Cancer Target Gene Screening: a web application for breast cancer target gene screening using multi-omics data analysis
Abstract Breast cancer comprises several molecular subtypes with distinct clinical features and treatment responses, and a substantial portion of each subtype remains incurable. A comprehensive analysis of multi-omics data and clinical profiles is required in order to better understand the biologica...
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Veröffentlicht in: | Briefings in bioinformatics 2020-03, Vol.21 (2), p.663-675 |
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description | Abstract
Breast cancer comprises several molecular subtypes with distinct clinical features and treatment responses, and a substantial portion of each subtype remains incurable. A comprehensive analysis of multi-omics data and clinical profiles is required in order to better understand the biological complexity of this cancer type and to identify new prognostic and therapeutic markers. Thus, there arises a need for useful analytical tools to assist in the investigation and clinical management of the disease. We developed Cancer Target Gene Screening (CTGS), a web application that provides rapid and user-friendly analysis of multi-omics data sets from a large number of primary breast tumors. It allows the investigation of genomic and epigenomic aberrations, evaluation of transcriptomic profiles and performance of survival analyses and of bivariate correlations between layers of omics data. Notably, the genome-wide screening function of CTGS prioritizes candidate genes of clinical and biological significance among genes with copy number alteration, DNA methylation and dysregulated expression by the integrative analysis of different types of omics data in customized subgroups of breast cancer patients. These features may help in the identification of druggable cancer driver genes in a specific subtype or the clinical condition of human breast cancer. CTGS is available at http://ctgs.biohackers.net. |
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Breast cancer comprises several molecular subtypes with distinct clinical features and treatment responses, and a substantial portion of each subtype remains incurable. A comprehensive analysis of multi-omics data and clinical profiles is required in order to better understand the biological complexity of this cancer type and to identify new prognostic and therapeutic markers. Thus, there arises a need for useful analytical tools to assist in the investigation and clinical management of the disease. We developed Cancer Target Gene Screening (CTGS), a web application that provides rapid and user-friendly analysis of multi-omics data sets from a large number of primary breast tumors. It allows the investigation of genomic and epigenomic aberrations, evaluation of transcriptomic profiles and performance of survival analyses and of bivariate correlations between layers of omics data. Notably, the genome-wide screening function of CTGS prioritizes candidate genes of clinical and biological significance among genes with copy number alteration, DNA methylation and dysregulated expression by the integrative analysis of different types of omics data in customized subgroups of breast cancer patients. These features may help in the identification of druggable cancer driver genes in a specific subtype or the clinical condition of human breast cancer. CTGS is available at http://ctgs.biohackers.net.</description><identifier>ISSN: 1467-5463</identifier><identifier>EISSN: 1477-4054</identifier><identifier>DOI: 10.1093/bib/bbz003</identifier><identifier>PMID: 30698638</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Applications programs ; Bivariate analysis ; Breast cancer ; Copy number ; Correlation analysis ; Data analysis ; Deoxyribonucleic acid ; DNA ; DNA methylation ; Gene expression ; Genes ; Genomes ; Subgroups ; Tumors</subject><ispartof>Briefings in bioinformatics, 2020-03, Vol.21 (2), p.663-675</ispartof><rights>The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com 2019</rights><rights>The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.</rights><rights>The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c345t-94aa0eb3ef478393f73589f64a9804b1b50cab01fbbe9845bfa72620116844b83</citedby><cites>FETCH-LOGICAL-c345t-94aa0eb3ef478393f73589f64a9804b1b50cab01fbbe9845bfa72620116844b83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,1598,27901,27902</link.rule.ids><linktorsrc>$$Uhttps://dx.doi.org/10.1093/bib/bbz003$$EView_record_in_Oxford_University_Press$$FView_record_in_$$GOxford_University_Press</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30698638$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kim, Hyung-Yong</creatorcontrib><creatorcontrib>Choi, Hee-Joo</creatorcontrib><creatorcontrib>Lee, Jeong-Yeon</creatorcontrib><creatorcontrib>Kong, Gu</creatorcontrib><title>Cancer Target Gene Screening: a web application for breast cancer target gene screening using multi-omics data analysis</title><title>Briefings in bioinformatics</title><addtitle>Brief Bioinform</addtitle><description>Abstract
Breast cancer comprises several molecular subtypes with distinct clinical features and treatment responses, and a substantial portion of each subtype remains incurable. A comprehensive analysis of multi-omics data and clinical profiles is required in order to better understand the biological complexity of this cancer type and to identify new prognostic and therapeutic markers. Thus, there arises a need for useful analytical tools to assist in the investigation and clinical management of the disease. We developed Cancer Target Gene Screening (CTGS), a web application that provides rapid and user-friendly analysis of multi-omics data sets from a large number of primary breast tumors. It allows the investigation of genomic and epigenomic aberrations, evaluation of transcriptomic profiles and performance of survival analyses and of bivariate correlations between layers of omics data. Notably, the genome-wide screening function of CTGS prioritizes candidate genes of clinical and biological significance among genes with copy number alteration, DNA methylation and dysregulated expression by the integrative analysis of different types of omics data in customized subgroups of breast cancer patients. These features may help in the identification of druggable cancer driver genes in a specific subtype or the clinical condition of human breast cancer. CTGS is available at http://ctgs.biohackers.net.</description><subject>Applications programs</subject><subject>Bivariate analysis</subject><subject>Breast cancer</subject><subject>Copy number</subject><subject>Correlation analysis</subject><subject>Data analysis</subject><subject>Deoxyribonucleic acid</subject><subject>DNA</subject><subject>DNA methylation</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Genomes</subject><subject>Subgroups</subject><subject>Tumors</subject><issn>1467-5463</issn><issn>1477-4054</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kc1LxDAQxYMoun5c_AMkIIIIdZMmbRNvsugqCB5cz2USp0ukXyYton-9WaoePHiZmcPvPYb3CDnm7JIzLebGmbkxn4yJLTLjsigSyTK5vbnzIslkLvbIfgivjKWsUHyX7AmWa5ULNSPvC2gteroCv8aBLrFF-mQ9Yuva9RUF-o6GQt_XzsLgupZWnafGI4SB2kk6TNL1Rhp-pHQMm9mM9eCSrnE20BcYgEIL9Udw4ZDsVFAHPPreB-T59ma1uEseHpf3i-uHxAqZDYmWAAyNwEoWSmhRFSJTusolaMWk4SZjFgzjlTGolcxMBUWap4zzXElplDgg55Nv77u3EcNQNi5YrGtosRtDmfJCZynPhYzo6R_0tRt9_DdSMtXRM-YXqYuJsr4LwWNV9t414D9KzspNHWWso5zqiPDJt-VoGnz5RX_yj8DZBHRj_5_RF3s_krs</recordid><startdate>20200323</startdate><enddate>20200323</enddate><creator>Kim, Hyung-Yong</creator><creator>Choi, Hee-Joo</creator><creator>Lee, Jeong-Yeon</creator><creator>Kong, Gu</creator><general>Oxford University Press</general><general>Oxford Publishing Limited (England)</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7SC</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>K9.</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20200323</creationdate><title>Cancer Target Gene Screening: a web application for breast cancer target gene screening using multi-omics data analysis</title><author>Kim, Hyung-Yong ; Choi, Hee-Joo ; Lee, Jeong-Yeon ; Kong, Gu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c345t-94aa0eb3ef478393f73589f64a9804b1b50cab01fbbe9845bfa72620116844b83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Applications programs</topic><topic>Bivariate analysis</topic><topic>Breast cancer</topic><topic>Copy number</topic><topic>Correlation analysis</topic><topic>Data analysis</topic><topic>Deoxyribonucleic acid</topic><topic>DNA</topic><topic>DNA methylation</topic><topic>Gene expression</topic><topic>Genes</topic><topic>Genomes</topic><topic>Subgroups</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Hyung-Yong</creatorcontrib><creatorcontrib>Choi, Hee-Joo</creatorcontrib><creatorcontrib>Lee, Jeong-Yeon</creatorcontrib><creatorcontrib>Kong, Gu</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Briefings in bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kim, Hyung-Yong</au><au>Choi, Hee-Joo</au><au>Lee, Jeong-Yeon</au><au>Kong, Gu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cancer Target Gene Screening: a web application for breast cancer target gene screening using multi-omics data analysis</atitle><jtitle>Briefings in bioinformatics</jtitle><addtitle>Brief Bioinform</addtitle><date>2020-03-23</date><risdate>2020</risdate><volume>21</volume><issue>2</issue><spage>663</spage><epage>675</epage><pages>663-675</pages><issn>1467-5463</issn><eissn>1477-4054</eissn><abstract>Abstract
Breast cancer comprises several molecular subtypes with distinct clinical features and treatment responses, and a substantial portion of each subtype remains incurable. A comprehensive analysis of multi-omics data and clinical profiles is required in order to better understand the biological complexity of this cancer type and to identify new prognostic and therapeutic markers. Thus, there arises a need for useful analytical tools to assist in the investigation and clinical management of the disease. We developed Cancer Target Gene Screening (CTGS), a web application that provides rapid and user-friendly analysis of multi-omics data sets from a large number of primary breast tumors. It allows the investigation of genomic and epigenomic aberrations, evaluation of transcriptomic profiles and performance of survival analyses and of bivariate correlations between layers of omics data. Notably, the genome-wide screening function of CTGS prioritizes candidate genes of clinical and biological significance among genes with copy number alteration, DNA methylation and dysregulated expression by the integrative analysis of different types of omics data in customized subgroups of breast cancer patients. These features may help in the identification of druggable cancer driver genes in a specific subtype or the clinical condition of human breast cancer. CTGS is available at http://ctgs.biohackers.net.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>30698638</pmid><doi>10.1093/bib/bbz003</doi><tpages>13</tpages></addata></record> |
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subjects | Applications programs Bivariate analysis Breast cancer Copy number Correlation analysis Data analysis Deoxyribonucleic acid DNA DNA methylation Gene expression Genes Genomes Subgroups Tumors |
title | Cancer Target Gene Screening: a web application for breast cancer target gene screening using multi-omics data analysis |
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