Identification of Significant Gene Signatures and Prognostic Biomarkers for Patients With Cervical Cancer by Integrated Bioinformatic Methods
Cervical cancer is the leading cause of death with gynecological malignancies. We aimed to explore the molecular mechanism of carcinogenesis and biomarkers for cervical cancer by integrated bioinformatic analysis. We employed RNA-sequencing details of 254 cervical squamous cell carcinomas and 3 norm...
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| creator | Li, Xiaofang Tian, Run Gao, Hugh Yan, Feng Ying, Le Yang, Yongkang Yang, Pei Gao, Yan’e |
| description | Cervical cancer is the leading cause of death with gynecological malignancies. We aimed to explore the molecular mechanism of carcinogenesis and biomarkers for cervical cancer by integrated bioinformatic analysis. We employed RNA-sequencing details of 254 cervical squamous cell carcinomas and 3 normal samples from The Cancer Genome Atlas. To explore the distinct pathways, messenger RNA expression was submitted to a Gene Set Enrichment Analysis. Kyoto Encyclopedia of Genes and Genomes and protein–protein interaction network analysis of differentially expressed genes were performed. Then, we conducted pathway enrichment analysis for modules acquired in protein–protein interaction analysis and obtained a list of pathways in every module. After intersecting the results from the 3 approaches, we evaluated the survival rates of both mutual pathways and genes in the pathway, and 5 survival-related genes were obtained. Finally, Cox hazards ratio analysis of these 5 genes was performed. DNA replication pathway (P < .001; 12 genes included) was suggested to have the strongest association with the prognosis of cervical squamous cancer. In total, 5 of the 12 genes, namely, minichromosome maintenance 2, minichromosome maintenance 4, minichromosome maintenance 5, proliferating cell nuclear antigen, and ribonuclease H2 subunit A were significantly correlated with survival. Minichromosome maintenance 5 was shown as an independent prognostic biomarker for patients with cervical cancer. This study identified a distinct pathway (DNA replication). Five genes which may be prognostic biomarkers and minichromosome maintenance 5 were identified as independent prognostic biomarkers for patients with cervical cancer. |
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We aimed to explore the molecular mechanism of carcinogenesis and biomarkers for cervical cancer by integrated bioinformatic analysis. We employed RNA-sequencing details of 254 cervical squamous cell carcinomas and 3 normal samples from The Cancer Genome Atlas. To explore the distinct pathways, messenger RNA expression was submitted to a Gene Set Enrichment Analysis. Kyoto Encyclopedia of Genes and Genomes and protein–protein interaction network analysis of differentially expressed genes were performed. Then, we conducted pathway enrichment analysis for modules acquired in protein–protein interaction analysis and obtained a list of pathways in every module. After intersecting the results from the 3 approaches, we evaluated the survival rates of both mutual pathways and genes in the pathway, and 5 survival-related genes were obtained. Finally, Cox hazards ratio analysis of these 5 genes was performed. DNA replication pathway (P < .001; 12 genes included) was suggested to have the strongest association with the prognosis of cervical squamous cancer. In total, 5 of the 12 genes, namely, minichromosome maintenance 2, minichromosome maintenance 4, minichromosome maintenance 5, proliferating cell nuclear antigen, and ribonuclease H2 subunit A were significantly correlated with survival. Minichromosome maintenance 5 was shown as an independent prognostic biomarker for patients with cervical cancer. This study identified a distinct pathway (DNA replication). Five genes which may be prognostic biomarkers and minichromosome maintenance 5 were identified as independent prognostic biomarkers for patients with cervical cancer.</description><identifier>ISSN: 1533-0346</identifier><identifier>EISSN: 1533-0338</identifier><identifier>DOI: 10.1177/1533033818767455</identifier><identifier>PMID: 29642758</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Biomarkers ; Carcinoma, Squamous Cell - genetics ; Carcinoma, Squamous Cell - mortality ; Cell Cycle Proteins - genetics ; Cervical cancer ; Computational Biology - methods ; Female ; Gene set enrichment analysis ; Genes ; Humans ; Kaplan-Meier Estimate ; Medical prognosis ; Original ; Prognosis ; Proportional Hazards Models ; Proteins ; Transcriptome - genetics ; Uterine Cervical Neoplasms - genetics ; Uterine Cervical Neoplasms - mortality</subject><ispartof>Technology in cancer research & treatment, 2018-01, Vol.17, p.1533033818767455-1533033818767455</ispartof><rights>The Author(s) 2018</rights><rights>The Author(s) 2018. This work is licensed under the Creative Commons Attribution – Non-Commercial License http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2018 2018 SAGE Publications</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c462t-473f5b4236c42b2ae52db690232a62630435d4c56e4c7ebb2a835b0062bf35273</citedby><cites>FETCH-LOGICAL-c462t-473f5b4236c42b2ae52db690232a62630435d4c56e4c7ebb2a835b0062bf35273</cites><orcidid>0000-0002-7894-7312</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5900817/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5900817/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,21946,27832,27903,27904,44924,45312,53770,53772</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29642758$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Xiaofang</creatorcontrib><creatorcontrib>Tian, Run</creatorcontrib><creatorcontrib>Gao, Hugh</creatorcontrib><creatorcontrib>Yan, Feng</creatorcontrib><creatorcontrib>Ying, Le</creatorcontrib><creatorcontrib>Yang, Yongkang</creatorcontrib><creatorcontrib>Yang, Pei</creatorcontrib><creatorcontrib>Gao, Yan’e</creatorcontrib><title>Identification of Significant Gene Signatures and Prognostic Biomarkers for Patients With Cervical Cancer by Integrated Bioinformatic Methods</title><title>Technology in cancer research & treatment</title><addtitle>Technol Cancer Res Treat</addtitle><description>Cervical cancer is the leading cause of death with gynecological malignancies. We aimed to explore the molecular mechanism of carcinogenesis and biomarkers for cervical cancer by integrated bioinformatic analysis. We employed RNA-sequencing details of 254 cervical squamous cell carcinomas and 3 normal samples from The Cancer Genome Atlas. To explore the distinct pathways, messenger RNA expression was submitted to a Gene Set Enrichment Analysis. Kyoto Encyclopedia of Genes and Genomes and protein–protein interaction network analysis of differentially expressed genes were performed. Then, we conducted pathway enrichment analysis for modules acquired in protein–protein interaction analysis and obtained a list of pathways in every module. After intersecting the results from the 3 approaches, we evaluated the survival rates of both mutual pathways and genes in the pathway, and 5 survival-related genes were obtained. Finally, Cox hazards ratio analysis of these 5 genes was performed. DNA replication pathway (P < .001; 12 genes included) was suggested to have the strongest association with the prognosis of cervical squamous cancer. In total, 5 of the 12 genes, namely, minichromosome maintenance 2, minichromosome maintenance 4, minichromosome maintenance 5, proliferating cell nuclear antigen, and ribonuclease H2 subunit A were significantly correlated with survival. Minichromosome maintenance 5 was shown as an independent prognostic biomarker for patients with cervical cancer. This study identified a distinct pathway (DNA replication). Five genes which may be prognostic biomarkers and minichromosome maintenance 5 were identified as independent prognostic biomarkers for patients with cervical cancer.</description><subject>Biomarkers</subject><subject>Carcinoma, Squamous Cell - genetics</subject><subject>Carcinoma, Squamous Cell - mortality</subject><subject>Cell Cycle Proteins - genetics</subject><subject>Cervical cancer</subject><subject>Computational Biology - methods</subject><subject>Female</subject><subject>Gene set enrichment analysis</subject><subject>Genes</subject><subject>Humans</subject><subject>Kaplan-Meier Estimate</subject><subject>Medical prognosis</subject><subject>Original</subject><subject>Prognosis</subject><subject>Proportional Hazards Models</subject><subject>Proteins</subject><subject>Transcriptome - genetics</subject><subject>Uterine Cervical Neoplasms - genetics</subject><subject>Uterine Cervical Neoplasms - mortality</subject><issn>1533-0346</issn><issn>1533-0338</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp1kU9rFTEUxUNR2lq770oCbtyM5v_M2xTqQ-uDigUVlyGTuTMvdV5Sk0yhH8LvbKavvtaCq4STc365l4PQCSVvKa3rd1RyTjhvaFOrWki5hw5nqZq1Z7u7UAfoRUpXhDClON1HB2yhBKtlc4h-rzrw2fXOmuyCx6HHX93g7wSf8Tl4uBNMniIkbHyHL2MYfEjZWfzehY2JPyEm3IeILwuj0BL-4fIaLyHeFMqIl8ZbiLi9xSufYYgmQzdHnS-hjZlBnyGvQ5deoue9GRMc359H6PvHD9-Wn6qLL-er5dlFZYViuRI172UrGFdWsJYZkKxr1YIwzoxiihPBZSesVCBsDW1xNFy2hCjW9lyymh-h0y33emo30NkydDSjvo6urHOrg3H63xfv1noIN1ouCGnoDHhzD4jh1wQp641LFsbReAhT0owwUabkpCnW10-sV2GKvqynGad80ZQmZxfZumwMKUXod8NQoueu9dOuS-TV4yV2gb_lFkO1NSQzwMOv_wX-ASI4swM</recordid><startdate>20180101</startdate><enddate>20180101</enddate><creator>Li, Xiaofang</creator><creator>Tian, Run</creator><creator>Gao, Hugh</creator><creator>Yan, Feng</creator><creator>Ying, Le</creator><creator>Yang, Yongkang</creator><creator>Yang, Pei</creator><creator>Gao, Yan’e</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><scope>AFRWT</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>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</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/0000-0002-7894-7312</orcidid></search><sort><creationdate>20180101</creationdate><title>Identification of Significant Gene Signatures and Prognostic Biomarkers for Patients With Cervical Cancer by Integrated Bioinformatic Methods</title><author>Li, Xiaofang ; Tian, Run ; Gao, Hugh ; Yan, Feng ; Ying, Le ; Yang, Yongkang ; Yang, Pei ; Gao, Yan’e</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c462t-473f5b4236c42b2ae52db690232a62630435d4c56e4c7ebb2a835b0062bf35273</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Biomarkers</topic><topic>Carcinoma, Squamous Cell - genetics</topic><topic>Carcinoma, Squamous Cell - mortality</topic><topic>Cell Cycle Proteins - genetics</topic><topic>Cervical cancer</topic><topic>Computational Biology - methods</topic><topic>Female</topic><topic>Gene set enrichment analysis</topic><topic>Genes</topic><topic>Humans</topic><topic>Kaplan-Meier Estimate</topic><topic>Medical prognosis</topic><topic>Original</topic><topic>Prognosis</topic><topic>Proportional Hazards Models</topic><topic>Proteins</topic><topic>Transcriptome - genetics</topic><topic>Uterine Cervical Neoplasms - genetics</topic><topic>Uterine Cervical Neoplasms - mortality</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Xiaofang</creatorcontrib><creatorcontrib>Tian, Run</creatorcontrib><creatorcontrib>Gao, Hugh</creatorcontrib><creatorcontrib>Yan, Feng</creatorcontrib><creatorcontrib>Ying, Le</creatorcontrib><creatorcontrib>Yang, Yongkang</creatorcontrib><creatorcontrib>Yang, Pei</creatorcontrib><creatorcontrib>Gao, Yan’e</creatorcontrib><collection>Sage Journals GOLD Open Access 2024</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>Oncogenes and Growth Factors Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</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 Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Publicly Available Content Database</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>Technology in cancer research & treatment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Xiaofang</au><au>Tian, Run</au><au>Gao, Hugh</au><au>Yan, Feng</au><au>Ying, Le</au><au>Yang, Yongkang</au><au>Yang, Pei</au><au>Gao, Yan’e</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of Significant Gene Signatures and Prognostic Biomarkers for Patients With Cervical Cancer by Integrated Bioinformatic Methods</atitle><jtitle>Technology in cancer research & treatment</jtitle><addtitle>Technol Cancer Res Treat</addtitle><date>2018-01-01</date><risdate>2018</risdate><volume>17</volume><spage>1533033818767455</spage><epage>1533033818767455</epage><pages>1533033818767455-1533033818767455</pages><issn>1533-0346</issn><eissn>1533-0338</eissn><abstract>Cervical cancer is the leading cause of death with gynecological malignancies. We aimed to explore the molecular mechanism of carcinogenesis and biomarkers for cervical cancer by integrated bioinformatic analysis. We employed RNA-sequencing details of 254 cervical squamous cell carcinomas and 3 normal samples from The Cancer Genome Atlas. To explore the distinct pathways, messenger RNA expression was submitted to a Gene Set Enrichment Analysis. Kyoto Encyclopedia of Genes and Genomes and protein–protein interaction network analysis of differentially expressed genes were performed. Then, we conducted pathway enrichment analysis for modules acquired in protein–protein interaction analysis and obtained a list of pathways in every module. After intersecting the results from the 3 approaches, we evaluated the survival rates of both mutual pathways and genes in the pathway, and 5 survival-related genes were obtained. Finally, Cox hazards ratio analysis of these 5 genes was performed. DNA replication pathway (P < .001; 12 genes included) was suggested to have the strongest association with the prognosis of cervical squamous cancer. In total, 5 of the 12 genes, namely, minichromosome maintenance 2, minichromosome maintenance 4, minichromosome maintenance 5, proliferating cell nuclear antigen, and ribonuclease H2 subunit A were significantly correlated with survival. Minichromosome maintenance 5 was shown as an independent prognostic biomarker for patients with cervical cancer. This study identified a distinct pathway (DNA replication). Five genes which may be prognostic biomarkers and minichromosome maintenance 5 were identified as independent prognostic biomarkers for patients with cervical cancer.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>29642758</pmid><doi>10.1177/1533033818767455</doi><orcidid>https://orcid.org/0000-0002-7894-7312</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Biomarkers Carcinoma, Squamous Cell - genetics Carcinoma, Squamous Cell - mortality Cell Cycle Proteins - genetics Cervical cancer Computational Biology - methods Female Gene set enrichment analysis Genes Humans Kaplan-Meier Estimate Medical prognosis Original Prognosis Proportional Hazards Models Proteins Transcriptome - genetics Uterine Cervical Neoplasms - genetics Uterine Cervical Neoplasms - mortality |
| title | Identification of Significant Gene Signatures and Prognostic Biomarkers for Patients With Cervical Cancer by Integrated Bioinformatic Methods |
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