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Hepatic microRNA expression is associated with the response to interferon treatment of chronic hepatitis C.

Murakami Y, Tanaka M, Toyoda H, Hayashi K, Kuroda M, Tajima A, Shimotohno K - BMC Med Genomics (2010)

Bottom Line: The expression level of 470 mature miRNAs found their biopsy specimen, obtained prior to the combination therapy, were quantified using microarray analysis.We found that the expression level of 9 miRNAs were significantly different in the sustained virological response (SVR) and non-responder (NR) groups.The hepatic miRNA expression pattern that exists in CHC patients before combination therapy is associated with their therapeutic outcome.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Genomic Medicine, Kyoto University Graduate School of Medicine, 53 Shogoinkawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan. ymurakami@genome.med.kyoto-u.ac.jp

ABSTRACT

Background: HCV infection frequently induces chronic liver diseases. The current standard treatment for chronic hepatitis (CH) C combines pegylated interferon (IFN) and ribavirin, and is less than ideal due to undesirable effects. MicroRNAs (miRNAs) are endogenous small non-coding RNAs that control gene expression by degrading or suppressing the translation of target mRNAs. In this study we administered the standard combination treatment to CHC patients. We then examined their miRNA expression profiles in order to identify the miRNAs that were associated with each patient's drug response.

Methods: 99 CHC patients with no anti-viral therapy history were enrolled. The expression level of 470 mature miRNAs found their biopsy specimen, obtained prior to the combination therapy, were quantified using microarray analysis. The miRNA expression pattern was classified based on the final virological response to the combination therapy. Monte Carlo Cross Validation (MCCV) was used to validate the outcome of the prediction based on the miRNA expression profile.

Results: We found that the expression level of 9 miRNAs were significantly different in the sustained virological response (SVR) and non-responder (NR) groups. MCCV revealed an accuracy, sensitivity, and specificity of 70.5%, 76.5% and 63.3% in SVR and non-SVR and 70.0%, 67.5%, and 73.7% in relapse (R) and NR, respectively.

Conclusions: The hepatic miRNA expression pattern that exists in CHC patients before combination therapy is associated with their therapeutic outcome. This information can be utilized as a novel biomarker to predict drug response and can also be applied to developing novel anti-viral therapy for CHC patients.

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Method for predicting the clinical outcome using MCCV. Prediction performance of signatures from 35 miRNAs (Table 2 and 3). Left: Mean accuracy, specificity, and sensitivity (% in vertical axis) as a function of the training set size were determined for the 100 random splits of patients (non-SVR (NR+R) vs. SVR). Right: prediction performance of the training set size was determined by performing 48 random splits of patients (NR vs. R). A. Prediction performance (mean accuracy, specificity, and sensitivity) and number of miRNAs which was used for the prediction are also shown in each training set (TS) and validation set (VS).
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Figure 4: Method for predicting the clinical outcome using MCCV. Prediction performance of signatures from 35 miRNAs (Table 2 and 3). Left: Mean accuracy, specificity, and sensitivity (% in vertical axis) as a function of the training set size were determined for the 100 random splits of patients (non-SVR (NR+R) vs. SVR). Right: prediction performance of the training set size was determined by performing 48 random splits of patients (NR vs. R). A. Prediction performance (mean accuracy, specificity, and sensitivity) and number of miRNAs which was used for the prediction are also shown in each training set (TS) and validation set (VS).

Mentions: Before initial drug administration, we attempted to simulate the clinical outcome of the combination therapy before drug administration by using MCCV. We first extracted the SVR and non-SVR groups from all of the patients, and then the R and NR groups were predicted afterwards. MCCV simulation showed that the accuracy, specificity, and sensitivity of the liver specimen classified as SVR or non-SVR was up to 70.5%, 63.3%, and 76.8%, respectively (TSs = 80). On the other hand, the accuracy, specificity, and sensitivity of the liver specimen classified as R or NR was 70.0%, 73.7%, and 67.5%, respectively (TSs = 42)(Figure 4). Fold change of their normalized expression level, P value, and number of selection by MCCV in the 35 informative miRNAs that were identified based on the all patients are shown in Table 2 and 3.


Hepatic microRNA expression is associated with the response to interferon treatment of chronic hepatitis C.

Murakami Y, Tanaka M, Toyoda H, Hayashi K, Kuroda M, Tajima A, Shimotohno K - BMC Med Genomics (2010)

Method for predicting the clinical outcome using MCCV. Prediction performance of signatures from 35 miRNAs (Table 2 and 3). Left: Mean accuracy, specificity, and sensitivity (% in vertical axis) as a function of the training set size were determined for the 100 random splits of patients (non-SVR (NR+R) vs. SVR). Right: prediction performance of the training set size was determined by performing 48 random splits of patients (NR vs. R). A. Prediction performance (mean accuracy, specificity, and sensitivity) and number of miRNAs which was used for the prediction are also shown in each training set (TS) and validation set (VS).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2984584&req=5

Figure 4: Method for predicting the clinical outcome using MCCV. Prediction performance of signatures from 35 miRNAs (Table 2 and 3). Left: Mean accuracy, specificity, and sensitivity (% in vertical axis) as a function of the training set size were determined for the 100 random splits of patients (non-SVR (NR+R) vs. SVR). Right: prediction performance of the training set size was determined by performing 48 random splits of patients (NR vs. R). A. Prediction performance (mean accuracy, specificity, and sensitivity) and number of miRNAs which was used for the prediction are also shown in each training set (TS) and validation set (VS).
Mentions: Before initial drug administration, we attempted to simulate the clinical outcome of the combination therapy before drug administration by using MCCV. We first extracted the SVR and non-SVR groups from all of the patients, and then the R and NR groups were predicted afterwards. MCCV simulation showed that the accuracy, specificity, and sensitivity of the liver specimen classified as SVR or non-SVR was up to 70.5%, 63.3%, and 76.8%, respectively (TSs = 80). On the other hand, the accuracy, specificity, and sensitivity of the liver specimen classified as R or NR was 70.0%, 73.7%, and 67.5%, respectively (TSs = 42)(Figure 4). Fold change of their normalized expression level, P value, and number of selection by MCCV in the 35 informative miRNAs that were identified based on the all patients are shown in Table 2 and 3.

Bottom Line: The expression level of 470 mature miRNAs found their biopsy specimen, obtained prior to the combination therapy, were quantified using microarray analysis.We found that the expression level of 9 miRNAs were significantly different in the sustained virological response (SVR) and non-responder (NR) groups.The hepatic miRNA expression pattern that exists in CHC patients before combination therapy is associated with their therapeutic outcome.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Genomic Medicine, Kyoto University Graduate School of Medicine, 53 Shogoinkawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan. ymurakami@genome.med.kyoto-u.ac.jp

ABSTRACT

Background: HCV infection frequently induces chronic liver diseases. The current standard treatment for chronic hepatitis (CH) C combines pegylated interferon (IFN) and ribavirin, and is less than ideal due to undesirable effects. MicroRNAs (miRNAs) are endogenous small non-coding RNAs that control gene expression by degrading or suppressing the translation of target mRNAs. In this study we administered the standard combination treatment to CHC patients. We then examined their miRNA expression profiles in order to identify the miRNAs that were associated with each patient's drug response.

Methods: 99 CHC patients with no anti-viral therapy history were enrolled. The expression level of 470 mature miRNAs found their biopsy specimen, obtained prior to the combination therapy, were quantified using microarray analysis. The miRNA expression pattern was classified based on the final virological response to the combination therapy. Monte Carlo Cross Validation (MCCV) was used to validate the outcome of the prediction based on the miRNA expression profile.

Results: We found that the expression level of 9 miRNAs were significantly different in the sustained virological response (SVR) and non-responder (NR) groups. MCCV revealed an accuracy, sensitivity, and specificity of 70.5%, 76.5% and 63.3% in SVR and non-SVR and 70.0%, 67.5%, and 73.7% in relapse (R) and NR, respectively.

Conclusions: The hepatic miRNA expression pattern that exists in CHC patients before combination therapy is associated with their therapeutic outcome. This information can be utilized as a novel biomarker to predict drug response and can also be applied to developing novel anti-viral therapy for CHC patients.

Show MeSH
Related in: MedlinePlus