S-Space College of Veterinary Medicine (수의과대학) Dept. of Veterinary Medicine (수의학과) Journal Papers (저널논문_수의학과)
Recurrence-associated pathways in hepatitis B virus-positive hepatocellular carcinoma
- 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
- Issue Date
- BioMed Central
- BMC Genomics, Vol.16, p. 279
- Recurrence-associated pathway; Hepatocellular carcinoma; Principal component analysis; Prognosis; Risk; Small tumor
- This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
- 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.