Genomic Predictors for Recurrence Patterns of Hepatocellular Carcinoma: Model Derivation and Validation
- Authors
- Kim, Ji Hoon; Sohn, Bo Hwa; Lee, Hyun-Sung; Kim, Sang-Bae; Yoo, Jeong Eun; Park, Yun-Yong; Jeong, Woojin; Lee, Sung Sook; Park, Eun Sung; Kaseb, Ahmed; Kim, Baek Hui; Kim, Wan Bae; Yeon, Jong Eun; Byun, Kwan Soo; Chu, In-Sun; Kim, Sung Soo; Wang, Xin Wei; Thorgeirsson, Snorri S.; Luk, John M.; Kang, Koo Jeong; Heo, Jeonghoon; Park, Young Nyun; Lee, Ju-Seog
- Issue Date
- 12월-2014
- Publisher
- PUBLIC LIBRARY SCIENCE
- Citation
- PLOS MEDICINE, v.11, no.12
- Indexed
- SCIE
SCOPUS
- Journal Title
- PLOS MEDICINE
- Volume
- 11
- Number
- 12
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/96631
- DOI
- 10.1371/journal.pmed.1001770
- ISSN
- 1549-1277
- 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.
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Collections - College of Medicine > Department of Medical Science > 1. Journal Articles
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