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

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...

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Veröffentlicht in:BMC genomics 2015-04, Vol.16 (1), p.279-279, Article 279
Hauptverfasser: 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
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Sprache:eng
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Zusammenfassung: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. 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 (
ISSN:1471-2164
1471-2164
DOI:10.1186/s12864-015-1472-x