BACKGROUND: Quantitation of hepatitis C virus (HCV) RNA has become an essential tool for monitoring antiviral therapies in chronically infected patients. Different quantitative HCV RNA assays have been reported, mainly using techniques based on signal amplification with branched DNA (bDNA) technology or target sequence amplification by reverse-transcription PCR method (RT-PCR). OBJECTIVES AND STUDY DESIGN: An RT-PCR assay using TaqMan (fluorescence-based real-time PCR) and minor groove binding (MGB) probes was designed for the quantitative determination of HCV RNA in the clinical samples. Calculation of the concentration of HCV RNA was based on an external standard curve in the presence of an internal positive control (IPC). RESULTS: The assay detected 550 international units (IU)/mL with >95% probability of a positive result, with a linear range extending up to 10,000,000 IU/mL. The test exhibited good reproducibility with intra-assay and inter-assay coefficients of variation (CV) of 1.6% and 3.2%, respectively. All the major HCV genotypes were quantified with equivalent efficiency and accuracy. HCV genotypes 5 and 6 have also been amplified but too few samples have been tested. The performance of this new assay for quantitation of HCV viremia was evaluated with 213 anti-HCV positive sera, 120 of which corresponded to 30 patients sampled during the therapy. We used the Amplicor HCV Monitor assay (Roche Diagnostics, France) and the bDNA VERSANT HCV RNA assay (Bayer Diagnostics, France) to analyze 173 and 40 samples, respectively. The assay described here was significantly correlated with both commercial assays (R2 = 0.9535, P < 0.0001 and R2 = 0.8508, P < 0.0001, respectively). CONCLUSION: The present study illustrated the high reproducibility and reliability of our TaqMan HCV assay. Moreover, the monitoring of viral decline with our assay gave the same results as those obtained with the commercial assays indicating that this new technique provides an attractive approach for measuring HCV viral load.
BACKGROUND: Quantitation of hepatitis C virus (HCV) RNA has become an essential tool for monitoring antiviral therapies in chronically infectedpatients. Different quantitative HCV RNA assays have been reported, mainly using techniques based on signal amplification with branched DNA (bDNA) technology or target sequence amplification by reverse-transcription PCR method (RT-PCR). OBJECTIVES AND STUDY DESIGN: An RT-PCR assay using TaqMan (fluorescence-based real-time PCR) and minor groove binding (MGB) probes was designed for the quantitative determination of HCV RNA in the clinical samples. Calculation of the concentration of HCV RNA was based on an external standard curve in the presence of an internal positive control (IPC). RESULTS: The assay detected 550 international units (IU)/mL with >95% probability of a positive result, with a linear range extending up to 10,000,000 IU/mL. The test exhibited good reproducibility with intra-assay and inter-assay coefficients of variation (CV) of 1.6% and 3.2%, respectively. All the major HCV genotypes were quantified with equivalent efficiency and accuracy. HCV genotypes 5 and 6 have also been amplified but too few samples have been tested. The performance of this new assay for quantitation of HCV viremia was evaluated with 213 anti-HCV positive sera, 120 of which corresponded to 30 patients sampled during the therapy. We used the Amplicor HCV Monitor assay (Roche Diagnostics, France) and the bDNA VERSANT HCV RNA assay (Bayer Diagnostics, France) to analyze 173 and 40 samples, respectively. The assay described here was significantly correlated with both commercial assays (R2 = 0.9535, P < 0.0001 and R2 = 0.8508, P < 0.0001, respectively). CONCLUSION: The present study illustrated the high reproducibility and reliability of our TaqMan HCV assay. Moreover, the monitoring of viral decline with our assay gave the same results as those obtained with the commercial assays indicating that this new technique provides an attractive approach for measuring HCV viral load.
Authors: V Descamps; A Op de Beeck; C Plassart; E Brochot; C François; F Helle; M Adler; N Bourgeois; D Degré; G Duverlie; S Castelain Journal: J Clin Microbiol Date: 2011-12-07 Impact factor: 5.948
Authors: Jonathan J Cherry; Dione T Kobayashi; Maureen M Lynes; Nikolai N Naryshkin; Francesco Danilo Tiziano; Phillip G Zaworski; Lee L Rubin; Jill Jarecki Journal: Assay Drug Dev Technol Date: 2014-08 Impact factor: 1.738