Loading…

MCM2 and NUSAP1 Are Potential Biomarkers for the Diagnosis and Prognosis of Pancreatic Cancer

Pancreatic cancer (PC) is one of the most malignant tumors. Despite considerable progress in the treatment of PC, the prognosis of patients with PC is poor. The aim of this study was to identify potential biomarkers for the diagnosis and prognosis of PC. First, the original data of three independent...

Full description

Saved in:
Bibliographic Details
Published in:BioMed research international 2020, Vol.2020 (2020), p.1-20
Main Authors: Xie, Qiqi, Hao, Jinyong, Ma, Hanyun, Deng, Yajun, Zhao, Ruochen
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c461t-b98a3bef2229004b8d789e4c1942969de30a77a45065c731e1b6f85f294315dc3
cites cdi_FETCH-LOGICAL-c461t-b98a3bef2229004b8d789e4c1942969de30a77a45065c731e1b6f85f294315dc3
container_end_page 20
container_issue 2020
container_start_page 1
container_title BioMed research international
container_volume 2020
creator Xie, Qiqi
Hao, Jinyong
Ma, Hanyun
Deng, Yajun
Zhao, Ruochen
description Pancreatic cancer (PC) is one of the most malignant tumors. Despite considerable progress in the treatment of PC, the prognosis of patients with PC is poor. The aim of this study was to identify potential biomarkers for the diagnosis and prognosis of PC. First, the original data of three independent mRNA expression datasets were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases and screened for differentially expressed genes (DEGs) using the R software. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the DEGs were performed, and a protein-protein interaction (PPI) network was constructed to screen for hub genes. The hub genes were analyzed for genetic variations, as well as for survival, prognostic, and diagnostic value, using the cBioPortal and Gene Expression Profiling Interactive Analysis (GEPIA) databases and the pROC package. After screening for potential biomarkers, the mRNA and protein levels of the biomarkers were verified at the tissue and cellular levels using the Cancer Cell Line Encyclopedia, GEPIA, and the Human Protein Atlas. As a result, a total of 248 DEGs were identified. The GO terms enriched in DEGs were related to the separation of mitotic sister chromatids and the binding of the spindle to the extracellular matrix. The enriched pathways were associated with focal adhesion, ECM-receptor interaction, and phosphatidylinositol 3-kinase (PI3K)/AKT signaling. The top 20 genes were selected from the PPI network as hub genes, and based on the analysis of multiple databases, MCM2 and NUSAP1 were identified as potential biomarkers for the diagnosis and prognosis of PC. In conclusion, our results show that MCM2 and NUSAP1 can be used as potential biomarkers for the diagnosis and prognosis of PC. The study also provides new insights into the underlying molecular mechanisms of PC.
doi_str_mv 10.1155/2020/8604340
format article
fullrecord <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7206867</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A629053531</galeid><sourcerecordid>A629053531</sourcerecordid><originalsourceid>FETCH-LOGICAL-c461t-b98a3bef2229004b8d789e4c1942969de30a77a45065c731e1b6f85f294315dc3</originalsourceid><addsrcrecordid>eNqNkUtvEzEUhS0EolXpjjWyxAYJQv32zAYphKfUQiToElkez3XiMrFbewLi3-MhIQVWeONr-fO59_gg9JCS55RKecYII2eNIoILcgcdM07FTFFB7x5qzo_QaSlXpK6GKtKq--iIM8EI1_IYfblYXDBsY48_XH6aLymeZ8DLNEIcgx3wy5A2Nn-FXLBPGY9rwK-CXcVUQvn1apnT_pQ8XtroMtgxOLyoJeQH6J63Q4HT_X6CLt-8_rx4Nzv_-Pb9Yn4-c0LRcda1jeUdeMZYS4joml43LQhHW8Fa1fbAidXaCkmUdJpToJ3yjfSsFZzK3vET9GKne73tNtC7On22g7nOoU7_wyQbzN83MazNKn0zmhHVKF0FnuwFcrrZQhnNJhQHw2AjpG0xTNQvbogQsqKP_0Gv0jbHam-iCNOCa3pLrewAJkSfal83iZq5qi4ll3yinu0ol1MpGfxhZErMFLCZAjb7gCv-6E-bB_h3nBV4ugPWIfb2e_hPOagMeHtL0yomCf8JcwOzPw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2400274371</pqid></control><display><type>article</type><title>MCM2 and NUSAP1 Are Potential Biomarkers for the Diagnosis and Prognosis of Pancreatic Cancer</title><source>Publicly Available Content (ProQuest)</source><source>Wiley Open Access</source><creator>Xie, Qiqi ; Hao, Jinyong ; Ma, Hanyun ; Deng, Yajun ; Zhao, Ruochen</creator><contributor>Dasgupta, Bhaskar ; Bhaskar Dasgupta</contributor><creatorcontrib>Xie, Qiqi ; Hao, Jinyong ; Ma, Hanyun ; Deng, Yajun ; Zhao, Ruochen ; Dasgupta, Bhaskar ; Bhaskar Dasgupta</creatorcontrib><description>Pancreatic cancer (PC) is one of the most malignant tumors. Despite considerable progress in the treatment of PC, the prognosis of patients with PC is poor. The aim of this study was to identify potential biomarkers for the diagnosis and prognosis of PC. First, the original data of three independent mRNA expression datasets were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases and screened for differentially expressed genes (DEGs) using the R software. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the DEGs were performed, and a protein-protein interaction (PPI) network was constructed to screen for hub genes. The hub genes were analyzed for genetic variations, as well as for survival, prognostic, and diagnostic value, using the cBioPortal and Gene Expression Profiling Interactive Analysis (GEPIA) databases and the pROC package. After screening for potential biomarkers, the mRNA and protein levels of the biomarkers were verified at the tissue and cellular levels using the Cancer Cell Line Encyclopedia, GEPIA, and the Human Protein Atlas. As a result, a total of 248 DEGs were identified. The GO terms enriched in DEGs were related to the separation of mitotic sister chromatids and the binding of the spindle to the extracellular matrix. The enriched pathways were associated with focal adhesion, ECM-receptor interaction, and phosphatidylinositol 3-kinase (PI3K)/AKT signaling. The top 20 genes were selected from the PPI network as hub genes, and based on the analysis of multiple databases, MCM2 and NUSAP1 were identified as potential biomarkers for the diagnosis and prognosis of PC. In conclusion, our results show that MCM2 and NUSAP1 can be used as potential biomarkers for the diagnosis and prognosis of PC. The study also provides new insights into the underlying molecular mechanisms of PC.</description><identifier>ISSN: 2314-6133</identifier><identifier>EISSN: 2314-6141</identifier><identifier>DOI: 10.1155/2020/8604340</identifier><identifier>PMID: 32420375</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>1-Phosphatidylinositol 3-kinase ; AKT protein ; Biological markers ; Biomarkers ; Biomarkers, Tumor - genetics ; Biomarkers, Tumor - metabolism ; Cancer ; Chromatids ; Databases, Nucleic Acid ; Datasets ; Diagnosis ; Diagnostic systems ; Disease-Free Survival ; Encyclopedias ; Enrichment ; Extracellular matrix ; Female ; Gene expression ; Genes ; Genetic aspects ; Genetic diversity ; Genomes ; Genomics ; Humans ; Kinases ; Male ; Medical prognosis ; Microtubule-Associated Proteins - genetics ; Microtubule-Associated Proteins - metabolism ; Minichromosome Maintenance Complex Component 2 - genetics ; Minichromosome Maintenance Complex Component 2 - metabolism ; Molecular modelling ; Neoplasm Proteins - genetics ; Neoplasm Proteins - metabolism ; Pancreatic cancer ; Pancreatic Neoplasms - diagnosis ; Pancreatic Neoplasms - genetics ; Pancreatic Neoplasms - metabolism ; Pancreatic Neoplasms - mortality ; Pathogenesis ; Prognosis ; Protein interaction ; Protein-protein interactions ; Proteins ; RNA ; Sister chromatids ; Software ; Survival Rate ; Tumors</subject><ispartof>BioMed research international, 2020, Vol.2020 (2020), p.1-20</ispartof><rights>Copyright © 2020 Yajun Deng et al.</rights><rights>COPYRIGHT 2020 John Wiley &amp; Sons, Inc.</rights><rights>Copyright © 2020 Yajun Deng et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2020 Yajun Deng et al. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c461t-b98a3bef2229004b8d789e4c1942969de30a77a45065c731e1b6f85f294315dc3</citedby><cites>FETCH-LOGICAL-c461t-b98a3bef2229004b8d789e4c1942969de30a77a45065c731e1b6f85f294315dc3</cites><orcidid>0000-0002-8689-7634 ; 0000-0003-4099-5287 ; 0000-0003-0953-6525 ; 0000-0003-2191-7910</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2400274371/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2400274371?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,4010,25731,27900,27901,27902,36989,36990,44566,74869</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32420375$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Dasgupta, Bhaskar</contributor><contributor>Bhaskar Dasgupta</contributor><creatorcontrib>Xie, Qiqi</creatorcontrib><creatorcontrib>Hao, Jinyong</creatorcontrib><creatorcontrib>Ma, Hanyun</creatorcontrib><creatorcontrib>Deng, Yajun</creatorcontrib><creatorcontrib>Zhao, Ruochen</creatorcontrib><title>MCM2 and NUSAP1 Are Potential Biomarkers for the Diagnosis and Prognosis of Pancreatic Cancer</title><title>BioMed research international</title><addtitle>Biomed Res Int</addtitle><description>Pancreatic cancer (PC) is one of the most malignant tumors. Despite considerable progress in the treatment of PC, the prognosis of patients with PC is poor. The aim of this study was to identify potential biomarkers for the diagnosis and prognosis of PC. First, the original data of three independent mRNA expression datasets were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases and screened for differentially expressed genes (DEGs) using the R software. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the DEGs were performed, and a protein-protein interaction (PPI) network was constructed to screen for hub genes. The hub genes were analyzed for genetic variations, as well as for survival, prognostic, and diagnostic value, using the cBioPortal and Gene Expression Profiling Interactive Analysis (GEPIA) databases and the pROC package. After screening for potential biomarkers, the mRNA and protein levels of the biomarkers were verified at the tissue and cellular levels using the Cancer Cell Line Encyclopedia, GEPIA, and the Human Protein Atlas. As a result, a total of 248 DEGs were identified. The GO terms enriched in DEGs were related to the separation of mitotic sister chromatids and the binding of the spindle to the extracellular matrix. The enriched pathways were associated with focal adhesion, ECM-receptor interaction, and phosphatidylinositol 3-kinase (PI3K)/AKT signaling. The top 20 genes were selected from the PPI network as hub genes, and based on the analysis of multiple databases, MCM2 and NUSAP1 were identified as potential biomarkers for the diagnosis and prognosis of PC. In conclusion, our results show that MCM2 and NUSAP1 can be used as potential biomarkers for the diagnosis and prognosis of PC. The study also provides new insights into the underlying molecular mechanisms of PC.</description><subject>1-Phosphatidylinositol 3-kinase</subject><subject>AKT protein</subject><subject>Biological markers</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biomarkers, Tumor - metabolism</subject><subject>Cancer</subject><subject>Chromatids</subject><subject>Databases, Nucleic Acid</subject><subject>Datasets</subject><subject>Diagnosis</subject><subject>Diagnostic systems</subject><subject>Disease-Free Survival</subject><subject>Encyclopedias</subject><subject>Enrichment</subject><subject>Extracellular matrix</subject><subject>Female</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genetic diversity</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Humans</subject><subject>Kinases</subject><subject>Male</subject><subject>Medical prognosis</subject><subject>Microtubule-Associated Proteins - genetics</subject><subject>Microtubule-Associated Proteins - metabolism</subject><subject>Minichromosome Maintenance Complex Component 2 - genetics</subject><subject>Minichromosome Maintenance Complex Component 2 - metabolism</subject><subject>Molecular modelling</subject><subject>Neoplasm Proteins - genetics</subject><subject>Neoplasm Proteins - metabolism</subject><subject>Pancreatic cancer</subject><subject>Pancreatic Neoplasms - diagnosis</subject><subject>Pancreatic Neoplasms - genetics</subject><subject>Pancreatic Neoplasms - metabolism</subject><subject>Pancreatic Neoplasms - mortality</subject><subject>Pathogenesis</subject><subject>Prognosis</subject><subject>Protein interaction</subject><subject>Protein-protein interactions</subject><subject>Proteins</subject><subject>RNA</subject><subject>Sister chromatids</subject><subject>Software</subject><subject>Survival Rate</subject><subject>Tumors</subject><issn>2314-6133</issn><issn>2314-6141</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNqNkUtvEzEUhS0EolXpjjWyxAYJQv32zAYphKfUQiToElkez3XiMrFbewLi3-MhIQVWeONr-fO59_gg9JCS55RKecYII2eNIoILcgcdM07FTFFB7x5qzo_QaSlXpK6GKtKq--iIM8EI1_IYfblYXDBsY48_XH6aLymeZ8DLNEIcgx3wy5A2Nn-FXLBPGY9rwK-CXcVUQvn1apnT_pQ8XtroMtgxOLyoJeQH6J63Q4HT_X6CLt-8_rx4Nzv_-Pb9Yn4-c0LRcda1jeUdeMZYS4joml43LQhHW8Fa1fbAidXaCkmUdJpToJ3yjfSsFZzK3vET9GKne73tNtC7On22g7nOoU7_wyQbzN83MazNKn0zmhHVKF0FnuwFcrrZQhnNJhQHw2AjpG0xTNQvbogQsqKP_0Gv0jbHam-iCNOCa3pLrewAJkSfal83iZq5qi4ll3yinu0ol1MpGfxhZErMFLCZAjb7gCv-6E-bB_h3nBV4ugPWIfb2e_hPOagMeHtL0yomCf8JcwOzPw</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Xie, Qiqi</creator><creator>Hao, Jinyong</creator><creator>Ma, Hanyun</creator><creator>Deng, Yajun</creator><creator>Zhao, Ruochen</creator><general>Hindawi Publishing Corporation</general><general>Hindawi</general><general>John Wiley &amp; Sons, Inc</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7QO</scope><scope>7T7</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-8689-7634</orcidid><orcidid>https://orcid.org/0000-0003-4099-5287</orcidid><orcidid>https://orcid.org/0000-0003-0953-6525</orcidid><orcidid>https://orcid.org/0000-0003-2191-7910</orcidid></search><sort><creationdate>2020</creationdate><title>MCM2 and NUSAP1 Are Potential Biomarkers for the Diagnosis and Prognosis of Pancreatic Cancer</title><author>Xie, Qiqi ; Hao, Jinyong ; Ma, Hanyun ; Deng, Yajun ; Zhao, Ruochen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c461t-b98a3bef2229004b8d789e4c1942969de30a77a45065c731e1b6f85f294315dc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>1-Phosphatidylinositol 3-kinase</topic><topic>AKT protein</topic><topic>Biological markers</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Biomarkers, Tumor - metabolism</topic><topic>Cancer</topic><topic>Chromatids</topic><topic>Databases, Nucleic Acid</topic><topic>Datasets</topic><topic>Diagnosis</topic><topic>Diagnostic systems</topic><topic>Disease-Free Survival</topic><topic>Encyclopedias</topic><topic>Enrichment</topic><topic>Extracellular matrix</topic><topic>Female</topic><topic>Gene expression</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genetic diversity</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Humans</topic><topic>Kinases</topic><topic>Male</topic><topic>Medical prognosis</topic><topic>Microtubule-Associated Proteins - genetics</topic><topic>Microtubule-Associated Proteins - metabolism</topic><topic>Minichromosome Maintenance Complex Component 2 - genetics</topic><topic>Minichromosome Maintenance Complex Component 2 - metabolism</topic><topic>Molecular modelling</topic><topic>Neoplasm Proteins - genetics</topic><topic>Neoplasm Proteins - metabolism</topic><topic>Pancreatic cancer</topic><topic>Pancreatic Neoplasms - diagnosis</topic><topic>Pancreatic Neoplasms - genetics</topic><topic>Pancreatic Neoplasms - metabolism</topic><topic>Pancreatic Neoplasms - mortality</topic><topic>Pathogenesis</topic><topic>Prognosis</topic><topic>Protein interaction</topic><topic>Protein-protein interactions</topic><topic>Proteins</topic><topic>RNA</topic><topic>Sister chromatids</topic><topic>Software</topic><topic>Survival Rate</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xie, Qiqi</creatorcontrib><creatorcontrib>Hao, Jinyong</creatorcontrib><creatorcontrib>Ma, Hanyun</creatorcontrib><creatorcontrib>Deng, Yajun</creatorcontrib><creatorcontrib>Zhao, Ruochen</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>ProQuest Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Database‎ (1962 - current)</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Middle East &amp; Africa Database</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Biological Sciences</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>ProQuest advanced technologies &amp; aerospace journals</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BioMed research international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xie, Qiqi</au><au>Hao, Jinyong</au><au>Ma, Hanyun</au><au>Deng, Yajun</au><au>Zhao, Ruochen</au><au>Dasgupta, Bhaskar</au><au>Bhaskar Dasgupta</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MCM2 and NUSAP1 Are Potential Biomarkers for the Diagnosis and Prognosis of Pancreatic Cancer</atitle><jtitle>BioMed research international</jtitle><addtitle>Biomed Res Int</addtitle><date>2020</date><risdate>2020</risdate><volume>2020</volume><issue>2020</issue><spage>1</spage><epage>20</epage><pages>1-20</pages><issn>2314-6133</issn><eissn>2314-6141</eissn><abstract>Pancreatic cancer (PC) is one of the most malignant tumors. Despite considerable progress in the treatment of PC, the prognosis of patients with PC is poor. The aim of this study was to identify potential biomarkers for the diagnosis and prognosis of PC. First, the original data of three independent mRNA expression datasets were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases and screened for differentially expressed genes (DEGs) using the R software. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the DEGs were performed, and a protein-protein interaction (PPI) network was constructed to screen for hub genes. The hub genes were analyzed for genetic variations, as well as for survival, prognostic, and diagnostic value, using the cBioPortal and Gene Expression Profiling Interactive Analysis (GEPIA) databases and the pROC package. After screening for potential biomarkers, the mRNA and protein levels of the biomarkers were verified at the tissue and cellular levels using the Cancer Cell Line Encyclopedia, GEPIA, and the Human Protein Atlas. As a result, a total of 248 DEGs were identified. The GO terms enriched in DEGs were related to the separation of mitotic sister chromatids and the binding of the spindle to the extracellular matrix. The enriched pathways were associated with focal adhesion, ECM-receptor interaction, and phosphatidylinositol 3-kinase (PI3K)/AKT signaling. The top 20 genes were selected from the PPI network as hub genes, and based on the analysis of multiple databases, MCM2 and NUSAP1 were identified as potential biomarkers for the diagnosis and prognosis of PC. In conclusion, our results show that MCM2 and NUSAP1 can be used as potential biomarkers for the diagnosis and prognosis of PC. The study also provides new insights into the underlying molecular mechanisms of PC.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><pmid>32420375</pmid><doi>10.1155/2020/8604340</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0002-8689-7634</orcidid><orcidid>https://orcid.org/0000-0003-4099-5287</orcidid><orcidid>https://orcid.org/0000-0003-0953-6525</orcidid><orcidid>https://orcid.org/0000-0003-2191-7910</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2314-6133
ispartof BioMed research international, 2020, Vol.2020 (2020), p.1-20
issn 2314-6133
2314-6141
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7206867
source Publicly Available Content (ProQuest); Wiley Open Access
subjects 1-Phosphatidylinositol 3-kinase
AKT protein
Biological markers
Biomarkers
Biomarkers, Tumor - genetics
Biomarkers, Tumor - metabolism
Cancer
Chromatids
Databases, Nucleic Acid
Datasets
Diagnosis
Diagnostic systems
Disease-Free Survival
Encyclopedias
Enrichment
Extracellular matrix
Female
Gene expression
Genes
Genetic aspects
Genetic diversity
Genomes
Genomics
Humans
Kinases
Male
Medical prognosis
Microtubule-Associated Proteins - genetics
Microtubule-Associated Proteins - metabolism
Minichromosome Maintenance Complex Component 2 - genetics
Minichromosome Maintenance Complex Component 2 - metabolism
Molecular modelling
Neoplasm Proteins - genetics
Neoplasm Proteins - metabolism
Pancreatic cancer
Pancreatic Neoplasms - diagnosis
Pancreatic Neoplasms - genetics
Pancreatic Neoplasms - metabolism
Pancreatic Neoplasms - mortality
Pathogenesis
Prognosis
Protein interaction
Protein-protein interactions
Proteins
RNA
Sister chromatids
Software
Survival Rate
Tumors
title MCM2 and NUSAP1 Are Potential Biomarkers for the Diagnosis and Prognosis of Pancreatic Cancer
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-29T15%3A46%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=MCM2%20and%20NUSAP1%20Are%20Potential%20Biomarkers%20for%20the%20Diagnosis%20and%20Prognosis%20of%20Pancreatic%20Cancer&rft.jtitle=BioMed%20research%20international&rft.au=Xie,%20Qiqi&rft.date=2020&rft.volume=2020&rft.issue=2020&rft.spage=1&rft.epage=20&rft.pages=1-20&rft.issn=2314-6133&rft.eissn=2314-6141&rft_id=info:doi/10.1155/2020/8604340&rft_dat=%3Cgale_pubme%3EA629053531%3C/gale_pubme%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c461t-b98a3bef2229004b8d789e4c1942969de30a77a45065c731e1b6f85f294315dc3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2400274371&rft_id=info:pmid/32420375&rft_galeid=A629053531&rfr_iscdi=true