Biomedical subjects

Aki Abe

Publications and source records attributed to Aki Abe.

3 recordsLinked to original sources

PubMed2005

Pretreatment prediction of interferon-alfa efficacy in chronic hepatitis C patients.

BACKGROUND & AIMS: Interferon has been used widely to treat patients with chronic hepatitis C infections. Prediction of interferon efficacy before treatment has been performed mainly by using viral information, such as viral load and genotype. This information has allowed the successful prediction of sustained responders (SR) and non-SRs, which includes transient responders (TR) and nonresponders (NR). In the current study we examined whether liver messenger RNA expression profiles also can be used to predict interferon efficacy. METHODS: RNA was isolated from 69 liver biopsy samples from patients receiving interferon monotherapy and was analyzed on a complementary DNA microarray. Of these 69 samples, 31 were used to develop an algorithm for predicting interferon efficacy, and 38 were used to validate the precision of the algorithm. We also applied our methodology to the prediction of the efficacy of interferon/ribavirin combination therapy using an additional 56 biopsy samples. RESULTS: Our microarray analysis combined with the algorithm was 94% successful at predicting SR/TR and NR patients. A validation study confirmed that this algorithm can predict interferon efficacy with 95% accuracy and a P value of less than .00001. Similarly, we obtained a 93% prediction efficacy and a P value of less than .0001 for patients receiving combination therapy. CONCLUSIONS: By using only host data from the complementary DNA microarray we are able to successfully predict SR/TR and NR patients for interferon therapy. Therefore, this technique can help determine the appropriate treatment for hepatitis C patients.

Adult↗

PubMed2004

A low-density cDNA microarray with a unique reference RNA: pattern recognition analysis for IFN efficacy prediction to HCV as a model.

We have designed and established a low-density (295 genes) cDNA microarray for the prediction of IFN efficacy in hepatitis C patients. To obtain a precise and consistent microarray data, we collected a data set from three spots for each gene (mRNA) and using three different scanning conditions. We also established an artificial reference RNA representing pseudo-inflammatory conditions from established hepatocyte cell lines supplemented with synthetic RNAs to 48 inflammatory genes. We also developed a novel algorithm that replaces the standard hierarchical-clustering method and allows handling of the large data set with ease. This algorithm utilizes a standard space database (SSDB) as a key scale to calculate the Mahalanobis distance (MD) from the center of gravity in the SSDB. We further utilized sMD (divided by parameter k: MD/k) to reduce MD number as a predictive value. The efficacy prediction of conventional IFN mono-therapy was 100% for non-responder (NR) vs. transient responder (TR)/sustained responder (SR) (P < 0.0005). Finally, we show that this method is acceptable for clinical application.

Algorithms↗

PubMed2004

Virological significance of low-level hepatitis B virus infection in patients with hepatitis C virus associated liver disease.

The clinical and virological significance of low-level viremia by hepatitis B virus (HBV) in hepatitis C virus (HCV)-infected patients remains unclear. HBV-DNA and HCV-RNA were, therefore, quantitatively analyzed in livers and sera from co-infected patients. HBV-DNA and HCV-RNA were quantitated using real-time detection of polymerase chain reaction (RTD-PCR), based on Taq-Man chemistry, in 220 non-HCV-infected healthy volunteers and 93 HCV-infected patients without detectable HBsAg. Serum HBV-DNA was detected in 4 (1.8%) of 220 non-HCV-infected healthy volunteers and 32 (34.4%) of 93 HCV-infected patients without detectable HBsAg. HCV-infected patients displayed higher frequency of HBV infection than healthy volunteers (P < 0.0001). Hepatocellular carcinoma (HCC) was more frequent among co-infected patients than among HCV mono-infected patients (P < 0.001). However, quantities of HBV-DNA in sera from co-infected patients were very low (8-19,000 copies/ml). HBV-DNA was detected in liver tissue from co-infected patients at 2-20 copies per 100 hepatocytes, accounting for 1/1,000 to 1/10,000 of HBsAg positive patients. In livers of patients with HCC and HCV or HBV mono-infection, the viruses existed predominantly in non-cancerous tissue, with levels 10- to 1,000-fold and 1- to 100-fold higher than in cancerous tissue, respectively. In contrast, patients co-infected with HCV and HBV displayed decreased HBV levels in non-cancerous tissue, but no change in cancerous tissue. These results indicate that low-level HBV infection exists in HCV-infected patients. HCC was more common among HCV/HBV co-infected patients than among HCV mono-infected patients. HCV might initiate hepatocarcinogenesis, but does not necessarily determine progression to HCC.

Adult↗