Title |
Recurrence-associated pathways in hepatitis B virus-positive hepatocellular carcinoma
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Published in |
BMC Genomics, April 2015
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DOI | 10.1186/s12864-015-1472-x |
Pubmed ID | |
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 |
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 (<3 cm). Using pathway-based analysis, we successfully identified the pathways involved in recurrence of HBV-positive HCC that may be effectively used as prognostic markers. |
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Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Canada | 1 | 3% |
Unknown | 34 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 8 | 23% |
Student > Ph. D. Student | 5 | 14% |
Student > Bachelor | 4 | 11% |
Other | 3 | 9% |
Student > Master | 3 | 9% |
Other | 5 | 14% |
Unknown | 7 | 20% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 10 | 29% |
Biochemistry, Genetics and Molecular Biology | 5 | 14% |
Agricultural and Biological Sciences | 3 | 9% |
Social Sciences | 2 | 6% |
Immunology and Microbiology | 1 | 3% |
Other | 2 | 6% |
Unknown | 12 | 34% |