27

C6orf62

TAF9BSMCR8

ZNF439

PEF1

SIPA1L1PRSS23 SLC38A1

TNFRSF11B SMARCA1

CAPRIN2SNRPD3

hsa-miR-625-3pSRGAP1CNOT6L

MTR

EPM2AIP1

DCTN5

CHD7

MAP1B

PTPN22FAM91A1

LRAT

ABCG2

OTUD1

DNAJC7 SORBS2

STS

TTC30A PCDH10C16orf72

KPNA4 MLECSEMA5A

BBS10

NET1

KLHL36

TMEM138

TRIM5

CD69

MBOAT2

DUSP6

ZBTB6

PNMA1

ARID4A

ZNF268

ISCA1

CLN5

WDFY1

BRWD3

MYBL1hsa-miR-625-5p

SECISBP2L

TMEM132B

HPSE

PAFAH1B2

ZMAT3MED12L

CRK

TP53RKIRS1

PDPK1

IRS2

KCNE3SPATA6

TMEM19C1GALT1

PTPN14

PLA2G12A

MDM2 CREB5

PEX19GSK3B

MAP3K13SESTD1

ASXL2SPAG9 BAG4

CREM

DPYSL2

SCDMEF2D

IL6STTGFBR3

NUFIP2

LARS

ZBTB44 TMED5

hsa-miR-206

PRPF40A KDSRCTTNBP2NL

CFL2

ZNF709CMTM4hsa-miR-126-3p SGTB H3F3C

SORL1ESM1

GPR173

PLAG1 PPP1R12BMKL2

YAF2

MAF

hsa-miR-340-5pZC3H12B

ACACADAP

STAG2

RBM15B

MID1UHMK1

MEX3B

ANKRD50

CCDC6TSPYL4

hsa-miR-182-3p

ATP1B2MYO9A

CYP19A1

DLC1IL15

FGF2

ATF2

hsa-miR-183-5p

GFRA1

CHD9

RAP2A

ARSI

SMUG1

UNC13AMYL12A

IER3

UNK

NLGN4X

LHFPL4

ZBTB3

ALKBH4

MAVS

(b)

Figure 4: DEmiRNAs-DEmRNAs interaction network. (a) Interaction network between upregulated DEmiRNAs and downregulatedDEmRNAs. (b) Interaction network between downregulated DEmiRNAs and upregulated DEmRNAs. The rhombic nodes and ellipticalnodes indicate DEmiRNAs and DEmRNAs, respectively. Red and green color represent upregulation and downregulation, respectively.

immunohistochemistry for synovial sarcoma can be very use-ful to distinguish synovial sarcoma from histological mimics[23]. Additionally, TLE1 deficiency resulted in enhancedtumor growth [24]. In this analysis, TLE1 was a hub gene inPPI network as well, which may imply the important role ofTLE1 in VS.

Prickle1 is important for the nervous system develop-ment, and believed to be an integral part of the planar cellpolarity (PCP) pathway [25]. Prickle1 has been shown toregulate neuron morphogenesis, including neuron migra-tion and neurite growth in the mouse [25–27]. Yang etal. suggested that in mice, Prickle1 was part of a molecu-lar mechanism that regulated facial branchiomotor neuroncaudal migration and separated the facial branchiomotorneuron and the olivocochlear efferents [25]. Prickle1 wasshowed to be highly expressed in the spiral ganglion andinvolved in regulating distal and central outgrowth of spiralganglion neuron neurites of the inner ear [28]. PRICKLE1was detected to be one of top 10 downregulated DEmRNAsin VS. In view of this, we speculated PRICKLE1 may impli-cate in the pathogenesis of VS by participating in neuronmorphogenesis.

Galanin is a multifunctional neuropeptide initially iden-tified from the porcine intestine [29]. In mammals, galaninis widely distributed in the central nervous system andperipheral tissues, where it is involved in the modulation ofhormone and neurotransmitter release, cognitive functions,

and neuronal development [30]. The diverse physiologicaleffects of galanin are mediated by at least three galaninreceptor subtypes, including GalR1, GalR2, and GalR3[30].

Misawa et al. indicated that GALR1/2 methylation sta-tus may serve as an important site-specific biomarker forprediction of clinical outcome in patients with head andneck squamous cell carcinoma [31]. In addition, accord-ing to the KEGG pathway enrichment analysis, GALR1was enriched in neuroactive ligand-receptor interaction.These findings may show that GALR1 is associated withVS.

Based on the obtained DEmiRNAs-DEmRNAs pairs,they revealed that both PRICKLE1 and GALR1 are targetsof hsa-miR-30c-5p and hsa-miR-30a-5p, which imply thekey role of hsa-miR-30 in VS. Accordingly, we proposed ahypothesis that hsa-miR-30 may involve in VS by regulatingPRICKLE1 and GALR1.

In conclusion, abundant DEmiRNAs and DEmRNAsbetween VS and normal controls were identified which maymake a contribution for developing new diagnostic andtherapeutic strategies for VS and emphasized the importanceof several mRNAs and miRNAs which may implicate in VS.These findings may provide new insight into understandingthe mechanism of VS. The exact function of these mRNAsand miRNAs in VS need to be determined with furtherresearch.

8 BioMed Research International

anatomical structure development

anatomical structure morphogenesis

cell differentiation

cellular developmental process

multicellular organism development

negative regulation of biological process

negative regulation of cellular process

positive regulation of biological process

positive regulation of developmental process

positive regulation of metabolic process

regulation of biological process

regulation of cellular metabolic process

regulation of developmental process

regulation of multicellular organismal process

system development

0 250 500 750

17.520.022.5

−log10(FDR)

(a)

cation channel complex

cell periphery

integral component of plasma membrane

intracellular

intracellular part

intrinsic component of plasma membrane

membrane−bounded organelle

nucleus

plasma membrane

plasma membrane part

plasma membrane protein complex

plasma membrane region

transmembrane transporter complex

transporter complex

voltage−gated sodium channel complex

0 250 500 750 1000

4567

−log10(FDR)

(b)

DNA bindingDNA binding transcription factor activity

double−stranded DNA bindingheterocyclic compound binding

nucleic acid bindingorganic cyclic compound binding

protein bindingregulatory region nucleic acid binding

RNA polymerase II transcription factor activity, sequence−specific DNA bindingsequence−specific DNA binding

transcription factor activity, RNA polymerase II proximal promoter sequence−specific DNA bindingtranscription regulatory region DNA binding

transcriptional activator activity, RNA polymerase II proximal promoter sequence−specific DNA bindingtranscriptional activator activity, RNA polymerase II transcription regulatory region sequence−specific DNA binding

voltage−gated ion channel activity

0 200 400 600 800

6810121416

−log10(FDR)

(c)

Adrenergic signaling in cardiomyocytes

Basal cell carcinoma

Breast cancer

Calcium signaling pathway

cAMP signaling pathway

cGMP−PKG signaling pathway

Cushing,s syndrome

Gastric cancer

Human papillomavirus infection

Insulin signaling pathway

Neuroactive ligand−receptor interaction

Pathways in cancer

Renin secretion

Signaling pathways regulating pluripotency of stem cells

Wnt signaling pathway

0 20 40 60

2.53.03.54.0

−log10(FDR)

(d)

Figure 5: Significantly enriched GO terms and KEGG pathways of DEmiRNA-target DEmRNAs. (a). BP, biological process; (b). CC, cellularcomponent; (c). MF, molecular function; (d) KEGG pathways. The x-axis shows counts of DEmRNAs enriched in GO terms or KEGGpathways and the y-axis shows GO terms or KEGG pathways. The color scale represented -lg FDR.

BioMed Research International 9

Data Availability

The data used to support the findings of this study areincluded within the article.

Conflicts of Interest

The authors declare that they have no competing interests.

References

[1] J. M. Propp, B. J. McCarthy, F. G. Davis, and S. Preston-Martin,“Descriptive epidemiology of vestibular schwannomas,”Neuro-Oncology, vol. 8, no. 1, pp. 1–11, 2006.

[2] M. Torres-Martin, L. Lassaletta, J. M. de Campos et al., “Globalprofiling in vestibular schwannomas shows critical deregulationof microRNAs and upregulation in those included in chromo-somal region 14q32,” PLoS ONE, vol. 8, no. 6, article e65868,2013.

[3] J. A. Trofatter, M. M. MacCollin, J. L. Rutter et al., “Erratum: Anovel moesin-, ezrin-, and radixin-like gene is a candidate forthe neurofibromatosis 2 tumor suppressor (Cell (1993) 72 (791-800)),” Cell, vol. 75, no. 4, article 826, 1993.

[4] G. Soulier, B.M. van Leeuwen, H. Putter et al., “Quality of life in807 patients with vestibular schwannoma: comparing treatmentmodalities,” Otolaryngology - Head and Neck Surgery (UnitedStates), vol. 157, no. 1, pp. 92–98, 2017.

[5] D. B. Welling, J. M. Lasak, E. Akhmametyeva, B. Ghaheri, andL.-S. Chang, “cDNA microarray analysis of vestibular schwan-nomas,”Otology&Neurotology, vol. 23, no. 5, pp. 736–748, 2002.

[6] T. P. Caye and R. S. Borup, “Deregulated genes in sporadicvestibular schwannomas,” Otology & Neurotology, vol. 31, no. 2,pp. 256–266, 2012.

[7] M. Aarhus, O. Bruland, H. A. Sætran et al., “Global gene expres-sion profiling and tissue microarray reveal novel candidategenes and down-regulation of the tumor suppressor gene CAV1in sporadic vestibular schwannomas,” Neurosurgery, vol. 67, no.4, pp. 998–1019, 2010.

[8] E. C. Lai, “Micro RNAs are complementary to 3’UTR sequencemotifs that mediate negative post-transcriptional regulation,”Nature Genetics, vol. 30, no. 4, pp. 363-364, 2002.

[9] P. G. Hawkins and K. V. Morris, “RNA and transcriptionalmodulation of gene expression,”Cell Cycle, vol. 7, no. 5, pp. 602–607, 2008.

[10] C. Z. Chen, “MicroRNAs as oncogenes and tumor suppressors,”The New England Journal of Medicine, vol. 353, no. 17, pp. 1768–1771, 2005.

[11] T. R. Cech and J. A. Steitz, “The noncoding RNA revolution—trashing old rules to forge new ones,” Cell, vol. 157, no. 1, pp. 77–94, 2014.

[12] Y. Huang, X. J. Shen, Q. Zou, and Q. L. Zhao, “Biological func-tions of MicroRNAs: a review,” Russian Journal of BioorganicChemistry, vol. 67, no. 1, pp. 129–139, 2011.

[13] M. Nugent, “MicroRNAs: Exploring new horizons in oste-oarthritis,” Osteoarthritis and Cartilage, vol. 24, no. 4, pp. 573–580, 2016.

[14] Y. Chen, Z. Mao, Y. Shi et al., “Comprehensive analysis ofmiRNA–mRNA–lncRNA networks in severe asthma,” Epige-nomics, vol. 11, no. 2, pp. 115–131, 2019.

[15] A. N. Hasso and D. S. Smith, “The cerebellopontine angle,”Seminars in Ultrasound, CT andMRI, vol. 10, no. 3, pp. 280–301,1989.

[16] N. Reich, B. Evans, D. Levy, D. Fahey, E. Knight, and J. E.Darnell, “Interferon-induced transcription of a gene encodinga 15-kDa protein depends on an upstream enhancer element,”Proceedings of the National Acadamy of Sciences of the UnitedStates of America, vol. 84, no. 18, pp. 6394–6398, 1987.

[17] A. Takaoka, S. Hayakawa, H. Yanai et al., “Integration ofinterferon-𝛼/𝛽 signalling to p53 responses in tumour suppres-sion and antiviral defence,” Nature, vol. 424, no. 6948, pp. 516–523, 2003.

[18] J. B. Andersen, M. Aaboe, E. C. Borden et al., “Stage-associatedoverexpression of the ubiquitin-like protein, ISG15, in bladdercancer,” British Journal of Cancer, vol. 94, no. 10, pp. 1465–1471,2006.

[19] Q. Zhang, Y. He, M. Nie, and W. Cai, “Roles of miR-138 andISG15 in oral squamous cell carcinoma,” Experimental andTherapeutic Medicine, vol. 14, no. 3, pp. 2329–2334, 2017.

[20] C. M. Falvey, T. R. O’Donovan, S. El-Mashed et al., “UBE2L6/UBCH8 and ISG15 attenuate autophagy in esophageal cancercells,” Oncotarget, vol. 8, no. 14, pp. 23479–23491, 2017.

[21] X. Yao, T. Pham, B. Temple et al., “TLE1 inhibits anoikis andpromotes tumorigenicity in human lung cancer cells throughZEB1-mediated E-cadherin repression,” Oncotarget, vol. 8, no.42, pp. 72235–72249, 2017.

[22] D. Yuan, X. Yang, Z. Yuan, Y. Zhao, and J. Guo, “TLE1 functionand therapeutic potential in cancer,”Oncotarget, vol. 8, no. 9, pp.15971–15976, 2017.

[23] I. H. Bakrin, F. A. Hussain, and S. E. Tuan Sharif, “Transducer-like enhancer of split 1 (TLE1) expression as a diagnosticimmunohistochemical marker for synovial sarcoma and itsassociation with morphological features,” Malaysian Journal ofPathology, vol. 38, no. 2, pp. 117–122, 2016.

[24] S. Ramasamy, B. Saez, S. Mukhopadhyay et al., “Tle1 tumorsuppressor negatively regulates inflammation in vivo andmodulates NF-𝜅B inflammatory pathway,” Proceedings of theNational Acadamy of Sciences of the United States of America,vol. 113, no. 7, pp. 1871–1876, 2016.

[25] T. Yang, A. G. Bassuk, S. Stricker, and B. Fritzsch, “Prickle1is necessary for the caudal migration of murine facial bran-chiomotor neurons,”Cell and Tissue Research, vol. 357, no. 3, pp.549–561, 2014.

[26] C. Liu, C. Lin, D. T. Whitaker et al., “Prickle1 is expressedin distinct cell populations of the central nervous system andcontributes to neuronal morphogenesis,” Human MolecularGenetics, vol. 22, no. 11, pp. 2234–2246, 2013.

[27] H.Okuda, S.Miyata, Y.Mori, andM. Tohyama, “Mouse Prickle1and Prickle2 are expressed in postmitotic neurons and promoteneurite outgrowth,” FEBS Letters, vol. 581, no. 24, pp. 4754–4760, 2007.

[28] T. Yang, J. Kersigo, S.Wu, B. Fritzsch, andA.G. Bassuk, “Prickle1regulates neurite outgrowth of apical spiral ganglion neuronsbut not hair cell polarity in the murine cochlea,” PLoS ONE, vol.12, no. 8, article e0183773, 2017.

[29] K. Tatemoto, A. Rokaeus, H. Jornvall, T. J. McDonald, andV. Mutt, “Galanin - a novel biologically active peptide fromporcine intestine,” FEBS Letters, vol. 164, no. 1, pp. 124–128, 1983.

10 BioMed Research International

[30] J. C. W. Ho, A. H. Y. Kwok, D. Zhao, Y. Wang, and F. C.Leung, “Characterization of the chicken galanin type I receptor(GalR1) and a novel GalR1-like receptor (GalR1-L),”General andComparative Endocrinology, vol. 170, no. 2, pp. 391–400, 2011.

[31] K. Misawa, D. Mochizuki, S. Endo et al., “Site-specific methyla-tion patterns of the GAL and GALR1/2 genes in head and neckcancer: Potential utility as biomarkers for prognosis,”MolecularCarcinogenesis, vol. 56, no. 3, pp. 1107–1116, 2017.

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