CANcer-specific Evaluation System (CANES): a high-accuracy platform, for preclinical single/multi-biomarker discovery
DC Field | Value | Language |
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dc.contributor.author | Kwon, Min-Seok | - |
dc.contributor.author | Nam, Seungyoon | - |
dc.contributor.author | Lee, Sungyoung | - |
dc.contributor.author | Ahn, Young Zoo | - |
dc.contributor.author | Chang, Hae Ryung | - |
dc.contributor.author | Kim, Yon Hui | - |
dc.contributor.author | Park, Taesung | - |
dc.date.available | 2020-02-27T17:42:01Z | - |
dc.date.created | 2020-02-06 | - |
dc.date.issued | 2017-09-19 | - |
dc.identifier.issn | 1949-2553 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/5701 | - |
dc.description.abstract | The recent creation of enormous, cancer-related "Big Data" public depositories represents a powerful means for understanding tumorigenesis. However, a consistently accurate system for clinically evaluating single/multi-biomarkers remains lacking, and it has been asserted that oft-failed clinical advancement of biomarkers occurs within the very early stages of biomarker assessment. To address these challenges, we developed a clinically testable, web-based tool, CANcer-specific single/multi-biomarker Evaluation System (CANES), to evaluate biomarker effectiveness, across 2,134 whole transcriptome datasets, from 94,147 biological samples (from 18 tumor types). For user-provided single/multi-biomarkers, CANES evaluates the performance of single/multi-biomarker candidates, based on four classification methods, support vector machine, random forest, neural networks, and classification and regression trees. In addition, CANES offers several advantages over earlier analysis tools, including: 1) survival analysis; 2) evaluation of mature miRNAs as markers for user-defined diagnostic or prognostic purposes; and 3) provision of a "pan-cancer" summary view, based on each single marker. We believe that such "landscape" evaluation of single/multi-biomarkers, for diagnostic therapeutic/prognostic decision-making, will be highly valuable for the discovery and "repurposing" of existing biomarkers (and their specific targeted therapies), leading to improved patient therapeutic stratification, a key component of targeted therapy success for the avoidance of therapy resistance. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IMPACT JOURNALS LLC | - |
dc.relation.isPartOf | ONCOTARGET | - |
dc.subject | GENE-EXPRESSION OMNIBUS | - |
dc.subject | BREAST-CANCER | - |
dc.subject | MICROARRAY DATA | - |
dc.subject | LANDSCAPE | - |
dc.subject | ALGORITHM | - |
dc.subject | PROFILES | - |
dc.subject | NETWORKS | - |
dc.subject | FAILURES | - |
dc.title | CANcer-specific Evaluation System (CANES): a high-accuracy platform, for preclinical single/multi-biomarker discovery | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000411153300049 | - |
dc.identifier.doi | 10.18632/oncotarget.19270 | - |
dc.identifier.bibliographicCitation | ONCOTARGET, v.8, no.41, pp.69808 - 69822 | - |
dc.identifier.scopusid | 2-s2.0-85030255639 | - |
dc.citation.endPage | 69822 | - |
dc.citation.startPage | 69808 | - |
dc.citation.title | ONCOTARGET | - |
dc.citation.volume | 8 | - |
dc.citation.number | 41 | - |
dc.contributor.affiliatedAuthor | Nam, Seungyoon | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | biomarker performance | - |
dc.subject.keywordAuthor | claudin | - |
dc.subject.keywordAuthor | gastric cancer | - |
dc.subject.keywordAuthor | transcriptome | - |
dc.subject.keywordAuthor | data mining | - |
dc.subject.keywordPlus | GENE-EXPRESSION OMNIBUS | - |
dc.subject.keywordPlus | BREAST-CANCER | - |
dc.subject.keywordPlus | MICROARRAY DATA | - |
dc.subject.keywordPlus | LANDSCAPE | - |
dc.subject.keywordPlus | ALGORITHM | - |
dc.subject.keywordPlus | PROFILES | - |
dc.subject.keywordPlus | NETWORKS | - |
dc.subject.keywordPlus | FAILURES | - |
dc.relation.journalResearchArea | Oncology | - |
dc.relation.journalResearchArea | Cell Biology | - |
dc.relation.journalWebOfScienceCategory | Oncology | - |
dc.relation.journalWebOfScienceCategory | Cell Biology | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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