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Gene Expression–Based Recurrence Prediction of Hepatitis B Virus–Related Human Hepatocellular Carcinoma
Purpose: The poor prognosis of hepatocellular carcinoma (HCC) is, in part, 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, hel...
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Published in: | Clinical cancer research 2008-04, Vol.14 (7), p.2056-2064 |
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Main Authors: | , , , , , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Purpose: The poor prognosis of hepatocellular carcinoma (HCC) is, in part, 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 from the treatment, and
at best, provide new therapeutic strategies for patients with a high risk of 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 B infections.
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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ISSN: | 1078-0432 1557-3265 |
DOI: | 10.1158/1078-0432.CCR-07-1473 |