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Convergence of Plasma Metabolomics and Proteomics Analysis to Discover Signatures of High-Grade Serous Ovarian Cancer
DC Field | Value | Language |
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dc.contributor.author | 김재훈 | - |
dc.date.accessioned | 2021-05-21T17:05:12Z | - |
dc.date.available | 2021-05-21T17:05:12Z | - |
dc.date.issued | 2020-11 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/182691 | - |
dc.description.abstract | The 5-year survival rate in the early and late stages of ovarian cancer differs by 63%. In addition, a liquid biopsy is necessary because there are no symptoms in the early stage and tissue collection is difficult without using invasive methods. Therefore, there is a need for biomarkers to achieve this goal. In this study, we found blood-based metabolite or protein biomarker candidates for the diagnosis of ovarian cancer in the 20 clinical samples (10 ovarian cancer patients and 10 healthy control subjects). Plasma metabolites and proteins were measured and quantified using mass spectrometry in ovarian cancer patients and control groups. We identified the differential abundant biomolecules (34 metabolites and 197 proteins) and statistically integrated molecules of different dimensions to better understand ovarian cancer signal transduction and to identify novel biological mechanisms. In addition, the biomarker reliability was verified through comparison with existing research results. Integrated analysis of metabolome and proteome identified emerging properties difficult to grasp with the single omics approach, more reliably interpreted the cancer signaling pathway, and explored new drug targets. Especially, through this analysis, proteins (PPCS, PMP2, and TUBB) and metabolites (L-carnitine and PC-O (30:0)) related to the carnitine system involved in cancer plasticity were identified. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | MDPI | - |
dc.relation.isPartOf | CANCERS | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | Convergence of Plasma Metabolomics and Proteomics Analysis to Discover Signatures of High-Grade Serous Ovarian Cancer | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Obstetrics and Gynecology (산부인과학교실) | - |
dc.contributor.googleauthor | Hee-Sung Ahn | - |
dc.contributor.googleauthor | Jeonghun Yeom | - |
dc.contributor.googleauthor | Jiyoung Yu | - |
dc.contributor.googleauthor | Young-Il Kwon | - |
dc.contributor.googleauthor | Jae-Hoon Kim | - |
dc.contributor.googleauthor | Kyunggon Kim | - |
dc.identifier.doi | 10.3390/cancers12113447 | - |
dc.contributor.localId | A00876 | - |
dc.relation.journalcode | J03449 | - |
dc.identifier.eissn | 2072-6694 | - |
dc.identifier.pmid | 33228226 | - |
dc.subject.keyword | FIA–MS/MS | - |
dc.subject.keyword | LC–MS/MS | - |
dc.subject.keyword | OMICS integrated analysis | - |
dc.subject.keyword | biomarker | - |
dc.subject.keyword | liquid biopsy | - |
dc.subject.keyword | metabolome | - |
dc.subject.keyword | ovarian cancer | - |
dc.subject.keyword | proteome | - |
dc.contributor.alternativeName | Kim, Jae Hoon | - |
dc.contributor.affiliatedAuthor | 김재훈 | - |
dc.citation.volume | 12 | - |
dc.citation.number | 11 | - |
dc.citation.startPage | 3447 | - |
dc.identifier.bibliographicCitation | CANCERS, Vol.12(11) : 3447, 2020-11 | - |
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