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; Jeonghoon Heo; Young Nyun Park; Ju Seog Lee

doi:10.1371/journal.pmed.1001770

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 KangJeonghoon Heo, Young Nyun Park, Ju Seog Lee

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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.

Original language	English (US)
Journal	PLoS Medicine
Volume	11
Issue number	12
DOIs	https://doi.org/10.1371/journal.pmed.1001770
State	Published - Dec 1 2014

ASJC Scopus subject areas

General Medicine

MD Anderson CCSG core facilities

Clinical Trials Office

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10.1371/journal.pmed.1001770

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Kim, J. H., Sohn, B. H., Lee, H. S., Kim, S. B., Yoo, J. E., Park, Y. Y., Jeong, W., Lee, S. S., Park, E. S., Kaseb, A., Kim, B. H., Kim, W. B., Yeon, J. E., Byun, K. S., Chu, I. S., Kim, S. S., Wang, X. W., Thorgeirsson, S. S., Luk, J. M., ... Lee, J. S. (2014). Genomic Predictors for Recurrence Patterns of Hepatocellular Carcinoma: Model Derivation and Validation. PLoS Medicine, 11(12). https://doi.org/10.1371/journal.pmed.1001770

Kim, JH, Sohn, BH, Lee, HS, Kim, SB, Yoo, JE, Park, YY, Jeong, W, Lee, SS, Park, ES, Kaseb, A, Kim, BH, Kim, WB, 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

@article{3a93267370334a00b20acaf08be201d4,

title = "Genomic Predictors for Recurrence Patterns of Hepatocellular Carcinoma: Model Derivation and Validation",

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.",

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

note = "Publisher Copyright: {\textcopyright} 2014 Kim et al.",

year = "2014",

month = dec,

day = "1",

doi = "10.1371/journal.pmed.1001770",

language = "English (US)",

volume = "11",

journal = "PLoS Medicine",

issn = "1549-1277",

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TY - JOUR

T1 - Genomic Predictors for Recurrence Patterns of Hepatocellular Carcinoma

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

PY - 2014/12/1

Y1 - 2014/12/1

N2 - 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.

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

Abstract

ASJC Scopus subject areas

MD Anderson CCSG core facilities

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