계명대학교 의학도서관 Repository

Genomic Predictors for Recurrence Patterns of Hepatocellular Carcinoma: Model Derivation and Validation

Metadata Downloads
Author(s)
Ji Hoon KimBo Hwa SohnHyun-Sung LeeSang-Bae KimJeong Eun YooYun-Yong ParkWoojin JeongSung Sook LeeEun Sung ParkAhmed KasebBaek Hui KimWan Bae KimJong Eun YeonKwan Soo ByunIn-Sun ChuSung Soo KimXin Wei WangSnorri S. ThorgeirssonJohn M. LukKoo Jeong KangJeonghoon HeoYoung Nyun ParkJu-Seog Lee
Keimyung Author(s)
Kang, Koo Jeong
Department
Dept. of Surgery (외과학)
Journal Title
PLOS Medicine
Issued Date
2014
Volume
11
Issue
12
Abstract
Background: Typically observed at 2 y after surgical resection, late recurrence is a major challenge in the management of
hepatocellular carcinoma (HCC). We aimed to develop a genomic predictor that can identify patients at high risk for late
recurrence and assess its clinical implications.
Methods and Findings: Systematic analysis of gene expression data fromhuman liver undergoing hepatic injury and regeneration
revealed a 233-gene signature that was significantly associated with late recurrence of HCC. Using this signature, we developed a
prognostic predictor that can identify patients at high risk of late recurrence, and tested and validated the robustness of the
predictor in patients (n=396) who underwent surgery between 1990 and 2011 at four centers (210 recurrences during a median of
3.7 y of follow-up). In multivariate analysis, this signature was the strongest risk factor for late recurrence (hazard ratio, 2.2; 95%
confidence interval, 1.3–3.7; p= 0.002). In contrast, our previously developed tumor-derived 65-gene risk score was significantly
associated with early recurrence (p= 0.005) but not with late recurrence (p =0.7). In multivariate analysis, the 65-gene risk score was
the strongest risk factor for very early recurrence (,1 y after surgical resection) (hazard ratio, 1.7; 95% confidence interval, 1.1–2.6;
p= 0.01). The potential significance of STAT3 activation in late recurrence was predicted by gene network analysis and validated
later. We also developed and validated 4- and 20-gene predictors from the full 233-gene predictor. The main limitation of the study
is that most of the patients in our study were hepatitis B virus–positive. Further investigations are needed to test our prediction
models in patients with different etiologies of HCC, such as hepatitis C virus.
Conclusions: Two independently developed predictors reflected well the differences between early and late recurrence of
HCC at the molecular level and provided new biomarkers for risk stratification.
Keimyung Author(s)(Kor)
강구정
Publisher
School of Medicine
Citation
Ji Hoon Kim et al. (2014). Genomic Predictors for Recurrence Patterns of Hepatocellular Carcinoma: Model Derivation and Validation. PLOS Medicine, 11(12), e1001770–e1001770. doi: 10.1371/journal.pmed.1001770
Type
Article
ISSN
1549-1277
DOI
10.1371/journal.pmed.1001770
URI
https://kumel.medlib.dsmc.or.kr/handle/2015.oak/33680
Appears in Collections:
1. School of Medicine (의과대학) > Dept. of Surgery (외과학)
공개 및 라이선스
  • 공개 구분공개
파일 목록

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.