MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal Cancer
Background. Colorectal cancer (CRC) is the third most common cancer in the world, and most of them are adenocarcinomas. CRC could be classified as colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) according to the original tumorigenesis position. Increasing evidences indicated that microR...
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| description | Background. Colorectal cancer (CRC) is the third most common cancer in the world, and most of them are adenocarcinomas. CRC could be classified as colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) according to the original tumorigenesis position. Increasing evidences indicated that microRNAs (miRNAs) play an important role in the occurrence of multiple tumors. Methods. In this study, we firstly downloaded miRNA (COAD, 8 controls vs. 455 tumors; READ, 3 controls vs. 161 tumors) and mRNA (COAD, 41 controls vs. 478 tumors; READ, 10 controls vs. 166 tumors) data from The Cancer Genome Atlas (TCGA) database and then used DESeq2, RegParallel, miRDB, TargetScanHuman 7.2, DAVID 6.8, STRING, and Cytoscape software to identify the potential prognosis biomarkers. Results. We identified 175 differential expression miRNAs (DEMs) and 3747 differential expression genes (DEGs) in COAD and 184 DEMs and 3928 DEGs in READ. And then, we obtained 21 (13 in COAD and 8 in READ) DEMs associated with the survival rates, which correlated with 440 (217 in COAD and 223 in READ) overlapping DEGs. Through survival analysis for those overlapping DEGs, we found 11 (8 in COAD and 3 in READ) overlapping DGEs associated with survival rates of patients, which were correlated with 9 (7 in COAD and 2 in READ) DEMs significantly. Conclusion. In this study, we found several candidate prognostic biomarkers which have been identified in various cancers and also found several new prognosis biomarkers of COAD and READ. In conclusion, this analysis based on theoretical knowledge and clinical outcomes we have done needs further confirmation by more researches. |
| doi_str_mv | 10.1155/2020/7905380 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7501550</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2445423100</sourcerecordid><originalsourceid>FETCH-LOGICAL-c537t-62d67e6b6a4bf981d807d930925c825b0919f2c1df179e627198c521d904123a3</originalsourceid><addsrcrecordid>eNqNkc9PFDEcxRsjEQLcPJsmXkxwpL-nvZjAKkICQhDPTbfTmSnOtks7o_G_p5tdF_RkL98m309evu89AF5j9AFjzo8JIui4VohTiV6APUIxqwRm-OX2T-kuOMz5HpUnsUBKvAK7lCjBEKN7QF95m-Lt15Pq1g1mdA28SbELMfsMT31cmPTDpQzbFBfw3Hd9ddenOHX9chrhN_cwuWB96OAnMxoYWziLQ0zOjmaAMxOsSwdgpzVDdoebuQ--n32-m51Xl9dfLmYnl5XltB4rQRpROzEXhs1bJXEjUd0oihThVhI-RwqrlljctLhWTpAaK2k5wY1CDBNq6D74uNZdTvOFa6wLYzKDXiZfLPzW0Xj99yb4Xnfxp645KkGiIvBuI5BisZVHvfDZumEwwcUpa8IYZyVTtELf_oPexymFYm9FMSIRF7JQ79dUyTfn5NrtMRjpVXl6VZ7elFfwN88NbOE_VRXgaA30PjTml_9POVcY15onGtOaYEkfAdQ_qfg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2444280568</pqid></control><display><type>article</type><title>MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal Cancer</title><source>MEDLINE</source><source>PubMed Central Open Access</source><source>Wiley-Blackwell Open Access Titles</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><creator>Liu, Yuan-Wu ; Zhu, Ning ; Zhang, Ti ; Yao, Zhi-Yong ; Xing, Xiaoliang ; Peng, Jing</creator><contributor>Liu, Hongliang ; Hongliang Liu</contributor><creatorcontrib>Liu, Yuan-Wu ; Zhu, Ning ; Zhang, Ti ; Yao, Zhi-Yong ; Xing, Xiaoliang ; Peng, Jing ; Liu, Hongliang ; Hongliang Liu</creatorcontrib><description>Background. Colorectal cancer (CRC) is the third most common cancer in the world, and most of them are adenocarcinomas. CRC could be classified as colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) according to the original tumorigenesis position. Increasing evidences indicated that microRNAs (miRNAs) play an important role in the occurrence of multiple tumors. Methods. In this study, we firstly downloaded miRNA (COAD, 8 controls vs. 455 tumors; READ, 3 controls vs. 161 tumors) and mRNA (COAD, 41 controls vs. 478 tumors; READ, 10 controls vs. 166 tumors) data from The Cancer Genome Atlas (TCGA) database and then used DESeq2, RegParallel, miRDB, TargetScanHuman 7.2, DAVID 6.8, STRING, and Cytoscape software to identify the potential prognosis biomarkers. Results. We identified 175 differential expression miRNAs (DEMs) and 3747 differential expression genes (DEGs) in COAD and 184 DEMs and 3928 DEGs in READ. And then, we obtained 21 (13 in COAD and 8 in READ) DEMs associated with the survival rates, which correlated with 440 (217 in COAD and 223 in READ) overlapping DEGs. Through survival analysis for those overlapping DEGs, we found 11 (8 in COAD and 3 in READ) overlapping DGEs associated with survival rates of patients, which were correlated with 9 (7 in COAD and 2 in READ) DEMs significantly. Conclusion. In this study, we found several candidate prognostic biomarkers which have been identified in various cancers and also found several new prognosis biomarkers of COAD and READ. In conclusion, this analysis based on theoretical knowledge and clinical outcomes we have done needs further confirmation by more researches.</description><identifier>ISSN: 2314-6133</identifier><identifier>EISSN: 2314-6141</identifier><identifier>DOI: 10.1155/2020/7905380</identifier><identifier>PMID: 32964043</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Adenocarcinoma ; Adenocarcinoma - genetics ; Adenocarcinoma - pathology ; Biomarkers ; Biomarkers, Tumor - genetics ; Biomedical research ; Cancer ; Cancer therapies ; Colon ; Colorectal cancer ; Colorectal carcinoma ; Colorectal Neoplasms - genetics ; Colorectal Neoplasms - pathology ; Correlation analysis ; DNA methylation ; Gene expression ; Gene Expression Profiling - methods ; Gene Expression Regulation, Neoplastic - genetics ; Gene Regulatory Networks - genetics ; Genomes ; High-Throughput Nucleotide Sequencing - methods ; Humans ; Medical prognosis ; Metastasis ; MicroRNAs ; MicroRNAs - genetics ; miRNA ; mRNA ; Next-generation sequencing ; Pathogenesis ; Prognosis ; Rectum ; Regression analysis ; RNA, Messenger - genetics ; Software ; Survival ; Survival Analysis ; Survival Rate ; Tumorigenesis ; Tumors</subject><ispartof>BioMed research international, 2020, Vol.2020 (2020), p.1-12</ispartof><rights>Copyright © 2020 Xiao-Liang Xing et al.</rights><rights>Copyright © 2020 Xiao-Liang Xing 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. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2020 Xiao-Liang Xing et al. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c537t-62d67e6b6a4bf981d807d930925c825b0919f2c1df179e627198c521d904123a3</citedby><cites>FETCH-LOGICAL-c537t-62d67e6b6a4bf981d807d930925c825b0919f2c1df179e627198c521d904123a3</cites><orcidid>0000-0002-5553-5171 ; 0000-0002-7804-0622 ; 0000-0001-5132-6252</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/PMC7501550/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7501550/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,4022,27922,27923,27924,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32964043$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Liu, Hongliang</contributor><contributor>Hongliang Liu</contributor><creatorcontrib>Liu, Yuan-Wu</creatorcontrib><creatorcontrib>Zhu, Ning</creatorcontrib><creatorcontrib>Zhang, Ti</creatorcontrib><creatorcontrib>Yao, Zhi-Yong</creatorcontrib><creatorcontrib>Xing, Xiaoliang</creatorcontrib><creatorcontrib>Peng, Jing</creatorcontrib><title>MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal Cancer</title><title>BioMed research international</title><addtitle>Biomed Res Int</addtitle><description>Background. Colorectal cancer (CRC) is the third most common cancer in the world, and most of them are adenocarcinomas. CRC could be classified as colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) according to the original tumorigenesis position. Increasing evidences indicated that microRNAs (miRNAs) play an important role in the occurrence of multiple tumors. Methods. In this study, we firstly downloaded miRNA (COAD, 8 controls vs. 455 tumors; READ, 3 controls vs. 161 tumors) and mRNA (COAD, 41 controls vs. 478 tumors; READ, 10 controls vs. 166 tumors) data from The Cancer Genome Atlas (TCGA) database and then used DESeq2, RegParallel, miRDB, TargetScanHuman 7.2, DAVID 6.8, STRING, and Cytoscape software to identify the potential prognosis biomarkers. Results. We identified 175 differential expression miRNAs (DEMs) and 3747 differential expression genes (DEGs) in COAD and 184 DEMs and 3928 DEGs in READ. And then, we obtained 21 (13 in COAD and 8 in READ) DEMs associated with the survival rates, which correlated with 440 (217 in COAD and 223 in READ) overlapping DEGs. Through survival analysis for those overlapping DEGs, we found 11 (8 in COAD and 3 in READ) overlapping DGEs associated with survival rates of patients, which were correlated with 9 (7 in COAD and 2 in READ) DEMs significantly. Conclusion. In this study, we found several candidate prognostic biomarkers which have been identified in various cancers and also found several new prognosis biomarkers of COAD and READ. In conclusion, this analysis based on theoretical knowledge and clinical outcomes we have done needs further confirmation by more researches.</description><subject>Adenocarcinoma</subject><subject>Adenocarcinoma - genetics</subject><subject>Adenocarcinoma - pathology</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biomedical research</subject><subject>Cancer</subject><subject>Cancer therapies</subject><subject>Colon</subject><subject>Colorectal cancer</subject><subject>Colorectal carcinoma</subject><subject>Colorectal Neoplasms - genetics</subject><subject>Colorectal Neoplasms - pathology</subject><subject>Correlation analysis</subject><subject>DNA methylation</subject><subject>Gene expression</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Expression Regulation, Neoplastic - genetics</subject><subject>Gene Regulatory Networks - genetics</subject><subject>Genomes</subject><subject>High-Throughput Nucleotide Sequencing - methods</subject><subject>Humans</subject><subject>Medical prognosis</subject><subject>Metastasis</subject><subject>MicroRNAs</subject><subject>MicroRNAs - genetics</subject><subject>miRNA</subject><subject>mRNA</subject><subject>Next-generation sequencing</subject><subject>Pathogenesis</subject><subject>Prognosis</subject><subject>Rectum</subject><subject>Regression analysis</subject><subject>RNA, Messenger - genetics</subject><subject>Software</subject><subject>Survival</subject><subject>Survival Analysis</subject><subject>Survival Rate</subject><subject>Tumorigenesis</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>RHX</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNkc9PFDEcxRsjEQLcPJsmXkxwpL-nvZjAKkICQhDPTbfTmSnOtks7o_G_p5tdF_RkL98m309evu89AF5j9AFjzo8JIui4VohTiV6APUIxqwRm-OX2T-kuOMz5HpUnsUBKvAK7lCjBEKN7QF95m-Lt15Pq1g1mdA28SbELMfsMT31cmPTDpQzbFBfw3Hd9ddenOHX9chrhN_cwuWB96OAnMxoYWziLQ0zOjmaAMxOsSwdgpzVDdoebuQ--n32-m51Xl9dfLmYnl5XltB4rQRpROzEXhs1bJXEjUd0oihThVhI-RwqrlljctLhWTpAaK2k5wY1CDBNq6D74uNZdTvOFa6wLYzKDXiZfLPzW0Xj99yb4Xnfxp645KkGiIvBuI5BisZVHvfDZumEwwcUpa8IYZyVTtELf_oPexymFYm9FMSIRF7JQ79dUyTfn5NrtMRjpVXl6VZ7elFfwN88NbOE_VRXgaA30PjTml_9POVcY15onGtOaYEkfAdQ_qfg</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Liu, Yuan-Wu</creator><creator>Zhu, Ning</creator><creator>Zhang, Ti</creator><creator>Yao, Zhi-Yong</creator><creator>Xing, Xiaoliang</creator><creator>Peng, Jing</creator><general>Hindawi Publishing Corporation</general><general>Hindawi</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/0000-0002-5553-5171</orcidid><orcidid>https://orcid.org/0000-0002-7804-0622</orcidid><orcidid>https://orcid.org/0000-0001-5132-6252</orcidid></search><sort><creationdate>2020</creationdate><title>MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal Cancer</title><author>Liu, Yuan-Wu ; Zhu, Ning ; Zhang, Ti ; Yao, Zhi-Yong ; Xing, Xiaoliang ; Peng, Jing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c537t-62d67e6b6a4bf981d807d930925c825b0919f2c1df179e627198c521d904123a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adenocarcinoma</topic><topic>Adenocarcinoma - genetics</topic><topic>Adenocarcinoma - pathology</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Biomedical research</topic><topic>Cancer</topic><topic>Cancer therapies</topic><topic>Colon</topic><topic>Colorectal cancer</topic><topic>Colorectal carcinoma</topic><topic>Colorectal Neoplasms - genetics</topic><topic>Colorectal Neoplasms - pathology</topic><topic>Correlation analysis</topic><topic>DNA methylation</topic><topic>Gene expression</topic><topic>Gene Expression Profiling - methods</topic><topic>Gene Expression Regulation, Neoplastic - genetics</topic><topic>Gene Regulatory Networks - genetics</topic><topic>Genomes</topic><topic>High-Throughput Nucleotide Sequencing - methods</topic><topic>Humans</topic><topic>Medical prognosis</topic><topic>Metastasis</topic><topic>MicroRNAs</topic><topic>MicroRNAs - genetics</topic><topic>miRNA</topic><topic>mRNA</topic><topic>Next-generation sequencing</topic><topic>Pathogenesis</topic><topic>Prognosis</topic><topic>Rectum</topic><topic>Regression analysis</topic><topic>RNA, Messenger - genetics</topic><topic>Software</topic><topic>Survival</topic><topic>Survival Analysis</topic><topic>Survival Rate</topic><topic>Tumorigenesis</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Yuan-Wu</creatorcontrib><creatorcontrib>Zhu, Ning</creatorcontrib><creatorcontrib>Zhang, Ti</creatorcontrib><creatorcontrib>Yao, Zhi-Yong</creatorcontrib><creatorcontrib>Xing, Xiaoliang</creatorcontrib><creatorcontrib>Peng, Jing</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>Health & 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 Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central Korea</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</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</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>BioMed research international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Yuan-Wu</au><au>Zhu, Ning</au><au>Zhang, Ti</au><au>Yao, Zhi-Yong</au><au>Xing, Xiaoliang</au><au>Peng, Jing</au><au>Liu, Hongliang</au><au>Hongliang Liu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal 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>12</epage><pages>1-12</pages><issn>2314-6133</issn><eissn>2314-6141</eissn><abstract>Background. Colorectal cancer (CRC) is the third most common cancer in the world, and most of them are adenocarcinomas. CRC could be classified as colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) according to the original tumorigenesis position. Increasing evidences indicated that microRNAs (miRNAs) play an important role in the occurrence of multiple tumors. Methods. In this study, we firstly downloaded miRNA (COAD, 8 controls vs. 455 tumors; READ, 3 controls vs. 161 tumors) and mRNA (COAD, 41 controls vs. 478 tumors; READ, 10 controls vs. 166 tumors) data from The Cancer Genome Atlas (TCGA) database and then used DESeq2, RegParallel, miRDB, TargetScanHuman 7.2, DAVID 6.8, STRING, and Cytoscape software to identify the potential prognosis biomarkers. Results. We identified 175 differential expression miRNAs (DEMs) and 3747 differential expression genes (DEGs) in COAD and 184 DEMs and 3928 DEGs in READ. And then, we obtained 21 (13 in COAD and 8 in READ) DEMs associated with the survival rates, which correlated with 440 (217 in COAD and 223 in READ) overlapping DEGs. Through survival analysis for those overlapping DEGs, we found 11 (8 in COAD and 3 in READ) overlapping DGEs associated with survival rates of patients, which were correlated with 9 (7 in COAD and 2 in READ) DEMs significantly. Conclusion. In this study, we found several candidate prognostic biomarkers which have been identified in various cancers and also found several new prognosis biomarkers of COAD and READ. In conclusion, this analysis based on theoretical knowledge and clinical outcomes we have done needs further confirmation by more researches.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><pmid>32964043</pmid><doi>10.1155/2020/7905380</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-5553-5171</orcidid><orcidid>https://orcid.org/0000-0002-7804-0622</orcidid><orcidid>https://orcid.org/0000-0001-5132-6252</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adenocarcinoma Adenocarcinoma - genetics Adenocarcinoma - pathology Biomarkers Biomarkers, Tumor - genetics Biomedical research Cancer Cancer therapies Colon Colorectal cancer Colorectal carcinoma Colorectal Neoplasms - genetics Colorectal Neoplasms - pathology Correlation analysis DNA methylation Gene expression Gene Expression Profiling - methods Gene Expression Regulation, Neoplastic - genetics Gene Regulatory Networks - genetics Genomes High-Throughput Nucleotide Sequencing - methods Humans Medical prognosis Metastasis MicroRNAs MicroRNAs - genetics miRNA mRNA Next-generation sequencing Pathogenesis Prognosis Rectum Regression analysis RNA, Messenger - genetics Software Survival Survival Analysis Survival Rate Tumorigenesis Tumors |
| title | MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal Cancer |
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