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

Overview of attention for article published in BMC Genomics, April 2015
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Title
Recurrence-associated pathways in hepatitis B virus-positive hepatocellular carcinoma
Published in
BMC Genomics, April 2015
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.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 3%
Unknown 31 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 25%
Student > Ph. D. Student 5 16%
Student > Bachelor 4 13%
Other 3 9%
Student > Master 3 9%
Other 4 13%
Unknown 5 16%
Readers by discipline Count As %
Medicine and Dentistry 10 31%
Biochemistry, Genetics and Molecular Biology 4 13%
Agricultural and Biological Sciences 3 9%
Social Sciences 2 6%
Immunology and Microbiology 1 3%
Other 2 6%
Unknown 10 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 January 2016.
All research outputs
#15,389,473
of 19,208,681 outputs
Outputs from BMC Genomics
#7,388
of 9,730 outputs
Outputs of similar age
#172,595
of 244,041 outputs
Outputs of similar age from BMC Genomics
#1
of 1 outputs
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