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Recurrence-associated pathways in hepatitis B virus-positive hepatocellular carcinoma

Cited 6 time in Web of Science Cited 8 time in Scopus
Authors
Kim, Bu-Yeo; Choi, Dong Wook; Woo, Seon Rang; Park, Eun-Ran; Lee, Je-Geun; Kim, Su-Hyeon; Koo, Imhoi; Park, Sun-Hoo; Han, Chul Ju; Kim, Sang Bum; Yeom, Young Il; Yang, Suk-Jin; Yu, Ami; Lee, Jae Won; Jang, Ja June; Cho, Myung-Haing; Jeon, Won Kyung; Park, Young Nyun; Suh, Kyung-Suk; Lee, Kee-Ho
Issue Date
2015-04-10
Publisher
BioMed Central
Citation
BMC Genomics, 16(1):279
Keywords
Recurrence-associated pathwayHepatocellular carcinomaPrincipal component analysisPrognosisRiskSmall tumor
Description
This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
Abstract
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.
Language
English
URI
http://hdl.handle.net/10371/100473
DOI
https://doi.org/10.1186/s12864-015-1472-x
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College of Medicine/School of Medicine (의과대학/대학원)Surgery (외과학전공)Journal Papers (저널논문_외과학전공)
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