Cited 9 times in
Recurrence-associated pathways in hepatitis B virus-positive hepatocellular carcinoma
DC Field | Value | Language |
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dc.contributor.author | 박영년 | - |
dc.date.accessioned | 2016-02-04T11:42:57Z | - |
dc.date.available | 2016-02-04T11:42:57Z | - |
dc.date.issued | 2015 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/141038 | - |
dc.description.abstract | BACKGROUND: Despite the recent identification of several prognostic gene signatures, the lack of common genes among experimental cohorts has posed a considerable challenge in uncovering the molecular basis underlying hepatocellular carcinoma (HCC) recurrence for application in clinical purposes. To overcome the limitations of individual gene-based analysis, we applied a pathway-based approach for analysis of HCC recurrence. RESULTS: By implementing a permutation-based semi-supervised principal component analysis algorithm using the optimal principal component, we selected sixty-four pathways associated with hepatitis B virus (HBV)-positive HCC recurrence (p < 0.01), from our microarray dataset composed of 142 HBV-positive HCCs. In relation to the public HBV- and public hepatitis C virus (HCV)-positive HCC datasets, we detected 46 (71.9%) and 18 (28.1%) common recurrence-associated pathways, respectively. However, overlap of recurrence-associated genes between datasets was rare, further supporting the utility of the pathway-based approach for recurrence analysis between different HCC datasets. Non-supervised clustering of the 64 recurrence-associated pathways facilitated the classification of HCC patients into high- and low-risk subgroups, based on risk of recurrence (p < 0.0001). The pathways identified were additionally successfully applied to discriminate subgroups depending on recurrence risk within the public HCC datasets. Through multivariate analysis, these recurrence-associated pathways were identified as an independent prognostic factor (p < 0.0001) along with tumor number, tumor size and Edmondson's grade. Moreover, the pathway-based approach had a clinical advantage in terms of discriminating the high-risk subgroup (N = 12) among patients (N = 26) with small HCC (<3 cm). CONCLUSIONS: Using pathway-based analysis, we successfully identified the pathways involved in recurrence of HBV-positive HCC that may be effectively used as prognostic markers. | - |
dc.description.statementOfResponsibility | open | - |
dc.format | application/pdf | - |
dc.relation.isPartOf | BMC GENOMICS | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.subject.MESH | Adult | - |
dc.subject.MESH | Algorithms | - |
dc.subject.MESH | Carcinoma, Hepatocellular/complications | - |
dc.subject.MESH | Carcinoma, Hepatocellular/diagnosis* | - |
dc.subject.MESH | Carcinoma, Hepatocellular/epidemiology | - |
dc.subject.MESH | Cluster Analysis | - |
dc.subject.MESH | Databases, Factual | - |
dc.subject.MESH | Disease-Free Survival | - |
dc.subject.MESH | Female | - |
dc.subject.MESH | Hepacivirus/isolation & purification | - |
dc.subject.MESH | Hepatitis B/complications | - |
dc.subject.MESH | Hepatitis B/diagnosis* | - |
dc.subject.MESH | Hepatitis B/virology | - |
dc.subject.MESH | Hepatitis B virus/isolation & purification | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Liver Neoplasms/complications | - |
dc.subject.MESH | Liver Neoplasms/diagnosis* | - |
dc.subject.MESH | Liver Neoplasms/epidemiology | - |
dc.subject.MESH | Male | - |
dc.subject.MESH | Middle Aged | - |
dc.subject.MESH | Neoplasm Recurrence, Local | - |
dc.subject.MESH | Principal Component Analysis | - |
dc.subject.MESH | Prognosis | - |
dc.subject.MESH | Risk | - |
dc.title | Recurrence-associated pathways in hepatitis B virus-positive hepatocellular carcinoma | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Pathology (병리학) | - |
dc.contributor.googleauthor | Bu-Yeo Kim | - |
dc.contributor.googleauthor | Dong Wook Choi | - |
dc.contributor.googleauthor | Seon Rang Woo | - |
dc.contributor.googleauthor | Eun-Ran Park | - |
dc.contributor.googleauthor | Je-Geun Lee | - |
dc.contributor.googleauthor | Su-Hyeon Kim | - |
dc.contributor.googleauthor | Imhoi Koo | - |
dc.contributor.googleauthor | Sun-Hoo Park | - |
dc.contributor.googleauthor | Chul Ju Han | - |
dc.contributor.googleauthor | Sang Bum Kim | - |
dc.contributor.googleauthor | Young Il Yeom | - |
dc.contributor.googleauthor | Suk-Jin Yang | - |
dc.contributor.googleauthor | Ami Yu | - |
dc.contributor.googleauthor | Jae Won Lee | - |
dc.contributor.googleauthor | Ja June Jang | - |
dc.contributor.googleauthor | Myung-Haing Cho | - |
dc.contributor.googleauthor | Won Kyung Jeon | - |
dc.contributor.googleauthor | Young Nyun Park | - |
dc.contributor.googleauthor | Kyung-Suk Suh | - |
dc.contributor.googleauthor | Kee-Ho Lee | - |
dc.identifier.doi | 10.1186/s12864-015-1472-x | - |
dc.admin.author | false | - |
dc.admin.mapping | false | - |
dc.contributor.localId | A01563 | - |
dc.relation.journalcode | J00357 | - |
dc.identifier.eissn | 1471-2164 | - |
dc.identifier.pmid | 25888140 | - |
dc.subject.keyword | Recurrence-associated pathway | - |
dc.subject.keyword | Hepatocellular carcinoma | - |
dc.subject.keyword | Principal component analysis | - |
dc.subject.keyword | Prognosis | - |
dc.subject.keyword | Risk | - |
dc.subject.keyword | Small tumor | - |
dc.contributor.alternativeName | Park, Young Nyun | - |
dc.contributor.affiliatedAuthor | Park, Young Nyun | - |
dc.rights.accessRights | free | - |
dc.citation.volume | 16 | - |
dc.citation.startPage | 279 | - |
dc.identifier.bibliographicCitation | BMC GENOMICS, Vol.16 : 279, 2015 | - |
dc.identifier.rimsid | 30472 | - |
dc.type.rims | ART | - |
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