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Journal of Translational Medicine

, 6:44

First Online: 09 August 2008Received: 01 August 2008Accepted: 09 August 2008DOI: 10.1186-1479-5876-6-44

Cite this article as: Huang, T., Tu, K., Shyr, Y. et al. J Transl Med 2008 6: 44. doi:10.1186-1479-5876-6-44

Abstract

BackgroundThe status of a disease can be reflected by specific transcriptional profiles resulting from the induction or repression activity of a number of genes. Here, we proposed a time-dependent diagnostic model to predict the treatment effects of interferon and ribavirin to HCV infected patients by using time series microarray gene expression profiles of a published study.

MethodsIn the published study, 33 African-American AA and 36 Caucasian American CA patients with chronic HCV genotype 1 infection received pegylated interferon and ribavirin therapy for 28 days. HG-U133A GeneChip containing 22283 probes was used to analyze the global gene expression in peripheral blood mononuclear cells PBMC of all the patients on day 0 pretreatment, 1, 2, 7, 14, and 28. According to the decrease of HCV RNA levels on day 28, two categories of responses were defined: good and poor. A voting method based on Student-s t test, Wilcoxon test, empirical Bayes test and significance analysis of microarray was used to identify differentially expressed genes. A time-dependent diagnostic model based on C4.5 decision tree was constructed to predict the treatment outcome. This model not only utilized the gene expression profiles before the treatment, but also during the treatment. Leave-one-out cross validation was used to evaluate the performance of the model.

ResultsThe model could correctly predict all Caucasian American patients- treatment effects at very early time point. The prediction accuracy of African-American patients achieved 85.7%. In addition, thirty potential biomarkers which may play important roles in response to interferon and ribavirin were identified.

ConclusionOur method provides a way of using time series gene expression profiling to predict the treatment effect of pegylated interferon and ribavirin therapy on HCV infected patients. Similar experimental and bioinformatical strategies may be used to improve treatment decisions for other chronic diseases.

Electronic supplementary materialThe online version of this article doi:10.1186-1479-5876-6-44 contains supplementary material, which is available to authorized users.

Tao Huang, Kang Tu contributed equally to this work.

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Author: Tao Huang - Kang Tu - Yu Shyr - Chao-Chun Wei - Lu Xie - Yi-Xue Li

Source: https://link.springer.com/



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