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<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "journalpublishing3.dtd">
<article xml:lang="en" article-type="research-article" xmlns:xlink="http://www.w3.org/1999/xlink">
<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.2019.10321</article-id>
<article-id pub-id-type="publisher-id">mmr-20-02-1343</article-id>
<article-categories>
<subj-group>
<subject>Articles</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Key genes associated with pancreatic cancer and their association with outcomes: A bioinformatics analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Wu</surname><given-names>Jiajia</given-names></name>
<xref rid="af1-mmr-20-02-1343" ref-type="aff">1</xref>
<xref rid="fn1-mmr-20-02-1343" ref-type="author-notes">&#x002A;</xref></contrib>
<contrib contrib-type="author"><name><surname>Li</surname><given-names>Zedong</given-names></name>
<xref rid="af2-mmr-20-02-1343" ref-type="aff">2</xref>
<xref rid="fn1-mmr-20-02-1343" ref-type="author-notes">&#x002A;</xref></contrib>
<contrib contrib-type="author"><name><surname>Zeng</surname><given-names>Kai</given-names></name>
<xref rid="af1-mmr-20-02-1343" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author"><name><surname>Wu</surname><given-names>Kangjian</given-names></name>
<xref rid="af1-mmr-20-02-1343" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author"><name><surname>Xu</surname><given-names>Dong</given-names></name>
<xref rid="af3-mmr-20-02-1343" ref-type="aff">3</xref></contrib>
<contrib contrib-type="author"><name><surname>Zhou</surname><given-names>Jun</given-names></name>
<xref rid="af2-mmr-20-02-1343" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author"><name><surname>Xu</surname><given-names>Lijian</given-names></name>
<xref rid="af1-mmr-20-02-1343" ref-type="aff">1</xref>
<xref rid="c1-mmr-20-02-1343" ref-type="corresp"/></contrib>
</contrib-group>
<aff id="af1-mmr-20-02-1343"><label>1</label>Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210000, P.R. China</aff>
<aff id="af2-mmr-20-02-1343"><label>2</label>Department of Minimally Invasive Surgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, P.R. China</aff>
<aff id="af3-mmr-20-02-1343"><label>3</label>Department of General Surgery, Gaochun People&#x0027;s Hospital, Nanjing, Jiangsu 211300, P.R. China</aff>
<author-notes>
<corresp id="c1-mmr-20-02-1343"><italic>Correspondence to</italic>: Professor Lijian Xu, Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, 121 Jiangjiayuan Road, Gulou, Nanjing, Jiangsu 210000, P.R. China, E-mail: <email>xulijian134@126.com</email></corresp>
<fn id="fn1-mmr-20-02-1343"><label>&#x002A;</label><p>Contributed equally</p></fn>
</author-notes>
<pub-date pub-type="ppub"><month>08</month><year>2019</year></pub-date>
<pub-date pub-type="epub"><day>03</day><month>06</month><year>2019</year></pub-date>
<volume>20</volume>
<issue>2</issue>
<fpage>1343</fpage>
<lpage>1352</lpage>
<history>
<date date-type="received"><day>04</day><month>10</month><year>2018</year></date>
<date date-type="accepted"><day>09</day><month>04</month><year>2019</year></date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2019, Spandidos Publications</copyright-statement>
<copyright-year>2019</copyright-year>
</permissions>
<abstract>
<p>Pancreatic cancer is a highly malignant neoplastic disease of the digestive system. In the present study, the dataset GSE62165 was downloaded from the Gene Expression Omnibus (GEO) database. GSE62165 contained the data of 118 pancreatic ductal adenocarcinoma samples (38 early-stage tumors, 62 lymph node metastases and 18 advanced tumors) and 13 control samples. Differences in the expression levels of genes between normal tissues and early-stage tumors were investigated. A total of 240 differentially expressed genes (DEGs) were identified using R software 3.5 (137 upregulated genes and 103 downregulated genes). Then, the differentially expressed genes were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. The following 18 core genes were identified using Cytoscape, based on the protein-interaction network of DEGs determined using the online tool STRING: <italic>EGF, ALB, COL17A1, FN1, TIMP1, PLAU, PLA2G1B, IGFBP3, PLAUR, VCAN, COL1A1, PNLIP, CTRL, PRSS3, COMP, CPB1, ITGA2</italic> and <italic>CEL</italic>. The pathways of the core genes were primarily associated with pancreatic secretion, protein digestion and absorption, and focal adhesion. Finally, survival analyses of core genes in pancreatic cancer were conducted using the UALCAN online database. It was revealed that <italic>PLAU</italic> and <italic>COL17A1</italic> were significantly associated with poor prognosis (P&#x003C;0.05). The expression levels of genes in primary pancreatic cancer tissues were then compared; only one gene, <italic>COL17A1</italic>, was identified to be significantly differentially expressed. Finally, another dataset from GEO, GSE28735, was analyzed to verify the upregulated expression of <italic>COL17A1</italic>. Taken together, the results of the present study have indicated that the expression of <italic>COL17A1</italic> gene may be associated with the occurrence and development of pancreatic cancer.</p>
</abstract>
<kwd-group>
<kwd>pancreatic cancer</kwd>
<kwd>bioinformatics analysis</kwd>
<kwd>prognosis</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec sec-type="intro">
<title>Introduction</title>
<p>Pancreatic cancer is a highly malignant neoplasm of the digestive system that accounts for &#x003E;200,000 deaths/year globally (<xref rid="b1-mmr-20-02-1343" ref-type="bibr">1</xref>). The incidence of pancreatic cancer is low compared with that of lung, breast, colorectal and gastric cancers; however, it is associated with a very high mortality rate. It has been reported that the incidence of pancreatic cancer is very similar to the associated mortality rate; the reported 5-year survival rate of patients with pancreatic cancer is &#x003C;6&#x0025; (<xref rid="b2-mmr-20-02-1343" ref-type="bibr">2</xref>). The mortality rate of patients with pancreatic cancer ranks fourth among common cancers, and is predicted to rise to second within a decade (<xref rid="b3-mmr-20-02-1343" ref-type="bibr">3</xref>). A number of factors have been identified as contributing to the etiopathogenesis of pancreatic cancer, including heredity, smoking, high-fat diet, chronic pancreatitis and consumption of nitrous acid compounds (<xref rid="b4-mmr-20-02-1343" ref-type="bibr">4</xref>). Due to the latency of pancreatic cancer, the majority of patients are diagnosed at an advanced stage, when tumor tissue has already infiltrated the surrounding tissues and has formed distant metastases, decreasing the usefulness of surgical interventions (<xref rid="b5-mmr-20-02-1343" ref-type="bibr">5</xref>). As a result of drug resistance, the efficacy of postoperative adjuvant therapy has also been very unsatisfactory (<xref rid="b6-mmr-20-02-1343" ref-type="bibr">6</xref>). Carbohydrate antigen 19-9 (CA19-9) is the most frequently used marker for the clinical diagnosis of cancer; the reported sensitivity and specificity of CA19-9 for the diagnosis of pancreatic cancer is 69-93 and 46&#x2013;98&#x0025;, respectively (<xref rid="b7-mmr-20-02-1343" ref-type="bibr">7</xref>). Therefore, early diagnosis and treatment are important to improve the prognosis and survival of patients with pancreatic cancer.</p>
<p>At present, high-throughput sequencing is employed in a variety of contexts, such as the discovery of gene mutations and chromosomal translocations that are closely associated with the occurrence and development of tumors (<xref rid="b8-mmr-20-02-1343" ref-type="bibr">8</xref>&#x2013;<xref rid="b10-mmr-20-02-1343" ref-type="bibr">10</xref>). High-throughput sequencing may be useful for the diagnosis of cancer and development of targeted therapies. These analyses may provide novel insights to guide subsequent research.</p>
</sec>
<sec sec-type="materials|methods">
<title>Materials and methods</title>
<sec>
<title/>
<sec>
<title>Microarray data</title>
<p>The gene expression profile of GSE62165 (<xref rid="b11-mmr-20-02-1343" ref-type="bibr">11</xref>) was downloaded from the GEO database (<xref rid="b12-mmr-20-02-1343" ref-type="bibr">12</xref>). The data were created using the GPL13667 Affymetrix<sup>&#x00AE;</sup> Human Genome U219 array (Affymetrix; Thermo Fisher Scientific, Inc.). GSE62165 contained data on 118 pancreatic ductal adenocarcinoma (PDAC) samples and 13 control samples. Data were standardized using the robust multi-array average (RMA) algorithm using limma package (version 3.38.3) (<xref rid="b13-mmr-20-02-1343" ref-type="bibr">13</xref>). In addition, a separate dataset, GSE28735 (<xref rid="b14-mmr-20-02-1343" ref-type="bibr">14</xref>,<xref rid="b15-mmr-20-02-1343" ref-type="bibr">15</xref>), was used to verify the results. The expression profiles included 45 matched pairs of pancreatic tumor and adjacent non-tumor tissues from 45 patients with PDAC. The Cancer Genome Atlas (TCGA; <uri xlink:href="http://cancergenome.nih.gov/">http://cancergenome.nih.gov/</uri>) contains genomic sequencing data involving 33 species of cancer.</p>
</sec>
<sec>
<title>Identification of differentially expressed genes (DEGs)</title>
<p>The limma package (version 3.38.3) (<xref rid="b13-mmr-20-02-1343" ref-type="bibr">13</xref>) was used to identify DEGs between pancreatic cancer tissue and normal pancreatic tissue samples in R software (version 3.5; <uri xlink:href="https://www.R-project.org">http://www.R-project.org</uri>). |log2 Fold Change (FC)|&#x003E;3.0 and adjusted P-value &#x003C;0.05 were considered to be the threshold for differential gene identification.</p>
</sec>
<sec>
<title>Gene Ontology (GO) and Kyoto Encyclopedia of genes and genomes (KEGG) pathway analysis of DEGs</title>
<p>GO (<uri xlink:href="http://www.geneontology.org/">http://www.geneontology.org/</uri>) and the KEGG (<uri xlink:href="https://www.kegg.jp/">https://www.kegg.jp/</uri>) (<xref rid="b16-mmr-20-02-1343" ref-type="bibr">16</xref>&#x2013;<xref rid="b19-mmr-20-02-1343" ref-type="bibr">19</xref>) were used to analyze the function of DEGs using the cluster Profiler R package (<xref rid="b20-mmr-20-02-1343" ref-type="bibr">20</xref>). P&#x003C;0.05 was considered to indicate a statistically significant difference in functional enrichment analysis.</p>
</sec>
<sec>
<title>Core genes screening from the protein-protein interaction (PPI) network</title>
<p>A PPI network for the DEGs was generated using the STRING database (<uri xlink:href="https://string-db.org/">https://string-db.org/</uri>). Then, Cytoscape (version 3.6.1) (<xref rid="b21-mmr-20-02-1343" ref-type="bibr">21</xref>) was employed, and a plug-in termed cytohubba (<xref rid="b22-mmr-20-02-1343" ref-type="bibr">22</xref>) was integrated into the software. The plug-in provides 12 types of topological analysis methods [Maximal Clique Centrality, Maximum Neighborhood Component (MNC), Density of MNC, Degree, Edge Percolated Component, Bottleneck, EcCentricity, Closeness, Radiality, Betweenness, Stress and Clustering Coefficient). Using 12 analysis methods, we identified the top 18 genes as core genes.</p>
</sec>
<sec>
<title>Expression levels and survival analysis of core genes in pancreatic cancer</title>
<p>UALCAN (<uri xlink:href="http://ualcan.path.uab.edu/index.html">http://ualcan.path.uab.edu/index.html</uri>) (<xref rid="b23-mmr-20-02-1343" ref-type="bibr">23</xref>) was employed to perform survival analysis based on the information of TCGA database. Survival analysis was performed via the Kaplan-Meier method using 18 identified core genes, based on their core gene expression levels in pancreatic adenocarcinoma (PAAD). P&#x003C;0.05 was considered to be statistically significant. The P-value was calculated using log-rank test. The &#x2018;scaled_estimate&#x2019; column provided the potential transcripts produced by each gene. The &#x2018;scaled_estimate&#x2019; was multiplied by 10<sup>6</sup> to obtain a transcripts per million (TPM) expression value (<xref rid="b24-mmr-20-02-1343" ref-type="bibr">24</xref>). Gene expression levels in tumor tissues exhibited notable inter-individual variability. High expression indicated that the TPM value was above the upper quartile value. Low expression indicated that the TPM value was equal or below the upper quartile value.</p>
</sec>
<sec>
<title>Verification of results</title>
<p>The findings from the bioinformatics analyses were validated using the dataset GSE28735 from the GEO database. The expression profiles included 45 matched pairs of pancreatic tumor and adjacent non-tumor tissues from 45 patients with PDAC. The online analysis tool GEO2R (<uri xlink:href="https://www.ncbi.nlm.nih.gov/geo/geo2r/">https://www.ncbi.nlm.nih.gov/geo/geo2r/</uri>) was used to determine the expression of DEGs. We further verified the expression of COL17A1.</p>
</sec>
</sec>
</sec>
<sec sec-type="results">
<title>Results</title>
<sec>
<title/>
<sec>
<title>Analysis of DEGs</title>
<p>The selected chipset GSE62165 included 118 PDAC samples and 13 control samples. Differences in gene expression profiles were analyzed using 38 early-stage tumors and 13 normal tissues. A total of 240 DEGs (adjusted P-value &#x003C;0.05; |log<sub>2</sub>FC|&#x2265;3.0) were identified using R version 3.5 software, including 137 upregulated genes and 103 downregulated genes (<xref rid="tI-mmr-20-02-1343" ref-type="table">Table I</xref>). The heat map of genes with upregulated expression is presented in <xref rid="f1-mmr-20-02-1343" ref-type="fig">Fig. 1</xref>. A volcanic map of all genes is presented in <xref rid="f2-mmr-20-02-1343" ref-type="fig">Fig. 2</xref>.</p>
</sec>
<sec>
<title>Enrichment analysis of DEGs</title>
<p>To investigated the distribution of DEGs, GO and KEGG analysis of upregulated and downregulated genes was conducted. GO analysis revealed that the &#x2018;biological processes&#x2019; (BPs) of upregulated genes mainly included extracellular matrix organization, extracellular structure organization and collagen catabolic process. &#x2018;Molecular functions&#x2019; (MFs) of upregulated DEGs primarily included extracellular matrix structural constituents, glycosaminoglycan binding and cytokine activity. For the &#x2018;cell components&#x2019; (CCs) identified by GO analysis, proteinaceous extracellular matrix, extracellular matrix component and endoplasmic reticulum lumen were the most prominent (<xref rid="tII-mmr-20-02-1343" ref-type="table">Table II</xref>). For downregulated DEGs, the main enriched BPs were digestion, lipid digestion and sulfur amino acid metabolic process, whereas the primary MFs were exopeptidase activity, serine-type endopeptidase activity and serine-type peptidase activity (<xref rid="tII-mmr-20-02-1343" ref-type="table">Table II</xref>). <xref rid="f3-mmr-20-02-1343" ref-type="fig">Figs. 3</xref> and <xref rid="f4-mmr-20-02-1343" ref-type="fig">4</xref> present the associations between genes and enrichment results, indicating the genes that were highly changed between the two conditions.</p>
<p><xref rid="tIII-mmr-20-02-1343" ref-type="table">Table III</xref> presents KEGG pathway analysis of the DEGs, revealing that the upregulated genes were mainly located in extracellular matrix (ECM)-receptor interaction, protein digestion and absorption, and focal adhesion pathways. Conversely, downregulated genes were primarily located in pancreatic secretion, protein digestion and absorption, and fat digestion and absorption pathways. <xref rid="f5-mmr-20-02-1343" ref-type="fig">Figs. 5</xref> and <xref rid="f6-mmr-20-02-1343" ref-type="fig">6</xref> present the distribution of the major KEGG pathways generated using clusterProfiler. It was observed that ECM-receptor interactions (<xref rid="f5-mmr-20-02-1343" ref-type="fig">Fig. 5</xref>) and pancreatic secretion (<xref rid="f6-mmr-20-02-1343" ref-type="fig">Fig. 6</xref>) were the pathways most enriched with up- and downregulated DEGs, respectively.</p>
</sec>
<sec>
<title>Screening of core genes in the PPI</title>
<p>Based on the information in the STRING database and using 12 types of calculation methods in Cytoscape, the following 18 core genes were identified: <italic>EGF, ALB, COL17A1, FN1, TIMP1, PLAU, PLA2G1B, IGFBP3, PLAUR, VCAN, COL1A1, PNLIP, CTRL, PRSS3, COMP, CPB1, ITGA2</italic> and <italic>CEL</italic>. These core genes were associated with each other and may exhibit synergistic effects in the development of pancreatic cancer (<xref rid="f7-mmr-20-02-1343" ref-type="fig">Fig. 7</xref>). According to the previous enrichment analysis, the core genes, were mainly located in pancreatic secretion, protein digestion and absorption, and focal adhesion pathways.</p>
</sec>
<sec>
<title>Gene expression level and survival analysis</title>
<p>Notably, COL17A1 and PLAU genes were the only genes associated with survival. Following the identification of core genes, survival analysis for PAAD was performed using UALCAN. <italic>PLAU</italic> [which encodes the serine protease urokinase-type plasminogen activator (uPA); <xref rid="f8-mmr-20-02-1343" ref-type="fig">Fig. 8</xref>] and <italic>COL17A1</italic> [which encodes collagen type XVII &#x03B1;1 chain (COL17A1); <xref rid="f9-mmr-20-02-1343" ref-type="fig">Fig. 9</xref>] were demonstrated to be significantly associated with survival (P&#x003C;0.05). Subsequently, the expression levels of genes in primary pancreatic cancer were compared; only one gene was identified to be significantly differentially expressed, <italic>COL17A1</italic>, whereas PLAU was not significantly differentially expressed. The expression levels of <italic>COL17A1</italic> were analyzed in TCGA database, and the results were consistent with those of the aforementioned differential gene analysis; <italic>COL17A1</italic> was significantly upregulated in PAAD tumor tissues compared with normal tissues (P=1.62&#x00D7;10<sup>&#x2212;12</sup>; <xref rid="f10-mmr-20-02-1343" ref-type="fig">Fig. 10</xref>).</p>
</sec>
<sec>
<title>Verification of COL17A1</title>
<p>Differences in gene expression between 45 pancreatic cancer patients and 45 normal pancreatic tissues were analyzed. In particular, the expression level of COL17A1 was investigated. The results of the analysis to verify the importance of <italic>COL17A1</italic> are presented in <xref rid="tIV-mmr-20-02-1343" ref-type="table">Table IV</xref>; it was observed that <italic>COL17A1</italic> was significantly upregulated in pancreatic tumor tissue in the two GEO databases.</p>
</sec>
</sec>
</sec>
<sec sec-type="discussion">
<title>Discussion</title>
<p>The incidence of pancreatic cancer and the associated mortality rates have exhibited an increasing trend in previous years (<xref rid="b3-mmr-20-02-1343" ref-type="bibr">3</xref>). Studies have reported that patients with pancreatic cancer survive for only 4 months on average without treatment; even in patients who undergo treatment, the survival is not significantly extended (<xref rid="b25-mmr-20-02-1343" ref-type="bibr">25</xref>). Therefore, accurate early diagnosis of pancreatic cancer and the development of effective targeted therapy is of major importance.</p>
<p>A previous study identified core genes in pancreatic cancer that were reported to be of diagnostic relevance (<xref rid="b26-mmr-20-02-1343" ref-type="bibr">26</xref>). In the present study, the chipset GSE62165 from the GEO was analyzed, containing data of 118 PDAC and 13 normal pancreatic tissues (<xref rid="b11-mmr-20-02-1343" ref-type="bibr">11</xref>). Differences in gene expression levels were only compared between normal tissues and early-stage tumor tissue. A total of 240 DEGs (137 upregulated and 103 downregulated) were identified using R, and GO (<xref rid="b27-mmr-20-02-1343" ref-type="bibr">27</xref>) and KEGG pathway analyses of DEGs revealed the locations and functions of DEGs. Upregulated genes were mainly located in the ECM and collagen trimers, and were involved in ECM organization and ECM-receptor interactions, focal adhesion, and protein digestion and absorption. Conversely, downregulated genes were mainly enriched in digestion and exopeptidase activity pathways. A PPI network was built, and 18 core genes were identified; the prognostic value of these genes for patients with pancreatic cancer was analyzed using UACLAN. <italic>PLAU</italic> and <italic>COL17A1</italic> were significantly associated with poorer survival; it was then revealed using data from TCGA that <italic>COL17A1</italic> was significantly upregulated in pancreatic cancer tissues compared with control tissues, consistent with the results of the differential gene analysis. It was predicted that these two genes may be associated with the proliferation, invasion and metastasis of pancreatic cancer.</p>
<p><italic>PLAU</italic> encodes a serine protease, uPA (<xref rid="b28-mmr-20-02-1343" ref-type="bibr">28</xref>). Following GO and KEGG analyses, the functional enrichment of PLAU was investigated. <italic>PLAU</italic> is mainly involved in the regulation of cell motility, cellular component movement and locomotion (<xref rid="b29-mmr-20-02-1343" ref-type="bibr">29</xref>). It is primarily expressed in the endoplasmic reticulum lumen and invadopodium (<xref rid="b30-mmr-20-02-1343" ref-type="bibr">30</xref>). PLAU plays a key role in regulating cell migration and adhesion during tissue regeneration and intracellular signaling (<xref rid="b31-mmr-20-02-1343" ref-type="bibr">31</xref>). Increased expression of COL17A1 leads to tumor cell invasion and metastasis of tumor cells to surrounding tissues (<xref rid="b32-mmr-20-02-1343" ref-type="bibr">32</xref>). PLAU is involved in predicting the survival rate of patients with gastric cancer (<xref rid="b33-mmr-20-02-1343" ref-type="bibr">33</xref>). It may serve an important role in the invasion and metastasis of pancreatic cancer cells (<xref rid="b34-mmr-20-02-1343" ref-type="bibr">34</xref>); however, the specific pathways involved are yet to be determined. It is hypothesized that <italic>PLAU</italic> may serve an important role in the diagnosis and treatment of pancreatic cancer in the future.</p>
<p>COL17A1 is mainly located in the extracellular matrix and collagen trimmers (<xref rid="b35-mmr-20-02-1343" ref-type="bibr">35</xref>). Extracellular matrix molecules, including proteoglycan and fibrin, have been reported to affect the growth, migration and differentiation of cells (<xref rid="b36-mmr-20-02-1343" ref-type="bibr">36</xref>). A study showed that COL17A1 can inhibit the migration and invasion of breast cancer cells, acting as a p53 transcriptional target gene (<xref rid="b37-mmr-20-02-1343" ref-type="bibr">37</xref>). A previous study has reported that the extracellular matrix is closely associated with the metastasis of breast cancer (<xref rid="b38-mmr-20-02-1343" ref-type="bibr">38</xref>). High levels of collagen in breast and colorectal cancers have been associated with tumor invasion (<xref rid="b39-mmr-20-02-1343" ref-type="bibr">39</xref>,<xref rid="b40-mmr-20-02-1343" ref-type="bibr">40</xref>). A previous study that employed the minimum-redundancy-maximum-relevance method also identified <italic>COL17A1</italic> as a core gene of pancreatic cancer (<xref rid="b26-mmr-20-02-1343" ref-type="bibr">26</xref>); however, in the present study, the upregulated expression of <italic>COL17A1</italic> in pancreatic cancer was verified in multiple datasets, and its effects on patient survival were determined. Survival analysis using UACLAN based on data from TCGA revealed that the expression levels of <italic>CLO17A1</italic> were closely associated with the survival of patients with pancreatic cancer, and that <italic>CLO17A1</italic> was highly expressed in primary pancreatic tumor tissues. The present findings suggested that the expression of <italic>COL17A1</italic> is associated with the occurrence and development of pancreatic cancer. Therefore, this bioinformatics analysis may provide novel insight for future studies investigating the pathogenesis of pancreatic cancer.</p>
<p>However, the present study presented certain limitations. In examining the expression level of COL17A1, only four normal samples were investigated, and further studies examining a high number of control samples are required to confirm the present results.</p>
</sec>
</body>
<back>
<ack>
<title>Acknowledgements</title>
<p>Not applicable.</p>
</ack>
<sec>
<title>Funding</title>
<p>The present work was supported by The &#x2018;Six Talents Summit&#x2019; Project in Jiangsu Province, miR-203 targets Survivin to upregulate the expression of Caspase-3 and promote the apoptosis of pancreatic cancer cells (grant no. WAW-008).</p>
</sec>
<sec>
<title>Availability of data and materials</title>
<p>The datasets used and/or analyzed in the present study are available in the GEO (<uri xlink:href="http://www.ncbi.nlm.nih.gov/geo">http://www.ncbi.nlm.nih.gov/geo</uri>) and UALCAN (<uri xlink:href="http://ualcan.path.uab.edu">http://ualcan.path.uab.edu</uri>) repositories.</p>
</sec>
<sec>
<title>Authors&#x0027; contributions</title>
<p>JZ and LX conceived the study. JW, ZL, KW, KZ and DX analyzed the data and drafted the manuscript. All authors reviewed 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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<title>References</title>
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</back>
<floats-group>
<fig id="f1-mmr-20-02-1343" position="float">
<label>Figure 1.</label>
<caption><p>Heat map of gene expression in pancreatic ductal adenocarcinoma tissues and healthy controls. The expression levels of various genes in 51 samples (38 early-stage tumor samples and 13 controls) are presented. Green indicates downregulated expression; red indicates upregulated expression; black indicates no significant difference in expression.</p></caption>
<graphic xlink:href="MMR-20-02-1343-g00.tif"/>
</fig>
<fig id="f2-mmr-20-02-1343" position="float">
<label>Figure 2.</label>
<caption><p>Volcano plot of the expression of genes in patients with early-stage pancreatic ductal adenocarcinoma. The expression of all identified genes in tumor tissues compared with in healthy control samples is presented. Blue indicates downregulated genes; red indicates upregulated genes; grey indicates genes that were not significantly differentially expressed. FC, fold change.</p></caption>
<graphic xlink:href="MMR-20-02-1343-g01.tif"/>
</fig>
<fig id="f3-mmr-20-02-1343" position="float">
<label>Figure 3.</label>
<caption><p>Functions of genes upregulated in pancreatic cancer tissues. Heat plot of the cell components, molecular functions and biological processes of upregulated genes in pancreatic cancer tissues, as identified by Gene Ontology analysis.</p></caption>
<graphic xlink:href="MMR-20-02-1343-g02.tif"/>
</fig>
<fig id="f4-mmr-20-02-1343" position="float">
<label>Figure 4.</label>
<caption><p>Functions of genes downregulated in pancreatic cancer tissues. Heat plot of the molecular functions and biological processes of downregulated genes in pancreatic cancer tissues, as identified by Gene Ontology analysis.</p></caption>
<graphic xlink:href="MMR-20-02-1343-g03.tif"/>
</fig>
<fig id="f5-mmr-20-02-1343" position="float">
<label>Figure 5.</label>
<caption><p>Pathways enriched with genes upregulated in pancreatic cancer. Net plot of the pathways enriched with genes identified as upregulated in pancreatic cancer tissues, as identified by Kyoto Encyclopedia of Genes and Genomes pathway analysis. ECM, extracellular matrix; IL-17, interleukin-17.</p></caption>
<graphic xlink:href="MMR-20-02-1343-g04.tif"/>
</fig>
<fig id="f6-mmr-20-02-1343" position="float">
<label>Figure 6.</label>
<caption><p>Pathways enriched with genes downregulated in pancreatic cancer. Net plot of the pathways enriched with genes identified as downregulated in pancreatic cancer tissues, as identified by Kyoto Encyclopedia of Genes and Genomes pathway analysis.</p></caption>
<graphic xlink:href="MMR-20-02-1343-g05.tif"/>
</fig>
<fig id="f7-mmr-20-02-1343" position="float">
<label>Figure 7.</label>
<caption><p>Protein-protein interaction network of the 18 identified core genes.</p></caption>
<graphic xlink:href="MMR-20-02-1343-g06.tif"/>
</fig>
<fig id="f8-mmr-20-02-1343" position="float">
<label>Figure 8.</label>
<caption><p>Survival analysis of <italic>PLAU</italic> in PAAD. Kaplan-Meier analysis of the association between the expression of <italic>PLAU</italic> and the overall survival of patients with PAAD. PAAD, pancreatic adenocarcinoma; <italic>PLAU</italic>, gene encoding urokinase-type plasminogen activator.</p></caption>
<graphic xlink:href="MMR-20-02-1343-g07.tif"/>
</fig>
<fig id="f9-mmr-20-02-1343" position="float">
<label>Figure 9.</label>
<caption><p>Survival analysis of <italic>COL17A1</italic> in PAAD. Kaplan-Meier analysis of the association between the expression of <italic>COL17A1</italic> and the overall survival of patients with PAAD. PAAD, pancreatic adenocarcinoma; <italic>COL17A1</italic>, gene encoding collagen type XVII &#x03B1;1 chain.</p></caption>
<graphic xlink:href="MMR-20-02-1343-g08.tif"/>
</fig>
<fig id="f10-mmr-20-02-1343" position="float">
<label>Figure 10.</label>
<caption><p>Expression levels of <italic>COL17A1</italic> in PAAD and normal tissues. The expression of <italic>COL17A1</italic> was compared between PAAD primary tumor and normal control tissues, based on data from TCGA. PAAD, pancreatic adenocarcinoma; <italic>COL17A1</italic>, gene encoding collagen type XVII &#x03B1;1 chain; TCGA, The Cancer Genome Atlas.</p></caption>
<graphic xlink:href="MMR-20-02-1343-g09.tif"/>
</fig>
<table-wrap id="tI-mmr-20-02-1343" position="float">
<label>Table I.</label>
<caption><p>Top 20 differentially expressed genes in early-stage pancreatic cancer tissues based on Log2FC.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom" colspan="3">A, Upregulated genes</th>
</tr>
<tr>
<th align="left" valign="bottom" colspan="3"><hr/></th>
</tr>
<tr>
<th align="left" valign="bottom">Gene symbol</th>
<th align="center" valign="bottom">Log2FC</th>
<th align="center" valign="bottom">Adjusted P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">COL1A1</td>
<td align="center" valign="top">5.9240335</td>
<td align="center" valign="top">3.17&#x00D7;10<sup>&#x2212;16</sup></td>
</tr>
<tr>
<td align="left" valign="top">KRT17</td>
<td align="center" valign="top">5.5334643</td>
<td align="center" valign="top">4.10&#x00D7;10<sup>&#x2212;12</sup></td>
</tr>
<tr>
<td align="left" valign="top">CEACAM5</td>
<td align="center" valign="top">5.3990511</td>
<td align="center" valign="top">1.66&#x00D7;10<sup>&#x2212;09</sup></td>
</tr>
<tr>
<td align="left" valign="top">S100P</td>
<td align="center" valign="top">5.2665291</td>
<td align="center" valign="top">1.66&#x00D7;10<sup>&#x2212;13</sup></td>
</tr>
<tr>
<td align="left" valign="top">COL10A1</td>
<td align="center" valign="top">5.2258147</td>
<td align="center" valign="top">1.17&#x00D7;10<sup>&#x2212;17</sup></td>
</tr>
<tr>
<td align="left" valign="top">SERPINB5</td>
<td align="center" valign="top">5.1642588</td>
<td align="center" valign="top">5.50&#x00D7;10<sup>&#x2212;15</sup></td>
</tr>
<tr>
<td align="left" valign="top">GJB2</td>
<td align="center" valign="top">5.0747799</td>
<td align="center" valign="top">7.98&#x00D7;10<sup>&#x2212;18</sup></td>
</tr>
<tr>
<td align="left" valign="top">COL17A1</td>
<td align="center" valign="top">5.0501325</td>
<td align="center" valign="top">1.80&#x00D7;10<sup>&#x2212;11</sup></td>
</tr>
<tr>
<td align="left" valign="top">CXCL5</td>
<td align="center" valign="top">5.0384043</td>
<td align="center" valign="top">1.28&#x00D7;10<sup>&#x2212;11</sup></td>
</tr>
<tr>
<td align="left" valign="top">TMPRSS4</td>
<td align="center" valign="top">5.0203823</td>
<td align="center" valign="top">2.37&#x00D7;10<sup>&#x2212;16</sup></td>
</tr>
<tr>
<td align="left" valign="top">SDR16C5</td>
<td align="center" valign="top">4.9961337</td>
<td align="center" valign="top">3.16&#x00D7;10<sup>&#x2212;16</sup></td>
</tr>
<tr>
<td align="left" valign="top">CTHRC1</td>
<td align="center" valign="top">4.9626426</td>
<td align="center" valign="top">7.77&#x00D7;10<sup>&#x2212;20</sup></td>
</tr>
<tr>
<td align="left" valign="top">COL11A1</td>
<td align="center" valign="top">4.9350078</td>
<td align="center" valign="top">6.41&#x00D7;10<sup>&#x2212;17</sup></td>
</tr>
<tr>
<td align="left" valign="top">SLC6A14</td>
<td align="center" valign="top">4.8841916</td>
<td align="center" valign="top">2.47&#x00D7;10<sup>&#x2212;15</sup></td>
</tr>
<tr>
<td align="left" valign="top">MMP11</td>
<td align="center" valign="top">4.8824426</td>
<td align="center" valign="top">3.14&#x00D7;10<sup>&#x2212;16</sup></td>
</tr>
<tr>
<td align="left" valign="top">SULF1</td>
<td align="center" valign="top">4.721966</td>
<td align="center" valign="top">2.96&#x00D7;10<sup>&#x2212;17</sup></td>
</tr>
<tr>
<td align="left" valign="top">FN1</td>
<td align="center" valign="top">4.6424864</td>
<td align="center" valign="top">2.99&#x00D7;10<sup>&#x2212;16</sup></td>
</tr>
<tr>
<td align="left" valign="top">POSTN</td>
<td align="center" valign="top">4.6415794</td>
<td align="center" valign="top">1.33&#x00D7;10<sup>&#x2212;16</sup></td>
</tr>
<tr>
<td align="left" valign="top">CCL18</td>
<td align="center" valign="top">4.5489901</td>
<td align="center" valign="top">1.41&#x00D7;10<sup>&#x2212;11</sup></td>
</tr>
<tr>
<td align="left" valign="top">MUC4</td>
<td align="center" valign="top">4.5022059</td>
<td align="center" valign="top">1.25&#x00D7;10<sup>&#x2212;09</sup></td>
</tr>
<tr>
<td align="center" valign="top" colspan="3"><hr/></td>
</tr>
<tr>
<td align="left" valign="top" colspan="3"><bold>B, Downregulated genes</bold></td>
</tr>
<tr>
<td align="left" valign="top" colspan="3"><hr/></td>
</tr>
<tr>
<td align="left" valign="top"><bold>Gene symbol</bold></td>
<td align="center" valign="top"><bold>Log2FC</bold></td>
<td align="center" valign="top"><bold>Adjusted P-value</bold></td>
</tr>
<tr>
<td align="center" valign="top" colspan="3"><hr/></td>
</tr>
<tr>
<td align="left" valign="top">SYCN</td>
<td align="center" valign="top">&#x2212;6.6535946</td>
<td align="center" valign="top">2.74&#x00D7;10<sup>&#x2212;07</sup></td>
</tr>
<tr>
<td align="left" valign="top">SERPINI2</td>
<td align="center" valign="top">&#x2212;6.2894352</td>
<td align="center" valign="top">8.73&#x00D7;10<sup>&#x2212;09</sup></td>
</tr>
<tr>
<td align="left" valign="top">AQP8</td>
<td align="center" valign="top">&#x2212;6.2356139</td>
<td align="center" valign="top">2.11&#x00D7;10<sup>&#x2212;10</sup></td>
</tr>
<tr>
<td align="left" valign="top">AMY1A</td>
<td align="center" valign="top">&#x2212;6.1790263</td>
<td align="center" valign="top">4.38&#x00D7;10<sup>&#x2212;10</sup></td>
</tr>
<tr>
<td align="left" valign="top">ALB</td>
<td align="center" valign="top">&#x2212;6.1165814</td>
<td align="center" valign="top">2.16&#x00D7;10<sup>&#x2212;08</sup></td>
</tr>
<tr>
<td align="left" valign="top">CELA2A</td>
<td align="center" valign="top">&#x2212;6.0845313</td>
<td align="center" valign="top">2.83&#x00D7;10<sup>&#x2212;06</sup></td>
</tr>
<tr>
<td align="left" valign="top">PNLIPRP1</td>
<td align="center" valign="top">&#x2212;6.0676353</td>
<td align="center" valign="top">6.52&#x00D7;10<sup>&#x2212;10</sup></td>
</tr>
<tr>
<td align="left" valign="top">CTRL</td>
<td align="center" valign="top">&#x2212;5.9224624</td>
<td align="center" valign="top">1.73&#x00D7;10<sup>&#x2212;06</sup></td>
</tr>
<tr>
<td align="left" valign="top">PDIA2</td>
<td align="center" valign="top">&#x2212;5.9185276</td>
<td align="center" valign="top">4.65&#x00D7;10<sup>&#x2212;09</sup></td>
</tr>
<tr>
<td align="left" valign="top">CPA1</td>
<td align="center" valign="top">&#x2212;5.804844</td>
<td align="center" valign="top">5.21&#x00D7;10<sup>&#x2212;06</sup></td>
</tr>
<tr>
<td align="left" valign="top">TMED6</td>
<td align="center" valign="top">&#x2212;5.7967792</td>
<td align="center" valign="top">2.37&#x00D7;10<sup>&#x2212;10</sup></td>
</tr>
<tr>
<td align="left" valign="top">CELP</td>
<td align="center" valign="top">&#x2212;5.7183603</td>
<td align="center" valign="top">1.15&#x00D7;10<sup>&#x2212;10</sup></td>
</tr>
<tr>
<td align="left" valign="top">AQP12A</td>
<td align="center" valign="top">&#x2212;5.6598636</td>
<td align="center" valign="top">3.88&#x00D7;10<sup>&#x2212;14</sup></td>
</tr>
<tr>
<td align="left" valign="top">CUZD1</td>
<td align="center" valign="top">&#x2212;5.5766969</td>
<td align="center" valign="top">1.68&#x00D7;10<sup>&#x2212;06</sup></td>
</tr>
<tr>
<td align="left" valign="top">CELA2B</td>
<td align="center" valign="top">&#x2212;5.5649112</td>
<td align="center" valign="top">2.23&#x00D7;10<sup>&#x2212;05</sup></td>
</tr>
<tr>
<td align="left" valign="top">CPA2</td>
<td align="center" valign="top">&#x2212;5.55513</td>
<td align="center" valign="top">3.43&#x00D7;10<sup>&#x2212;06</sup></td>
</tr>
<tr>
<td align="left" valign="top">CELA3A</td>
<td align="center" valign="top">&#x2212;5.5508171</td>
<td align="center" valign="top">1.84&#x00D7;10<sup>&#x2212;05</sup></td>
</tr>
<tr>
<td align="left" valign="top">GP2</td>
<td align="center" valign="top">&#x2212;5.5087922</td>
<td align="center" valign="top">1.20&#x00D7;10<sup>&#x2212;06</sup></td>
</tr>
<tr>
<td align="left" valign="top">ERP27</td>
<td align="center" valign="top">&#x2212;5.4765153</td>
<td align="center" valign="top">7.39&#x00D7;10<sup>&#x2212;09</sup></td>
</tr>
<tr>
<td align="left" valign="top">CPA1</td>
<td align="center" valign="top">&#x2212;5.4417426</td>
<td align="center" valign="top">1.81&#x00D7;10<sup>&#x2212;05</sup></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn1-mmr-20-02-1343"><p>Log2FC, log2 fold change.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="tII-mmr-20-02-1343" position="float">
<label>Table II.</label>
<caption><p>GO analysis of differentially expressed genes in pancreatic cancer.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom" colspan="5">A, Upregulated genes</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">ID</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">GOBP</td>
<td align="left" valign="top">GO:0030198</td>
<td align="left" valign="top">Extracellular matrix organization</td>
<td align="center" valign="top">22</td>
<td align="center" valign="top">9.83&#x00D7;10<sup>&#x2212;21</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOBP</td>
<td align="left" valign="top">GO:0043062</td>
<td align="left" valign="top">Extracellular structure organization</td>
<td align="center" valign="top">22</td>
<td align="center" valign="top">1.05&#x00D7;10<sup>&#x2212;20</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOBP</td>
<td align="left" valign="top">GO:0030574</td>
<td align="left" valign="top">Collagen catabolic process</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">2.16&#x00D7;10<sup>&#x2212;13</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOBP</td>
<td align="left" valign="top">GO:0044243</td>
<td align="left" valign="top">Multicellular organismal catabolic process</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">6.89&#x00D7;10<sup>&#x2212;13</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOBP</td>
<td align="left" valign="top">GO:0032963</td>
<td align="left" valign="top">Collagen metabolic process</td>
<td align="center" valign="top">11</td>
<td align="center" valign="top">4.16&#x00D7;10<sup>&#x2212;12</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOMF</td>
<td align="left" valign="top">GO:0005201</td>
<td align="left" valign="top">Extracellular matrix structural constituent</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">1.09&#x00D7;10<sup>&#x2212;09</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOMF</td>
<td align="left" valign="top">GO:0005539</td>
<td align="left" valign="top">Glycosaminoglycan binding</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">2.85&#x00D7;10<sup>&#x2212;05</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOMF</td>
<td align="left" valign="top">GO:0005125</td>
<td align="left" valign="top">Cytokine activity</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">3.50&#x00D7;10<sup>&#x2212;05</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOMF</td>
<td align="left" valign="top">GO:0008009</td>
<td align="left" valign="top">Chemokine activity</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">4.62&#x00D7;10<sup>&#x2212;05</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOMF</td>
<td align="left" valign="top">GO:1901681</td>
<td align="left" valign="top">Sulfur compound binding</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">4.91&#x00D7;10<sup>&#x2212;05</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOCC</td>
<td align="left" valign="top">GO:0005578</td>
<td align="left" valign="top">Proteinaceous extracellular matrix</td>
<td align="center" valign="top">20</td>
<td align="center" valign="top">1.05&#x00D7;10<sup>&#x2212;17</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOCC</td>
<td align="left" valign="top">GO:0044420</td>
<td align="left" valign="top">Extracellular matrix component</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">4.54&#x00D7;10<sup>&#x2212;11</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOCC</td>
<td align="left" valign="top">GO:0005788</td>
<td align="left" valign="top">Endoplasmic reticulum lumen</td>
<td align="center" valign="top">13</td>
<td align="center" valign="top">1.70&#x00D7;10<sup>&#x2212;10</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOCC</td>
<td align="left" valign="top">GO:0005581</td>
<td align="left" valign="top">Collagen trimer</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">2.20&#x00D7;10<sup>&#x2212;09</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOCC</td>
<td align="left" valign="top">GO:0098644</td>
<td align="left" valign="top">Complex of collagen trimers</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">1.32&#x00D7;10<sup>&#x2212;08</sup></td>
</tr>
<tr>
<td align="center" valign="top" colspan="5"><hr/></td>
</tr>
<tr>
<td align="left" valign="top" colspan="5"><bold>B, Downregulated genes</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>ID</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">GOBP</td>
<td align="left" valign="top">GO:0007586</td>
<td align="left" valign="top">Digestion</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">7.20&#x00D7;10<sup>&#x2212;10</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOBP</td>
<td align="left" valign="top">GO:0044241</td>
<td align="left" valign="top">Lipid digestion</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">1.00&#x00D7;10<sup>&#x2212;08</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOBP</td>
<td align="left" valign="top">GO:0000096</td>
<td align="left" valign="top">Sulfur amino acid metabolic process</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">1.27&#x00D7;10<sup>&#x2212;05</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOBP</td>
<td align="left" valign="top">GO:0009235</td>
<td align="left" valign="top">Cobalamin metabolic process</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">6.62&#x00D7;10<sup>&#x2212;05</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOBP</td>
<td align="left" valign="top">GO:1901605</td>
<td align="left" valign="top">&#x03B1;-Amino acid metabolic process</td>
<td align="center" valign="top">6</td>
<td align="center" valign="top">1.76&#x00D7;10<sup>&#x2212;4</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOMF</td>
<td align="left" valign="top">GO:0008238</td>
<td align="left" valign="top">Exopeptidase activity</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">7.37&#x00D7;10<sup>&#x2212;09</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOMF</td>
<td align="left" valign="top">GO:0004252</td>
<td align="left" valign="top">Serine-type endopeptidase activity</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">2.66&#x00D7;10<sup>&#x2212;08</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOMF</td>
<td align="left" valign="top">GO:0008236</td>
<td align="left" valign="top">Serine-type peptidase activity</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">7.39&#x00D7;10<sup>&#x2212;08</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOMF</td>
<td align="left" valign="top">GO:0008235</td>
<td align="left" valign="top">Metalloexopeptidase activity</td>
<td align="center" valign="top">6</td>
<td align="center" valign="top">8.31&#x00D7;10<sup>&#x2212;08</sup></td>
</tr>
<tr>
<td align="left" valign="top">GOMF</td>
<td align="left" valign="top">GO:0017171</td>
<td align="left" valign="top">Serine hydrolase activity</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">8.76&#x00D7;10<sup>&#x2212;08</sup></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn2-mmr-20-02-1343"><p>GO, Gene Ontology; MF, molecular function; CC, cell component; BP, biological process.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="tIII-mmr-20-02-1343" position="float">
<label>Table III.</label>
<caption><p>KEGG pathway analysis of differentially expressed genes in pancreatic cancer.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom" colspan="4">A, Upregulated genes</th>
</tr>
<tr>
<th align="left" valign="bottom" colspan="4"><hr/></th>
</tr>
<tr>
<th align="left" valign="bottom">ID</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">hsa04512</td>
<td align="left" valign="top">Extracellular matrix-receptor interaction</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">2.23&#x00D7;10<sup>&#x2212;07</sup></td>
</tr>
<tr>
<td align="left" valign="top">hsa04974</td>
<td align="left" valign="top">Protein digestion and absorption</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">4.25&#x00D7;10<sup>&#x2212;07</sup></td>
</tr>
<tr>
<td align="left" valign="top">hsa04510</td>
<td align="left" valign="top">Focal adhesion</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">8.15&#x00D7;10<sup>&#x2212;05</sup></td>
</tr>
<tr>
<td align="left" valign="top">hsa04657</td>
<td align="left" valign="top">Interleukin-17 signaling pathway</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">1.32&#x00D7;10<sup>&#x2212;4</sup></td>
</tr>
<tr>
<td align="left" valign="top">hsa05146</td>
<td align="left" valign="top">Amebiasis</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">1.53&#x00D7;10<sup>&#x2212;4</sup></td>
</tr>
<tr>
<td align="center" valign="top" colspan="4"><hr/></td>
</tr>
<tr>
<td align="left" valign="top" colspan="4"><bold>B, Downregulated genes</bold></td>
</tr>
<tr>
<td align="left" valign="top" colspan="4"><hr/></td>
</tr>
<tr>
<td align="left" valign="top"><bold>ID</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="4"><hr/></td>
</tr>
<tr>
<td align="left" valign="top">hsa04972</td>
<td align="left" valign="top">Pancreatic secretion</td>
<td align="center" valign="top">13</td>
<td align="center" valign="top">3.63&#x00D7;10<sup>&#x2212;16</sup></td>
</tr>
<tr>
<td align="left" valign="top">hsa04974</td>
<td align="left" valign="top">Protein digestion and absorption</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">1.03&#x00D7;10<sup>&#x2212;08</sup></td>
</tr>
<tr>
<td align="left" valign="top">hsa04975</td>
<td align="left" valign="top">Fat digestion and absorption</td>
<td align="center" valign="top">6</td>
<td align="center" valign="top">4.10&#x00D7;10<sup>&#x2212;08</sup></td>
</tr>
<tr>
<td align="left" valign="top">hsa00561</td>
<td align="left" valign="top">Glycerolipid metabolism</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">2.27&#x00D7;10<sup>&#x2212;4</sup></td>
</tr>
<tr>
<td align="left" valign="top">hsa00260</td>
<td align="left" valign="top">Glycine, serine and threonine metabolism</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">1.01&#x00D7;10<sup>&#x2212;3</sup></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn3-mmr-20-02-1343"><p>KEGG, Kyoto Encyclopedia of Genes and Genomes.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="tIV-mmr-20-02-1343" position="float">
<label>Table IV.</label>
<caption><p>Differential expression of COL17A1 in pancreatic cancer tissues in two databases.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom">Database</th>
<th align="center" valign="bottom">Gene</th>
<th align="center" valign="bottom">Log2FC</th>
<th align="center" valign="bottom">Adjusted P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">GSE62165</td>
<td align="center" valign="top">COL17A1</td>
<td align="center" valign="top">5.0501325</td>
<td align="center" valign="top">1.8&#x00D7;10<sup>&#x2212;11</sup></td>
</tr>
<tr>
<td align="left" valign="top">GSE28735</td>
<td align="center" valign="top">COL17A1</td>
<td align="center" valign="top">1.893626</td>
<td align="center" valign="top">6.56&#x00D7;10<sup>&#x2212;13</sup></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn4-mmr-20-02-1343"><p>Log2FC, Log2 fold change; COL17A1, collagen type XVII &#x03B1;1 chain.</p></fn>
</table-wrap-foot>
</table-wrap>
</floats-group>
</article>