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<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">Molecular Medicine Reports</journal-id>
<journal-title-group>
<journal-title>Molecular Medicine Reports</journal-title>
</journal-title-group>
<issn pub-type="ppub">1791-2997</issn>
<issn pub-type="epub">1791-3004</issn>
<publisher>
<publisher-name>D.A. Spandidos</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3892/mmr.2019.10684</article-id>
<article-id pub-id-type="publisher-id">mmr-20-05-4013</article-id>
<article-categories>
<subj-group>
<subject>Articles</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Identification of potential core genes and miRNAs in testicular seminoma via bioinformatics analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Wang</surname><given-names>Kai</given-names></name>
<xref rid="af1-mmr-20-05-4013" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author"><name><surname>Chen</surname><given-names>Yun</given-names></name>
<xref rid="af1-mmr-20-05-4013" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author"><name><surname>Zhao</surname><given-names>Zhihong</given-names></name>
<xref rid="af1-mmr-20-05-4013" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author"><name><surname>Feng</surname><given-names>Meiying</given-names></name>
<xref rid="af1-mmr-20-05-4013" ref-type="aff">1</xref>
<xref rid="af2-mmr-20-05-4013" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author"><name><surname>Zhang</surname><given-names>Shouquan</given-names></name>
<xref rid="af1-mmr-20-05-4013" ref-type="aff">1</xref>
<xref rid="c1-mmr-20-05-4013" ref-type="corresp"/></contrib>
</contrib-group>
<aff id="af1-mmr-20-05-4013"><label>1</label>Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong 510642, P.R. China</aff>
<aff id="af2-mmr-20-05-4013"><label>2</label>College of Life Sciences, Zhaoqing University, Zhaoqing, Guangdong 526061, P.R. China</aff>
<author-notes>
<corresp id="c1-mmr-20-05-4013"><italic>Correspondence to</italic>: Professor Shouquan Zhang, Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, 483 Wushan Road, Tianhe, Guangzhou, Guangdong 510642, P.R. China, E-mail: <email>sqzhang@scau.edu.cn</email></corresp>
</author-notes>
<pub-date pub-type="ppub"><month>11</month><year>2019</year></pub-date>
<pub-date pub-type="epub"><day>16</day><month>09</month><year>2019</year></pub-date>
<volume>20</volume>
<issue>5</issue>
<fpage>4013</fpage>
<lpage>4022</lpage>
<history>
<date date-type="received"><day>14</day><month>01</month><year>2019</year></date>
<date date-type="accepted"><day>21</day><month>06</month><year>2019</year></date>
</history>
<permissions>
<copyright-statement>Copyright: &#x00A9; Wang et al.</copyright-statement>
<copyright-year>2019</copyright-year>
<license license-type="open-access">
<license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivs License</ext-link>, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.</license-p></license>
</permissions>
<abstract>
<p>Testicular seminoma is one of the most common tumours in the field of urology, and its aetiology is still unclear. The aim of the present study was to identify the factors responsible for the development of testicular cancer and to investigate whether mutations in these genes were primarily congenital or acquired. To identify the key genes and miRNAs linked to testicular seminoma, as well as their potential molecular mechanisms, the GSE15220, GSE1818 and GSE59520 microarray datasets were analysed. A total of 5,195 and 1,163 differentially expressed genes (DEGs) were identified after analysing the GSE15220 and GSE1818 datasets, respectively. Among them, 287 genes were common between the two datasets. Of these, 110 were upregulated and 177 were downregulated. Five differentially expressed microRNAs (miRs; DEMs) that were downregulated in seminoma were identified after analysing the GSE59520 dataset. Following protein-protein interaction network and Gene Ontology analysis, the five nodes with the highest degrees were screened as hub genes. Among them, the high expression of hub genes, such as protein tyrosine phosphatase receptor type C (<italic>PTPRC</italic>), was associated with worse overall survival. We also predicted the potential target genes of the DEMs. DNA topoisomerase II &#x03B1; (TOP2A), marker of proliferation Ki-67 (MKI67), PTPRC and ubiquitin conjugating enzyme E2 C were associated with the PI3K/AKT and Wnt/&#x03B2;-catenin signalling pathways. In addition, <italic>hsa-miR-650</italic> and <italic>hsa-miR-665</italic> were associated with the PI3K/AKT and Wnt/&#x03B2;-catenin signalling pathways. Additionally, TOP2A and MKI67 were strongly associated with the target genes <italic>hsa-miR-650</italic> and <italic>hsa-miR-665</italic>, respectively. We proposed that the hub genes reported in the present study may have a certain impact on cellular proliferation and migration in testicular seminoma. The roles of these hub genes in seminoma may provide novel insight to improve the diagnosis and treatment of patients with seminoma.</p>
</abstract>
<kwd-group>
<kwd>testicular seminoma</kwd>
<kwd>microarray analysis</kwd>
<kwd>hub genes</kwd>
<kwd>microRNAs</kwd>
<kwd>prognosis</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec sec-type="intro">
<title>Introduction</title>
<p>The tumour of the testis is one of the most common type of tumours in the field of urology (<xref rid="b1-mmr-20-05-4013" ref-type="bibr">1</xref>). Testicular tumours are divided into seminoma and non-seminoma types, the vast majority of which are seminoma; non-seminoma types are extremely rare. Testicular tumours are almost all malignant, with germ cell tumours accounting for 90&#x2013;95&#x0025;, and non-germ cell tumours accounting for 5&#x2013;10&#x0025; (<xref rid="b2-mmr-20-05-4013" ref-type="bibr">2</xref>). In germ cell tumours, seminoma is the most common, accounting for 40&#x0025; to 50&#x0025; of primary testicular tumours, followed by embryonic cancer (20&#x2013;30&#x0025;) and teratoma (~10&#x0025;) (<xref rid="b3-mmr-20-05-4013" ref-type="bibr">3</xref>&#x2013;<xref rid="b5-mmr-20-05-4013" ref-type="bibr">5</xref>). Left and right testicular tumours of other cell types are rare. The treatment of testicular tumours is divided into single treatment, and the comprehensive treatment of surgical treatment radiation therapy and chemotherapy (<xref rid="b6-mmr-20-05-4013" ref-type="bibr">6</xref>). Unfortunately, once a testicular tumour is identified, radical orchiectomy should be performed first, and then a further treatment plan should be implemented based on the pathological findings (<xref rid="b7-mmr-20-05-4013" ref-type="bibr">7</xref>&#x2013;<xref rid="b10-mmr-20-05-4013" ref-type="bibr">10</xref>). Hence, it is urgent and necessary to explore novel therapeutic targets for the treatment of seminoma.</p>
<p>In the present study, we selected three gene expression datasets (GSE15220, GSE1818 and GSE59520), which were downloaded from the Gene Expression Omnibus (GEO) database, to obtain differentially expressed genes (DEGs) and differentially expressed microRNAs (DEMs) between testicular seminoma tissues and normal tissue samples. Then, functional enrichment and network analyses were applied to identify the DEGs. Subsequently, we established a protein-protein interaction (PPI) network to identify hub genes related to seminoma. The expression values of these hub genes were determined using the online database UALCAN. Survival analysis of these hub genes was performed using the online database Gene Expression Profiling Interactive Analysis (GEPIA). The potential target genes of the miRNAs were predicted by miRwalk 3.0 and screened by The Cancer Genome Atlas (TCGA) dataset.</p>
</sec>
<sec sec-type="materials|methods">
<title>Materials and methods</title>
<sec>
<title/>
<sec>
<title>Identification of DEGs and DEMs</title>
<p>Three gene expression profiles, GSE15220, GSE1818 and GSE59520, were acquired from the GEO database (<uri xlink:href="https://www.ncbi.nlm.nih.gov/geo/">https://www.ncbi.nlm.nih.gov/geo/</uri>). The array data of GSE15220 comprising 6 paired seminoma tissues, and adjacent tissues were submitted by Cheung <italic>et al</italic> (<xref rid="b11-mmr-20-05-4013" ref-type="bibr">11</xref>); GSE1818 consisted of 6 paired seminoma tissues and adjacent tissues. GSE59520 consisted of 14 seminoma tissues and three normal tissues (<xref rid="b12-mmr-20-05-4013" ref-type="bibr">12</xref>). DEGs were obtained from the GEO database by GEO2R analysis (<uri xlink:href="http://www.ncbi.nlm.nih.gov/geo/geo2r/">http://www.ncbi.nlm.nih.gov/geo/geo2r/</uri>). Adjusted P&#x003C;0.05 and log fold-change (|logFC|) &#x003E;2.0 were set as the DEG cutoff criterion. Adjusted P&#x003C;0.05 and |logFC| &#x003E;1.0 were set as the DEM cutoff criterion. The common dysregulated genes between GSE1818 and GSE59520 are presented as a Venn diagram and identified using R (version 3.6.1; <uri xlink:href="https://www.r-project.org/">http://www.r-project.org/</uri>). The Search Tool for the Retrieval of Interacting Genes (STRING) database (<uri xlink:href="https://string-db.org/">https://string-db.org/</uri>) for annotation, visualization and integrated discovery was employed to facilitate the transition from data collection to biological analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Enrichr online tool (<uri xlink:href="http://amp.pharm.mssm.edu/Enrichr/">http://amp.pharm.mssm.edu/Enrichr/</uri>). P&#x003C;0.05 was set as the cut off criterion. Potential target genes of the miRNAs were predicted by miRwalk 3.0 (<uri xlink:href="http://mirwalk.umm.uni-heidelberg.de/">http://mirwalk.umm.uni-heidelberg.de/</uri>) and screened using the TCGA (<uri xlink:href="https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga">https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga</uri>) database.</p>
</sec>
<sec>
<title>GO and KEGG pathway analyses of DEGs</title>
<p>GO analysis is a commonly used method for large-scale functional enrichment research; gene functions can be classified into biological process (BP), molecular function (MF) and cellular component (CC). KEGG is a widely used database that stores data on genomes, biological pathways, diseases, chemical substances and drugs. GO annotation and KEGG pathway enrichment analyses of the DEGs identified in this study were performed using Enrichr tools. P&#x003C;0.05 was considered to indicate a statistically significant difference.</p>
</sec>
<sec>
<title>Integration of the PPI network and hub gene selection</title>
<p>The STRING database is designed to analyse PPI information. To evaluate the potential PPI relationships, the DEGs we identified were mapped to the STRING database. The PPI pairs with a combined score of 0.4 were extracted. Subsequently, the PPI network was visualized by Cytoscape software (version 3.7.1; <uri xlink:href="http://www.cytoscape.org/">www.cytoscape.org/</uri>). Nodes with a higher degree of connectivity tend to be more essential in maintaining the stability of the entire network. CytoHubba (version 0.1) (<xref rid="b13-mmr-20-05-4013" ref-type="bibr">13</xref>), a plugin in Cytoscape, was used to calculate the degree of each protein node. In our study, the top five genes were identified as hub genes. miRwalk (version 3.0; <uri xlink:href="http://mirwalk.umm.uni-heidelberg.de/">http://mirwalk.umm.uni-heidelberg.de/</uri>) was used to predict the potential target genes of the miRNAs identified.</p>
</sec>
<sec>
<title>Expression profiles of hub genes based on tumour histology and survival analysis</title>
<p>UALCAN (<uri xlink:href="http://UALCAN.path.uab.edu">http://UALCAN.path.uab.edu</uri>) is a user-friendly, interactive web resource for analysing cancer transcriptome data. According to the median expression of a particular gene, the patients with testicular germ cell tumors (TGCT) were split into high and low expression groups. The overall survival (OS) of TGCT patients was evaluated using GEPIA (<xref rid="b14-mmr-20-05-4013" ref-type="bibr">14</xref>). P&#x003C;0.05 was considered to indicate a statistically significant result.</p>
</sec>
</sec>
</sec>
<sec sec-type="results">
<title>Results</title>
<sec>
<title/>
<sec>
<title>Identification of DEGs and DEMs</title>
<p>The gene expression profiles GSE15220, GSE1818 and GSE59520 were selected in this study. Based on the criteria of P&#x003C;0.05 and |logFC|&#x003E;2.0, a total of 5,195 DEGs were identified from GSE15220, and 1,163 DEGS were identified from GSE1818. Among them, 287 genes were common to the two datasets (<xref rid="f1-mmr-20-05-4013" ref-type="fig">Fig. 1</xref>). Of these, 110 were upregulated, and 176 were downregulated (<xref rid="f2-mmr-20-05-4013" ref-type="fig">Fig. 2</xref>). A total of 8 DEMs that are downregulated in seminoma were identified from GSE59520. All DEGs and DEMs were identified by comparing seminoma samples with normal samples.</p>
</sec>
<sec>
<title>Functional and pathway enrichment analyses</title>
<p>GO function and KEGG pathway enrichment analyses for the DEGs were performed using Enrichr (<xref rid="tI-mmr-20-05-4013" ref-type="table">Table I</xref>). The enriched GO terms were divided into CC, BP, and MF ontology terms. The results of GO analysis indicated that upregulated genes were mainly enriched in BPs, including &#x2018;regulation of the cellular macromolecule biosynthetic process&#x2019;, &#x2018;B cell activation&#x2019;, &#x2018;regulation of nucleic acid-templated transcription&#x2019;, and &#x2018;regulation of gene expression&#x2019;, while the downregulated genes were mainly involved in &#x2018;calcium-dependent cell-cell adhesion via plasma membrane cell adhesion molecules (CAMs)&#x2019;, &#x2018;spermatid development&#x2019;, &#x2018;spermatogenesis&#x2019;, and &#x2018;cell-cell adhesion via plasma membrane adhesion molecules&#x2019;. MF analysis showed that the upregulated genes were significantly enriched in &#x2018;RNA binding&#x2019;, &#x2018;protein homodimerization activity&#x2019;, &#x2018;protein heterodimerization activity&#x2019;, and &#x2018;transcription regulatory region DNA binding; downregulated genes were mainly enriched in &#x2018;motor activity, microtubule motor activity&#x2019;, &#x2018;actin binding&#x2019;, and &#x2018;ATPase activity&#x2019;. For CC ontology, the upregulated genes were mainly enriched in &#x2018;focal adhesion&#x2019;, &#x2018;phagocytic vesicle membrane&#x2019;, &#x2018;integral component of the luminal side of the endoplasmic reticulum membrane&#x2019;, and &#x2018;early endosome membrane&#x2019;, and the downregulated genes were mainly enriched in &#x2018;condensed nuclear chromosome&#x2019;, &#x2018;centromeric region&#x2019;, &#x2018;cytoplasmic dynein complex&#x2019;, &#x2018;spindle midzone&#x2019;, and &#x2018;focal adhesion&#x2019;.</p>
<p>In addition, KEGG pathway analysis showed that the DEGs were mainly enriched in &#x2018;viral carcinogenesis&#x2019;, &#x2018;leukocyte transendothelial migration&#x2019; and &#x2018;CAMs&#x2019;, while the downregulated genes were mainly enriched in &#x2018;amphetamine addiction&#x2019;, &#x2018;long-term potentiation&#x2019;, and &#x2018;oocyte meiosis in diabetic complications&#x2019;.</p>
</sec>
<sec>
<title>PPI network construction and the analysis of hub genes</title>
<p>A total of 123 nodes and 269 edges were mapped in the PPI network of the identified DEGs (<xref rid="f3-mmr-20-05-4013" ref-type="fig">Fig. 3</xref>). The 5 nodes with the highest degrees, including DNA topoisomerase II &#x03B1; (<italic>TOP2A</italic>), ubiquitin conjugating enzyme E2 C (<italic>UBE2C</italic>), protein tyrosine phosphatase receptor type C (<italic>PTPRC</italic>), marker of proliferation Ki-67 (<italic>MKI67</italic>), and centromere protein A (<italic>CENPA</italic>), were screened as hub genes (<xref rid="f4-mmr-20-05-4013" ref-type="fig">Fig. 4</xref>, <xref rid="tII-mmr-20-05-4013" ref-type="table">Table II</xref>). GO term enrichment analysis showed that in BPs, the genes in this module were mainly associated with &#x2018;negative regulation of chromosome organization&#x2019;, &#x2018;regulation of metaphase/anaphase transition of cell cycle&#x2019;, &#x2018;regulation of cell cycle process&#x2019;, and &#x2018;condensed nuclear chromosome kinetochore&#x2019; (<xref rid="tIII-mmr-20-05-4013" ref-type="table">Table III</xref>). The genes were significantly enriched in the &#x2018;condensed nuclear chromosome kinetochore&#x2019;, &#x2018;nuclear ubiquitin ligase complex&#x2019; &#x2018;chromosome&#x2019;, and &#x2018;nucleolus&#x2019; (<xref rid="tIII-mmr-20-05-4013" ref-type="table">Table III</xref>). MF analysis showed that the genes were mainly enriched in &#x2018;ubiquitin-like protein conjugating enzyme activity&#x2019;, &#x2018;protein kinase binding&#x2019;, and &#x2018;ubiquitin binding&#x2019; (<xref rid="tIII-mmr-20-05-4013" ref-type="table">Table III</xref>). KEGG analysis revealed that the genes were mainly enriched in &#x2018;cell adhesion molecules&#x2019;, &#x2018;primary immunodeficiency&#x2019;, and &#x2018;Fc gamma R-mediated phagocytosis&#x2019; (<xref rid="tIII-mmr-20-05-4013" ref-type="table">Table III</xref>).</p>
</sec>
<sec>
<title>Expression profiles of the hub genes and survival analysis</title>
<p>To investigate the expression and prognostic values of the five potential hub genes, the UALCAN bioinformatics analysis platform was used. All of the hub genes were significant (<xref rid="f5-mmr-20-05-4013" ref-type="fig">Fig. 5</xref>). We found that the high expression of these hub genes was associated with an unfavourable OS of patients with testicular seminoma by GEPIA (<xref rid="f6-mmr-20-05-4013" ref-type="fig">Fig. 6</xref>). However, because of the better prognosis of testicular cancer and few mortalities, the overexpression of only <italic>PTPRC</italic> was identified as an unfavourable prognostic overall survival in patients with seminoma.</p>
</sec>
<sec>
<title>Potential target genes of the miRNAs</title>
<p>To predict the potential target genes of the miRNAs, miRwalk and Cytoscape were used. miR-661 was found to be associated with PTPRC, miR-640 and miR-665 to MKI67, miR-1204 with CENPA, miR-1203 with UBE2C, miR-650 and 934 with TOP2A, and miR-1182 with TOP2A, UBE2C and MKI67 (<xref rid="f7-mmr-20-05-4013" ref-type="fig">Fig. 7</xref>).</p>
</sec>
</sec>
</sec>
<sec sec-type="discussion">
<title>Discussion</title>
<p>Although the cure and survival rates of testicular cancer are high, the main treatment methods are chemotherapy and resection (<xref rid="b15-mmr-20-05-4013" ref-type="bibr">15</xref>), which presents a great burden on the patient quality of life. In addition, the incidence of seminoma is rising. The lifestyles of males in different regions vary, while the incidence rate also differs (<xref rid="b16-mmr-20-05-4013" ref-type="bibr">16</xref>). It is estimated that by 2030, there will be 65,827 new cases worldwide, an increase of 10,561 cases from 2012 (<xref rid="b17-mmr-20-05-4013" ref-type="bibr">17</xref>). Although multiple approaches have reduced mortality, treatment resistance, disease relapse and treatment-derived side effects in particular, are important issues at present (<xref rid="b18-mmr-20-05-4013" ref-type="bibr">18</xref>). Therefore, it is important to develop novel specific targeted therapies for the treatment of seminoma.</p>
<p>In our study, a total of 287 DEGs were screened, including 110 upregulated genes and 177 downregulated genes. The upregulated genes were enriched in &#x2018;viral carcinogenesis&#x2019;, &#x2018;leukocyte transendothelial migration&#x2019; and &#x2018;CAMs&#x2019;, while the downregulated genes were mainly enriched in &#x2018;amphetamine addiction&#x2019;, &#x2018;long-term potentiation&#x2019; and &#x2018;oocyte meiosis in diabetic complications&#x2019;. Moreover, by constructing the PPI network, we identified five high-degree hub genes, including <italic>TOP2A, UBE2C, PTPRC, MKI67</italic> and <italic>CENPA</italic>. Among them, all hub genes were upregulated in seminoma. Finally, we used UALCAN to analyse the expression of these hub genes; all the hub genes were reported to be significant. Then, we predicted the association between the expression of the hub genes and the prognosis of TGCT patients. Based on GEPIA, the overexpression of all hub genes was related to an unfavourable prognosis in patients with testicular cancer. Among them, we found that the overexpression of PTPRC was an unfavourable prognostic factor for patients with seminoma.</p>
<p>TOP2A is the molecular target of several clinically useful chemotherapeutic drugs and has been used to treat a variety of tumours, including breast cancer, prostate cancer and endometrial cancer (<xref rid="b19-mmr-20-05-4013" ref-type="bibr">19</xref>). Certain studies have suggested that the overexpression of <italic>TOP2A</italic> may be associated with the poor prognosis of these malignant diseases. For seminoma, <italic>TOP2A</italic> overexpression was associated with aggressive clinical behaviours (<xref rid="b20-mmr-20-05-4013" ref-type="bibr">20</xref>). Coleman <italic>et al</italic> (<xref rid="b21-mmr-20-05-4013" ref-type="bibr">21</xref>) and Sano and Shuhin (<xref rid="b22-mmr-20-05-4013" ref-type="bibr">22</xref>) suggested that <italic>TOP2A</italic> may be a marker of seminoma cell proliferation, and <italic>TOP2A</italic> was easily detected in seminoma. Additionally, studies have also revealed that <italic>TOP2A</italic> is related to primary tumours (<xref rid="b23-mmr-20-05-4013" ref-type="bibr">23</xref>&#x2013;<xref rid="b25-mmr-20-05-4013" ref-type="bibr">25</xref>). In prostate cancer, Labb&#x00E9; <italic>et al</italic> (<xref rid="b26-mmr-20-05-4013" ref-type="bibr">26</xref>) found that <italic>TOP2A</italic> and EZH2 mRNA and protein upregulation was linked to a subgroup of primary and metastatic patients with more aggressive disease, and exhibited a notable overlap of genes involved in mitotic regulation, these results further support the hypothesis of <italic>TOP2A</italic> as a biomarker for the early identification of patients with increased metastatic potential that may benefit from adjuvant or neoadjuvant targeted therapy approaches (<xref rid="b26-mmr-20-05-4013" ref-type="bibr">26</xref>). <italic>UBE2C</italic> serves as the key component in the ubiquitin proteasome system by partnering with the anaphase-promoting complex (APC/C). Upregulated <italic>UBE2C</italic> protein expression has been reported in various types of human tumours (<xref rid="b27-mmr-20-05-4013" ref-type="bibr">27</xref>). Mo <italic>et al</italic> (<xref rid="b28-mmr-20-05-4013" ref-type="bibr">28</xref>) conducted an immunoassay to examine 209 breast cancer (BRCA) tissue samples and 53 normal tissue samples, and found that UBE2C is highly expressed in BRCA. Furthermore, the expression of <italic>UBE2C</italic> was positively correlated with tumour size (<xref rid="b24-mmr-20-05-4013" ref-type="bibr">24</xref>). Wang <italic>et al</italic> (<xref rid="b29-mmr-20-05-4013" ref-type="bibr">29</xref>) revealed that the level of phosphorylated aurora kinase A (p-AURKA) decreased markedly via the Wnt/&#x03B2;-catenin and PI3K/AKT signalling pathways following the knockdown of <italic>UBE2C</italic> with a small interfering RNA. The signalling pathway suppressed the occurrence and development of gastric cancer, and their data suggested that the activity of AURKA may be regulated by <italic>UBE2C</italic> via modulation of the activity of APC/C (<xref rid="b29-mmr-20-05-4013" ref-type="bibr">29</xref>), <italic>UBE2C</italic> may be a novel marker in the diagnosis of gastric cancer (<xref rid="b25-mmr-20-05-4013" ref-type="bibr">25</xref>); however, little is known about <italic>UBE2C</italic> in seminoma. PTPRC is a member of the protein tyrosine phosphatase (PTP) family. PTPs are signalling molecules that regulate a variety of cellular processes, including cell growth, differentiation, mitosis, and oncogenic transformation (<xref rid="b30-mmr-20-05-4013" ref-type="bibr">30</xref>). Porcu <italic>et al</italic> (<xref rid="b31-mmr-20-05-4013" ref-type="bibr">31</xref>) demonstrated that the downregulation of <italic>CD45</italic> (encoded by <italic>PTPRC</italic>) expression sensitizes T cells to cytokine stimulation, as observed by increased JAK/STAT signalling, whereas the overexpression of CD45 decreases cytokine-induced signalling. In our study, <italic>PTPRC</italic>, which may serve an important role in cytokine induction, was upregulated in seminoma. The expression of <italic>MKI67</italic> is strongly associated with tumour cell proliferation and growth, and is widely employed in routine pathological investigations as a proliferation marker (<xref rid="b32-mmr-20-05-4013" ref-type="bibr">32</xref>). It was revealed that the expression of P53 and Wnt signalling correlated with that the expression of <italic>MKI-67</italic> in several types of cancer (<xref rid="b33-mmr-20-05-4013" ref-type="bibr">33</xref>&#x2013;<xref rid="b36-mmr-20-05-4013" ref-type="bibr">36</xref>). Downregulated <italic>MKI67</italic> may be involved in cancer; in our study, it was downregulated in seminoma. Five pivotal genes detected in this study have been reported to be overexpressed in various human cancers, are associated with their prognosis and are significantly expressed in testicular seminoma tissues; but no significant difference in prognosis was reported. The role of these genes in TGCT is unclear; thus, further investigation is required.</p>
<p>Compared with normal testis samples, 11 DEMs were acquired in GSE59520 in seminoma samples. In the present study, <italic>hsa-miR-1182</italic> was downregulated in seminoma samples. Zhou <italic>et al</italic> (<xref rid="b37-mmr-20-05-4013" ref-type="bibr">37</xref>) reported that <italic>hsa-miR-1182</italic> is dysregulated in bladder cancer tissues and cell lines, in which functional assays were then performed, the overexpression of miR-1182 significantly inhibits bladder cancer cell proliferation, colony formation and invasion (<xref rid="b37-mmr-20-05-4013" ref-type="bibr">37</xref>,<xref rid="b38-mmr-20-05-4013" ref-type="bibr">38</xref>); however, the effects of <italic>hsa-miR-1182</italic> in seminoma are yet to be determined. <italic>Hsa-miR-650</italic> has been reported in many cancers. For example, Zhou <italic>et al</italic> (<xref rid="b39-mmr-20-05-4013" ref-type="bibr">39</xref>) observed that the expression of miR-650 in tumour tissues had a positive association with OS. <italic>Hsa-miR-650</italic> inhibited cell growth and invasion <italic>in vitro</italic> and <italic>in vivo</italic> (<xref rid="b40-mmr-20-05-4013" ref-type="bibr">40</xref>,<xref rid="b41-mmr-20-05-4013" ref-type="bibr">41</xref>). Furthermore, miR-650 targeted AKT2 and suppressed the activation of the AKT2/glycogen synthase kinase-3&#x03B2;/E-cadherin (<xref rid="b39-mmr-20-05-4013" ref-type="bibr">39</xref>). Interestingly, Yang <italic>et al</italic> (<xref rid="b42-mmr-20-05-4013" ref-type="bibr">42</xref>) suggested that phosphatase and tensin homolog/AKT signalling affects the expression of <italic>TOP2A</italic>, reducing cell growth and inducing the apoptosis of human breast cancer MCF-7 cells through ATP and caspase-3 signalling pathways (<xref rid="b42-mmr-20-05-4013" ref-type="bibr">42</xref>). In our study, <italic>TOP2A</italic> was identified as the target gene of <italic>hsa-miR-650</italic>, and <italic>hsa-miR-650</italic> was downregulated in seminoma, while <italic>TOP2A</italic> was upregulated. Thus, we proposed that in seminoma, the downregulation of <italic>hsa-miR-650</italic> could lead to the activation of the AKT pathway, upregulating <italic>TOP2A</italic> to affect seminoma cell migration and proliferation. At present, few studies have been conducted in the investigation of <italic>hsa-miR-934</italic>. For <italic>hsa-miR-1204</italic>, Xu <italic>et al</italic> (<xref rid="b43-mmr-20-05-4013" ref-type="bibr">43</xref>) revealed that <italic>hsa-miR-1204</italic> expression was significantly correlated with tumour size. The expression levels of <italic>hsa-miR-1204</italic> and glucose transporter-1 (GLUT-1) were significantly high in ovarian cancer (OC) patients (<xref rid="b43-mmr-20-05-4013" ref-type="bibr">43</xref>). The expression levels of <italic>hsa-miR-1204</italic> were positively correlated with the expression levels of GLUT-1 in OC patients. <italic>Hsa-miR-1204</italic> overexpression significantly promoted GLUT-1 expression, glucose uptake and cell proliferation. In our study, the target gene of <italic>hsa-miR-1204, CENPA</italic>, was revealed to mostly function in kinetochores and regulate cell division. The overexpression of <italic>CENPA</italic> is significantly related to colon cancer and neoplastic germ cells (<xref rid="b44-mmr-20-05-4013" ref-type="bibr">44</xref>,<xref rid="b45-mmr-20-05-4013" ref-type="bibr">45</xref>). <italic>Hsa-miR-1204</italic> and its target gene <italic>CENPA</italic> were both upregulated in seminoma; kinetochores are unique centromere macromolecular protein structures that attach chromosomes to the spindle for proper movement and segregation, during this process, an increasing amount of ATP is required (<xref rid="b46-mmr-20-05-4013" ref-type="bibr">46</xref>), and the overexpression of <italic>hsa-miR-1204</italic> can significantly promote GLUT-1 expression, glucose uptake and ATP production (<xref rid="b43-mmr-20-05-4013" ref-type="bibr">43</xref>). Thus, this pathway may affect the expression of <italic>CENPA</italic>; however, the association between <italic>CENPA</italic> and <italic>hsa-miR-1204</italic> requires further investigation. In addition, <italic>hsa-miR-661</italic> has been reported in non-small-cell lung cancer and OC (<xref rid="b47-mmr-20-05-4013" ref-type="bibr">47</xref>,<xref rid="b48-mmr-20-05-4013" ref-type="bibr">48</xref>). Hoffman <italic>et al</italic> (<xref rid="b49-mmr-20-05-4013" ref-type="bibr">49</xref>) found that low miR-661 expression correlates with poor outcomes in BRCA that typically express wild-type p53. In the present study, miR-661 was downregulated in seminoma. Of note, <italic>hsa-miR-1203</italic> has been reported to be dysregulated in prostate cancer, small cell carcinoma of the oesophagus and oesophageal squamous cell carcinoma (<xref rid="b50-mmr-20-05-4013" ref-type="bibr">50</xref>&#x2013;<xref rid="b52-mmr-20-05-4013" ref-type="bibr">52</xref>). In addition, Prashad <italic>et al</italic> (<xref rid="b53-mmr-20-05-4013" ref-type="bibr">53</xref>) reported that miR-665 suppresses neuroblastoma tumorigenesis by inhibiting c-MYC and suggested the potential of <italic>hsa-miR-665</italic> as an antineuroblastoma therapeutic factor. Dong <italic>et al</italic> (<xref rid="b54-mmr-20-05-4013" ref-type="bibr">54</xref>) found that miR-665 was downregulated in osteosarcoma tissues compared with nontumourous tissues, and the expression of miR-665 was inversely associated with the expression of Rab23 in the osteosarcoma tissues. These results suggest that miR-665 could act as a tumour suppressor gene in the development of osteosarcoma (<xref rid="b54-mmr-20-05-4013" ref-type="bibr">54</xref>); it has also been reported to be related to the Wnt/&#x03B2;-catenin signalling pathway (<xref rid="b55-mmr-20-05-4013" ref-type="bibr">55</xref>). In our study, miR-665 was downregulated in seminoma, and the target gene MKI67 was also associated with the Wnt/&#x03B2;-catenin signalling pathway (<xref rid="b34-mmr-20-05-4013" ref-type="bibr">34</xref>). For <italic>hsa-miR-640</italic>, Li <italic>et al</italic> (<xref rid="b56-mmr-20-05-4013" ref-type="bibr">56</xref>) demonstrated that miR-640 was downregulated in paclitaxel-resistant formalin-fixed paraffin-embedded tumour samples; however, Zhou <italic>et al</italic> (<xref rid="b57-mmr-20-05-4013" ref-type="bibr">57</xref>) found that miR-640 is related to the vascular endothelial growth factor receptor 2-mTOR pathway. In the present study, <italic>hsa-miR-640</italic> was downregulated in seminoma, and its target gene, MKI67, was also associated with mTOR (<xref rid="b58-mmr-20-05-4013" ref-type="bibr">58</xref>).</p>
<p>In summary, TOP2A, MKI67, PTPRC and UBE2C were revealed to be potentially associated with the PI3K/AKT and Wnt/&#x03B2;-catenin signalling pathways, while <italic>hsa-miR-650</italic> and <italic>hsa-miR-665</italic> were proposed to be linked the PI3K/AKT and Wnt/&#x03B2;-catenin signalling pathways. Moreover, TOP2A and MKI67 were strongly associated with the target genes of <italic>hsa-miR-650</italic> and <italic>hsa-miR-665</italic>, respectively.</p>
<p>At present, few bioinformatics analyses have been conducted to investigate DEGs and DEMs in seminoma. Of the DEGs screened in this study, only TOP2A and PTPRC have been reported in seminoma (<xref rid="b59-mmr-20-05-4013" ref-type="bibr">59</xref>,<xref rid="b60-mmr-20-05-4013" ref-type="bibr">60</xref>), to the best of our knowledge. Additionally, we screened the differential expression of genes from array data and predicted target genes of DEMs which were proposed to act together on the PI3K/AKT and Wnt/&#x03B2;-catenin signalling pathways with a strong correlation (<xref rid="b29-mmr-20-05-4013" ref-type="bibr">29</xref>,<xref rid="b39-mmr-20-05-4013" ref-type="bibr">39</xref>). The PI3K/AKT and Wnt/&#x03B2;-catenin signalling pathways participate in the growth, invasion, and migration of cancer cells in a variety of ways (<xref rid="b61-mmr-20-05-4013" ref-type="bibr">61</xref>&#x2013;<xref rid="b63-mmr-20-05-4013" ref-type="bibr">63</xref>). <italic>TOP2A, MKI67, PTPRC</italic> and <italic>UBE2C</italic> could be used as potential diagnostic biomarkers and therapeutic molecular targets for seminoma. In addition, the main treatment methods for seminoma in clinical practice are chemotherapy and testicular resection, which undoubtedly cause great physical burden to patients, particularly in individuals aged 15&#x2013;24 years (<xref rid="b7-mmr-20-05-4013" ref-type="bibr">7</xref>,<xref rid="b64-mmr-20-05-4013" ref-type="bibr">64</xref>). Therefore, our findings of the present study, including the genes identified, may serve as a basis for exploring gene therapy for seminoma in the future.</p>
<p>In this study, 287 differential genes for testicular seminoma were detected from the GEO database, and 5 pivotal genes and 8 miRNAs were screened, all of which were significantly differentially expressed in testicular cancer tissues. Among them, we predicted the target genes of the miRNAs. TOP2A, MKI67, PTPRC and UBE2C were determined to be associated with the PI3K/AKT and Wnt/&#x03B2;-catenin signalling pathways, and <italic>hsa-miR-650</italic> and <italic>hsa-miR-665</italic> were associated with the PI3K/AKT and Wnt/&#x03B2;-catenin signalling pathways. Furthermore, TOP2A and MKI67 were strongly associated with the target genes of <italic>hsa-miR-650</italic> and <italic>hsa-miR-665</italic>, respectively. To the best of our knowledge, <italic>hsa-miR-934</italic> has not been investigated. There may be certain associations that are yet to be identified; the hub genes we reported could have notable impact on cell proliferation and migration in testicular seminoma. In addition, in patients with testicular seminoma, PTPRC overexpression is an unfavourable prognostic factor, and further studies are needed to verify our findings. The results of the present study suggested that TOP2A, MKI67, CENPA, PTPRC, UBE2C, <italic>hsa-miR-650, hsa-miR-665, hsa-miR-640, hsa-miR-1182, hsa-miR-1203, hsa-miR-661</italic> and <italic>hsa-miR-1204</italic> may be potential targets for seminoma therapy.</p>
</sec>
</body>
<back>
<ack>
<title>Acknowledgements</title>
<p>Not applicable.</p>
</ack>
<sec>
<title>Funding</title>
<p>No funding was received.</p>
</sec>
<sec>
<title>Availability of data and materials</title>
<p>The datasests generated and/or analyzed during the current study are available from the Gene Expression Omnibus repository, <uri xlink:href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15220">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15220</uri>, <uri xlink:href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE1818">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE1818</uri> and <uri xlink:href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59520">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59520</uri>.</p>
</sec>
<sec>
<title>Authors&#x0027; contributions</title>
<p>KW and SZ made substantial contributions to the conception of the present study. KW performed the primary bioinformatics analysis and was a major contributor in writing the manuscript; YC made substantial contributions to data analysis, including the biological significance of hub genes and figure editing. ZZ and MF were involved in the interpretation of the hub genes data and edited the manuscript. All authors read and approved the final manuscript.</p>
</sec>
<sec>
<title>Ethics approval and consent to participate</title>
<p>Not applicable.</p>
</sec>
<sec>
<title>Patient consent for publication</title>
<p>Not applicable.</p>
</sec>
<sec>
<title>Competing interests</title>
<p>The authors declare that they have no competing interests.</p>
</sec>
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</back>
<floats-group>
<fig id="f1-mmr-20-05-4013" position="float">
<label>Figure 1.</label>
<caption><p>Venn diagram showing the intersecting genes of GSE1818 and GSE59520.</p></caption>
<graphic xlink:href="MMR-20-05-4013-g00.tif"/>
</fig>
<fig id="f2-mmr-20-05-4013" position="float">
<label>Figure 2.</label>
<caption><p>Volcano plot of the intersection of GSE1818 and GSE59520. Red indicates upregulated genes and green indicates downregulated genes.</p></caption>
<graphic xlink:href="MMR-20-05-4013-g01.tif"/>
</fig>
<fig id="f3-mmr-20-05-4013" position="float">
<label>Figure 3.</label>
<caption><p>PPI network. A PPI network of the differentially expressed genes; red indicates the upregulated genes, while green indicates the downregulated genes. PPI, protein-protein interaction.</p></caption>
<graphic xlink:href="MMR-20-05-4013-g02.tif"/>
</fig>
<fig id="f4-mmr-20-05-4013" position="float">
<label>Figure 4.</label>
<caption><p>PPI network of a significant module. A PPI network of the top five differentially expressed genes is shown. CENPA, centromere protein A; MKI67, marker of proliferation Ki-67; PPI, protein-protein interaction; PTPRC, protein tyrosine phosphatase receptor type C; TOP2A, DNA topoisomerase II &#x03B1;; UBE2C, ubiquitin conjugating enzyme E2 C.</p></caption>
<graphic xlink:href="MMR-20-05-4013-g03.tif"/>
</fig>
<fig id="f5-mmr-20-05-4013" position="float">
<label>Figure 5.</label>
<caption><p>Expression values of the top five DEGs in seminoma and non-seminoma tissues. The horizontal lines in the figure represent maximum, upper quartile, median, lower quartile, minimum from top to bottom. CENPA, centromere protein A; MKI67, marker of proliferation Ki-67; PTPRC, protein tyrosine phosphatase receptor type C; TGCT, testicular germ cell tumor; TOP2A, DNA topoisomerase II &#x03B1;; UBE2C, ubiquitin conjugating enzyme E2 C.</p></caption>
<graphic xlink:href="MMR-20-05-4013-g04.tif"/>
</fig>
<fig id="f6-mmr-20-05-4013" position="float">
<label>Figure 6.</label>
<caption><p>Gene Expression Profiling Interactive Analysis for overall survival associated with the expression of the five hub genes in patients with testicular cancer. Red line represents high expression, and blue line represents low expression. CENPA, centromere protein A; HR, hazard ratio; MKI67, marker of proliferation Ki-67; n, number of samples; PPI, protein-protein interaction; PTPRC, protein tyrosine phosphatase receptor type C; TPM, transcripts per million; TOP2A, DNA topoisomerase II &#x03B1;; UBE2C, ubiquitin conjugating enzyme E2 C.</p></caption>
<graphic xlink:href="MMR-20-05-4013-g05.tif"/>
</fig>
<fig id="f7-mmr-20-05-4013" position="float">
<label>Figure 7.</label>
<caption><p>Protein-protein interaction network of significant miRs and their target genes. Hsa, <italic>homo sapiens</italic>; miR, microRNA; MKI67, marker of proliferation Ki-67; PTPRC, protein tyrosine phosphatase receptor type C; TOP2A, DNA topoisomerase II &#x03B1;; UBE2C, ubiquitin conjugating enzyme E2 C.</p></caption>
<graphic xlink:href="MMR-20-05-4013-g06.tif"/>
</fig>
<table-wrap id="tI-mmr-20-05-4013" position="float">
<label>Table I.</label>
<caption><p>Significantly enriched Go terms and KEGG pathways of differentially expressed genes.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom" colspan="5">A, Upregulated</th>
</tr>
<tr>
<th align="left" valign="bottom" colspan="5"><hr/></th>
</tr>
<tr>
<th align="left" valign="bottom">Category</th>
<th align="center" valign="bottom">Term</th>
<th align="center" valign="bottom">Description</th>
<th align="center" valign="bottom">Count</th>
<th align="center" valign="bottom">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO:2000112</td>
<td align="left" valign="top">Regulation of cellular macromolecule biosynthetic process</td>
<td align="center" valign="top">13</td>
<td align="center" valign="top">0.000044</td>
</tr>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO: 0042113</td>
<td align="left" valign="top">B cell activation (GO:0042113)</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">0.000741</td>
</tr>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO:1903506</td>
<td align="left" valign="top">Regulation of nucleic acid-templated transcription</td>
<td align="center" valign="top">12</td>
<td align="center" valign="top">0.000130</td>
</tr>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO:0010468</td>
<td align="left" valign="top">Regulation of gene expression</td>
<td align="center" valign="top">15</td>
<td align="center" valign="top">0.000557</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0005925</td>
<td align="left" valign="top">Focal adhesion</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">0.000804</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0030670</td>
<td align="left" valign="top">Phagocytic vesicle membrane</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">0.000061</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0071556</td>
<td align="left" valign="top">Integral component of luminal side of endoplasmic reticulum membrane</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">0.000590</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0031901</td>
<td align="left" valign="top">Early endosome membrane</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">0.000741</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0042803</td>
<td align="left" valign="top">Protein homodimerization activity</td>
<td align="center" valign="top">16</td>
<td align="center" valign="top">7.14&#x00D7;10<sup>7</sup></td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0003723</td>
<td align="left" valign="top">RNA binding</td>
<td align="center" valign="top">18</td>
<td align="center" valign="top">0.000550</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0046982</td>
<td align="left" valign="top">Protein heterodimerization activity</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">0.000675</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0044212</td>
<td align="left" valign="top">Transcription regulatory region DNA binding</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">0.003244</td>
</tr>
<tr>
<td align="left" valign="top">KEGG pathway</td>
<td align="left" valign="top">hsa05230</td>
<td align="left" valign="top">Viral carcinogenesis</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">0.026682</td>
</tr>
<tr>
<td align="left" valign="top">KEGG pathway</td>
<td align="left" valign="top">hsa04670</td>
<td align="left" valign="top">Leukocyte transendothelial migration</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">0.027385</td>
</tr>
<tr>
<td align="left" valign="top">KEGG pathway</td>
<td align="left" valign="top">hsa04514</td>
<td align="left" valign="top">Cell adhesion molecules</td>
<td align="center" valign="top">6</td>
<td align="center" valign="top">0.000135</td>
</tr>
<tr>
<td align="center" valign="top" colspan="5"><hr/></td>
</tr>
<tr>
<td align="left" valign="top" colspan="5"><bold>B, Downregulated</bold></td>
</tr>
<tr>
<td align="left" valign="top" colspan="5"><hr/></td>
</tr>
<tr>
<td align="left" valign="top"><bold>Category</bold></td>
<td align="center" valign="top"><bold>Term</bold></td>
<td align="center" valign="top"><bold>Description</bold></td>
<td align="center" valign="top"><bold>Count</bold></td>
<td align="center" valign="top"><bold>P-value</bold></td>
</tr>
<tr>
<td align="center" valign="top" colspan="5"><hr/></td>
</tr>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO:0016339</td>
<td align="left" valign="top">Calcium-dependent cell-cell adhesion via plasma membrane cell adhesion molecules</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">0.000500</td>
</tr>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO:0007286</td>
<td align="left" valign="top">Spermatid development</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">0.004178</td>
</tr>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO:0007283</td>
<td align="left" valign="top">Spermatogenesis</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">0.047347</td>
</tr>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO:0098742</td>
<td align="left" valign="top">Cell-cell adhesion via plasma-membrane adhesion molecules</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">0.008733</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0000780</td>
<td align="left" valign="top">Condensed nuclear chromosome, centromeric region</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">0.005635</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0005868</td>
<td align="left" valign="top">Cytoplasmic dynein complex</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">0.015846</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0051233</td>
<td align="left" valign="top">Spindle midzone</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">0.030298</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0005925</td>
<td align="left" valign="top">Focal adhesion</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">0.038965</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0003774</td>
<td align="left" valign="top">Motor activity</td>
<td align="center" valign="top">6</td>
<td align="center" valign="top">0.000112</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0003777</td>
<td align="left" valign="top">Microtubule motor activity</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">0.002046</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0003779</td>
<td align="left" valign="top">Actin binding</td>
<td align="center" valign="top">6</td>
<td align="center" valign="top">0.025579</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0016887</td>
<td align="left" valign="top">ATPase activity</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">0.034558</td>
</tr>
<tr>
<td align="left" valign="top">KEGG pathway</td>
<td align="left" valign="top">hsa00531</td>
<td align="left" valign="top">Amphetamine addiction</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">0.002886</td>
</tr>
<tr>
<td align="left" valign="top">KEGG pathway</td>
<td align="left" valign="top">hsa04720</td>
<td align="left" valign="top">Long-term potentiation</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">0.020452</td>
</tr>
<tr>
<td align="left" valign="top">KEGG pathway</td>
<td align="left" valign="top">hsa04114</td>
<td align="left" valign="top">Oocyte meiosis in diabetic complication</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">0.023439</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn1-mmr-20-05-4013"><p>BP, biological process; CC, cellular component; DEG, differentially expressed gene; ECM, extracellular matrix; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; MF, molecular function.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="tII-mmr-20-05-4013" position="float">
<label>Table II.</label>
<caption><p>Top five hub genes with the highest degrees of connectivity.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom">Gene</th>
<th align="center" valign="bottom">Gene description</th>
<th align="center" valign="bottom">Degree</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top"><italic>TOP2A</italic></td>
<td align="left" valign="top">Topoisomerase (DNA) II &#x03B1; 170 kDa</td>
<td align="center" valign="top">33</td>
</tr>
<tr>
<td align="left" valign="top"><italic>UBE2C</italic></td>
<td align="left" valign="top">Ubiquitin-conjugating enzyme E2C</td>
<td align="center" valign="top">16</td>
</tr>
<tr>
<td align="left" valign="top"><italic>PTPRC</italic></td>
<td align="left" valign="top">Protein tyrosine phosphatase, receptor type, C</td>
<td align="center" valign="top">15</td>
</tr>
<tr>
<td align="left" valign="top"><italic>MKI67</italic></td>
<td align="left" valign="top">Antigen identified by monoclonal antibody Ki-67</td>
<td align="center" valign="top">13</td>
</tr>
<tr>
<td align="left" valign="top"><italic>CENPA</italic></td>
<td align="left" valign="top">Centromere protein A</td>
<td align="center" valign="top">13</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="tIII-mmr-20-05-4013" position="float">
<label>Table III.</label>
<caption><p>Significantly enriched GO terms and KEGG pathways of the top five hub genes.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom">Category</th>
<th align="center" valign="bottom">Term</th>
<th align="center" valign="bottom">Description</th>
<th align="center" valign="bottom">Count</th>
<th align="center" valign="bottom">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO:2001251</td>
<td align="left" valign="top">Negative regulation of chromosome organization</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.001749</td>
</tr>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO:1902099</td>
<td align="left" valign="top">Regulation of metaphase/anaphase transition of cell cycle</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.002248</td>
</tr>
<tr>
<td align="left" valign="top">BP term</td>
<td align="left" valign="top">GO:0010564</td>
<td align="left" valign="top">Regulation of cell cycle process</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.022500</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0000778</td>
<td align="left" valign="top">Condensed nuclear chromosome kinetochore</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">0.002997</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0005730</td>
<td align="left" valign="top">Nucleolus</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">0.010690</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0005694</td>
<td align="left" valign="top">Chromosome</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">0.000235</td>
</tr>
<tr>
<td align="left" valign="top">CC term</td>
<td align="left" valign="top">GO:0000152</td>
<td align="left" valign="top">Nuclear ubiquitin ligase complex</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.010460</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0061650</td>
<td align="left" valign="top">Ubiquitin-like protein conjugating enzyme activity</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.005488</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0019198</td>
<td align="left" valign="top">Transmembrane receptor protein phosphatase activity</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.003994</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0043130</td>
<td align="left" valign="top">Ubiquitin binding</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.015650</td>
</tr>
<tr>
<td align="left" valign="top">MF term</td>
<td align="left" valign="top">GO:0019901</td>
<td align="left" valign="top">Protein kinase binding</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">0.005841</td>
</tr>
<tr>
<td align="left" valign="top">KEGG pathway</td>
<td align="left" valign="top">hsa04514</td>
<td align="left" valign="top">Cell adhesion molecules</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.035000</td>
</tr>
<tr>
<td align="left" valign="top">KEGG pathway</td>
<td align="left" valign="top">hsa05340</td>
<td align="left" valign="top">Primary immunodeficiency</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.009217</td>
</tr>
<tr>
<td align="left" valign="top">KEGG pathway</td>
<td align="left" valign="top">hsa04666</td>
<td align="left" valign="top">Fc gamma R-mediated phagocytosis</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.023040</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn2-mmr-20-05-4013"><p>BP, biological process; CC, cellular component; DEG, differentially expressed gene; ECM, extracellular matrix; GO, Gene Ontology; hsa, <italic>homo sapiens</italic>; KEGG, Kyoto Encyclopedia of Genes and Genomes; MF, molecular function.</p></fn>
</table-wrap-foot>
</table-wrap>
</floats-group>
</article>