Evaluation of Methods for Monitoring Drug Resistance in Chronic Hepatitis B Patients during Lamivudine Therapy Based on Mass Spectrometry and Reverse Hybridization
- 1 April 2005
- journal article
- research article
- Published by SAGE Publications in Antiviral Therapy
- Vol. 10 (3) , 441-449
- https://doi.org/10.1177/135965350501000306
Abstract
A matrix-assisted laser desorption/ionization time-of-flight mass spectrometry-based genotyping assay, termed restriction fragment mass polymorphism (RFMP) has been recently developed for detecting hepatitis B virus (HBV) mutants. The assay is based on PCR amplification and mass measurement of oligonucleotides containing sites of mutations that confer resistance to lamivudine. We compared the efficacy and usefulness of the RFMP assay with a commercial assay using a reverse hybridization line probe technology, namely INNO-LiPA HBV DR (referred to henceforth as the LiPA assay), for the detection of lamivudine-resistant HBV mutants. A total of 60 patient samples were analysed for the presence of mutations at rtL180M and rtM204I/V of HBV polymerase by the LiPA and RFMP assays. The ability to detect mutations at rtM204I/V was compared with defined mixtures of wild-type and mutant HBV cloned in plasmids at relative concentrations ranging from 1–25%. Concordance between methods was found to be 95.0% (57/60) when only the presence of resistance mutations was considered, regardless of quasispecies. In three cases, additional minor populations of resistant viruses were identified by RFMP. Defined mixtures were consistently successfully identified at a 1% relative concentration of mutant versus wild-type viruses by the RFMP assay and 4% by the LiPA assay. The RFMP assay proved to be an accurate and reliable tool for detection of lamivudine-resistant mutations and was more sensitive than the LiPA assay in detecting mixtures of mutant and wild-type viruses. The improved sensitivity of the RPMP assay can help monitor drug resistance as it develops, enabling early intervention and prevention.Keywords
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