Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

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

Authors
Kim, Bu-YeoChoi, Dong WookWoo, Seon RangPark, Eun-RanLee, Je-GeunKim, Su-HyeonKoo, ImhoiPark, Sun-HooHan, Chul JuKim, Sang BumYeom, Young IlYang, Suk-JinYu, AmiLee, Jae WonJang, Ja JuneCho, Myung-HaingJeon, Won KyungPark, Young NyunSuh, Kyung-SukLee, Kee-Ho
Issue Date
10-Apr-2015
Publisher
BMC
Keywords
Recurrence-associated pathway; Hepatocellular carcinoma; Principal component analysis; Prognosis; Risk; Small tumor
Citation
BMC GENOMICS, v.16
Indexed
SCIE
SCOPUS
Journal Title
BMC GENOMICS
Volume
16
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/93851
DOI
10.1186/s12864-015-1472-x
ISSN
1471-2164
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.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Political Science & Economics > Department of Statistics > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher LEE, JAE WON photo

LEE, JAE WON
College of Political Science & Economics (Department of Statistics)
Read more

Altmetrics

Total Views & Downloads

BROWSE