Recurrence-associated pathways in hepatitis B virus-positive hepatocellular carcinoma View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Bu-Yeo Kim, Dong Wook Choi, Seon Rang Woo, Eun-Ran Park, Je-Geun Lee, Su-Hyeon Kim, Imhoi Koo, Sun-Hoo Park, Chul Ju Han, Sang Bum Kim, Young Il Yeom, Suk-Jin Yang, Ami Yu, Jae Won Lee, Ja June Jang, Myung-Haing Cho, Won Kyung Jeon, Young Nyun Park, Kyung-Suk Suh, Kee-Ho Lee

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. More... »

PAGES

279

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12864-015-1472-x

DOI

http://dx.doi.org/10.1186/s12864-015-1472-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1016288325

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25888140


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