Gene expression-based recurrence prediction of hepatitis B virus-related human hepatocellular carcinoma

Hyun Goo Woo, Eun Sung Park, JaeHee Cheon, Ju Han Kim, Ju Seog Lee, Bum Joon Park, Won Kim, Su Cheol Park, Young Jin Chung, Byeong Gwan Kim, Jung Hwan Yoon, Hyo Suk Lee, Chung Yong Kim, Nam Joon Yi, Kyung Suk Suh, Kuhn Uk Lee, In Sun Chu, Tania Roskams, Snorri S. Thorgeirsson, Yoon Jun Kim

Research output: Contribution to journalArticle

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Abstract

Purpose: The poor prognosis of hepatocellular carcinoma (HCC) is, inpart, due to the high rate of recurrence even after "curative resection" of tumors. Therefore, it is axiomatic that the development of an effective prognostic prediction model for HCC recurrence after surgery would, at minimum, help to identify in advance those who would most benefit fromthe treatment, and at best, provide new therapeutic strategies for patients with a high riskof early recurrence. Experimental Design: For the prediction of the recurrence time in patients with HCC, gene expression profiles were generated in 65 HCC patients with hepatitis Binfections. Result: Recurrence-associated gene expression signatures successfully discriminated between patients at high-risk and low-risk of early recurrence (P = 1.9 × 10 -6 , log-rank test). To test the consistency and robustness of the recurrence signature, we validated its prognostic power in an independent HCC microarray data set. CD24 was identified as a putative biomarker for the prediction of early recurrence. Genetic network analysis suggested that SP1 and peroxisome proliferator - activated receptor-α might have regulatory roles for the early recurrence of HCC. Conclusion: We have identified a gene expression signature that effectively predicted early recurrence of HCC independent of microarray platforms and cohorts, and provided novel biological insights into the mechanisms of tumor recurrence.

Original languageEnglish
Pages (from-to)2056-2064
Number of pages9
JournalClinical Cancer Research
Volume14
Issue number7
DOIs
Publication statusPublished - 2008 Apr 1

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Hepatitis B virus
Hepatocellular Carcinoma
Gene Expression
Recurrence
Transcriptome
Peroxisome Proliferator-Activated Receptors
Hepatitis
Neoplasms
Research Design
Biomarkers

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

Cite this

Woo, Hyun Goo ; Park, Eun Sung ; Cheon, JaeHee ; Kim, Ju Han ; Lee, Ju Seog ; Park, Bum Joon ; Kim, Won ; Park, Su Cheol ; Chung, Young Jin ; Kim, Byeong Gwan ; Yoon, Jung Hwan ; Lee, Hyo Suk ; Kim, Chung Yong ; Yi, Nam Joon ; Suh, Kyung Suk ; Lee, Kuhn Uk ; Chu, In Sun ; Roskams, Tania ; Thorgeirsson, Snorri S. ; Kim, Yoon Jun. / Gene expression-based recurrence prediction of hepatitis B virus-related human hepatocellular carcinoma. In: Clinical Cancer Research. 2008 ; Vol. 14, No. 7. pp. 2056-2064.
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abstract = "Purpose: The poor prognosis of hepatocellular carcinoma (HCC) is, inpart, due to the high rate of recurrence even after {"}curative resection{"} of tumors. Therefore, it is axiomatic that the development of an effective prognostic prediction model for HCC recurrence after surgery would, at minimum, help to identify in advance those who would most benefit fromthe treatment, and at best, provide new therapeutic strategies for patients with a high riskof early recurrence. Experimental Design: For the prediction of the recurrence time in patients with HCC, gene expression profiles were generated in 65 HCC patients with hepatitis Binfections. Result: Recurrence-associated gene expression signatures successfully discriminated between patients at high-risk and low-risk of early recurrence (P = 1.9 × 10 -6 , log-rank test). To test the consistency and robustness of the recurrence signature, we validated its prognostic power in an independent HCC microarray data set. CD24 was identified as a putative biomarker for the prediction of early recurrence. Genetic network analysis suggested that SP1 and peroxisome proliferator - activated receptor-α might have regulatory roles for the early recurrence of HCC. Conclusion: We have identified a gene expression signature that effectively predicted early recurrence of HCC independent of microarray platforms and cohorts, and provided novel biological insights into the mechanisms of tumor recurrence.",
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Woo, HG, Park, ES, Cheon, J, Kim, JH, Lee, JS, Park, BJ, Kim, W, Park, SC, Chung, YJ, Kim, BG, Yoon, JH, Lee, HS, Kim, CY, Yi, NJ, Suh, KS, Lee, KU, Chu, IS, Roskams, T, Thorgeirsson, SS & Kim, YJ 2008, 'Gene expression-based recurrence prediction of hepatitis B virus-related human hepatocellular carcinoma', Clinical Cancer Research, vol. 14, no. 7, pp. 2056-2064. https://doi.org/10.1158/1078-0432.CCR-07-1473

Gene expression-based recurrence prediction of hepatitis B virus-related human hepatocellular carcinoma. / Woo, Hyun Goo; Park, Eun Sung; Cheon, JaeHee; Kim, Ju Han; Lee, Ju Seog; Park, Bum Joon; Kim, Won; Park, Su Cheol; Chung, Young Jin; Kim, Byeong Gwan; Yoon, Jung Hwan; Lee, Hyo Suk; Kim, Chung Yong; Yi, Nam Joon; Suh, Kyung Suk; Lee, Kuhn Uk; Chu, In Sun; Roskams, Tania; Thorgeirsson, Snorri S.; Kim, Yoon Jun.

In: Clinical Cancer Research, Vol. 14, No. 7, 01.04.2008, p. 2056-2064.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Gene expression-based recurrence prediction of hepatitis B virus-related human hepatocellular carcinoma

AU - Woo, Hyun Goo

AU - Park, Eun Sung

AU - Cheon, JaeHee

AU - Kim, Ju Han

AU - Lee, Ju Seog

AU - Park, Bum Joon

AU - Kim, Won

AU - Park, Su Cheol

AU - Chung, Young Jin

AU - Kim, Byeong Gwan

AU - Yoon, Jung Hwan

AU - Lee, Hyo Suk

AU - Kim, Chung Yong

AU - Yi, Nam Joon

AU - Suh, Kyung Suk

AU - Lee, Kuhn Uk

AU - Chu, In Sun

AU - Roskams, Tania

AU - Thorgeirsson, Snorri S.

AU - Kim, Yoon Jun

PY - 2008/4/1

Y1 - 2008/4/1

N2 - Purpose: The poor prognosis of hepatocellular carcinoma (HCC) is, inpart, due to the high rate of recurrence even after "curative resection" of tumors. Therefore, it is axiomatic that the development of an effective prognostic prediction model for HCC recurrence after surgery would, at minimum, help to identify in advance those who would most benefit fromthe treatment, and at best, provide new therapeutic strategies for patients with a high riskof early recurrence. Experimental Design: For the prediction of the recurrence time in patients with HCC, gene expression profiles were generated in 65 HCC patients with hepatitis Binfections. Result: Recurrence-associated gene expression signatures successfully discriminated between patients at high-risk and low-risk of early recurrence (P = 1.9 × 10 -6 , log-rank test). To test the consistency and robustness of the recurrence signature, we validated its prognostic power in an independent HCC microarray data set. CD24 was identified as a putative biomarker for the prediction of early recurrence. Genetic network analysis suggested that SP1 and peroxisome proliferator - activated receptor-α might have regulatory roles for the early recurrence of HCC. Conclusion: We have identified a gene expression signature that effectively predicted early recurrence of HCC independent of microarray platforms and cohorts, and provided novel biological insights into the mechanisms of tumor recurrence.

AB - Purpose: The poor prognosis of hepatocellular carcinoma (HCC) is, inpart, due to the high rate of recurrence even after "curative resection" of tumors. Therefore, it is axiomatic that the development of an effective prognostic prediction model for HCC recurrence after surgery would, at minimum, help to identify in advance those who would most benefit fromthe treatment, and at best, provide new therapeutic strategies for patients with a high riskof early recurrence. Experimental Design: For the prediction of the recurrence time in patients with HCC, gene expression profiles were generated in 65 HCC patients with hepatitis Binfections. Result: Recurrence-associated gene expression signatures successfully discriminated between patients at high-risk and low-risk of early recurrence (P = 1.9 × 10 -6 , log-rank test). To test the consistency and robustness of the recurrence signature, we validated its prognostic power in an independent HCC microarray data set. CD24 was identified as a putative biomarker for the prediction of early recurrence. Genetic network analysis suggested that SP1 and peroxisome proliferator - activated receptor-α might have regulatory roles for the early recurrence of HCC. Conclusion: We have identified a gene expression signature that effectively predicted early recurrence of HCC independent of microarray platforms and cohorts, and provided novel biological insights into the mechanisms of tumor recurrence.

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