Genomic Predictors for Recurrence Patterns of Hepatocellular Carcinoma

Model Derivation and Validation

Ji Hoon Kim, Bo Hwa Sohn, Hyun Sung Lee, Sang Bae Kim, Jeong Eun Yoo, Yun Yong Park, Woojin Jeong, Sung Sook Lee, Eun Sung Park, Ahmed Kaseb, Baek-Hui Kim, Wan-Bae Kim, Jong Eun Yeon, Kwan Soo Byun, In Sun Chu, Sung Soo Kim, Xin Wei Wang, Snorri S. Thorgeirsson, John M. Luk, Koo Jeong Kang & 3 others Jeonghoon Heo, Young Nyun Park, Ju Seog Lee

Research output: Contribution to journalArticle

36 Citations (Scopus)

Abstract

Systematic analysis of gene expression data from human 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.

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.

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.

Please see later in the article for the Editors' Summary.

Original languageEnglish
JournalPLoS Medicine
Volume11
Issue number12
DOIs
Publication statusPublished - 2014 Jan 1
Externally publishedYes

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Hepatocellular Carcinoma
Recurrence
Genes
Multivariate Analysis
Confidence Intervals
Gene Regulatory Networks
Liver
Hepatitis B
Hepacivirus
Regeneration
Biomarkers
Gene Expression
Wounds and Injuries

ASJC Scopus subject areas

  • Medicine(all)

Cite this

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

In: PLoS Medicine, Vol. 11, No. 12, 01.01.2014.

Research output: Contribution to journalArticle

Kim, JH, Sohn, BH, Lee, HS, Kim, SB, Yoo, JE, Park, YY, Jeong, W, Lee, SS, Park, ES, Kaseb, A, Kim, B-H, Kim, W-B, Yeon, JE, Byun, KS, Chu, IS, Kim, SS, Wang, XW, Thorgeirsson, SS, Luk, JM, Kang, KJ, Heo, J, Park, YN & Lee, JS 2014, 'Genomic Predictors for Recurrence Patterns of Hepatocellular Carcinoma: Model Derivation and Validation', PLoS Medicine, vol. 11, no. 12. https://doi.org/10.1371/journal.pmed.1001770
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. / Genomic Predictors for Recurrence Patterns of Hepatocellular Carcinoma : Model Derivation and Validation. In: PLoS Medicine. 2014 ; Vol. 11, No. 12.
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abstract = "Systematic analysis of gene expression data from human 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.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.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.Please see later in the article for the Editors' Summary.",
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T2 - Model Derivation and Validation

AU - Kim, Ji Hoon

AU - Sohn, Bo Hwa

AU - Lee, Hyun Sung

AU - Kim, Sang Bae

AU - Yoo, Jeong Eun

AU - Park, Yun Yong

AU - Jeong, Woojin

AU - Lee, Sung Sook

AU - Park, Eun Sung

AU - Kaseb, Ahmed

AU - Kim, Baek-Hui

AU - Kim, Wan-Bae

AU - Yeon, Jong Eun

AU - Byun, Kwan Soo

AU - Chu, In Sun

AU - Kim, Sung Soo

AU - Wang, Xin Wei

AU - Thorgeirsson, Snorri S.

AU - Luk, John M.

AU - Kang, Koo Jeong

AU - Heo, Jeonghoon

AU - Park, Young Nyun

AU - Lee, Ju Seog

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