Literature DB >> 22286884

Development and performance of conventional HIV-1 phenotyping (Antivirogram®) and genotype-based calculated phenotyping assay (virco®TYPE HIV-1) on protease and reverse transcriptase genes to evaluate drug resistance.

Theresa Pattery1, Yvan Verlinden, Hans De Wolf, David Nauwelaers, Kurt Van Baelen, Margariet Van Houtte, Paula Mc Kenna, Jorge Villacian.   

Abstract

OBJECTIVES: A wide array of monitoring tests is commercially available to gauge HIV-1 disease progression and the overall health status of an HIV-1-infected patient. Viral load tests provide a picture of viral activity, while CD4 cell counts shed light on the immune status and can help physicians to prevent the development of opportunistic infections in patients. On the other hand, genotypic and phenotypic resistance testing and therapeutic drug monitoring help to optimize HIV-1 antiretroviral therapy. Resistance testing is currently recommended within the standard of care guidelines to aid the choice of new drug regimens following treatment failure(s).
METHODS: Genotypic testing described here is based on the amplification and sequencing of an HIV-1 protease (PR) and reverse transcriptase (RT) region from a patient sample to identify resistance mutations associated with PR and RT inhibitor resistance. A genotypic test takes a week to perform and the results are reported as a list of detected mutations. The virco®TYPE HIV-1 report uses genotypic data to predict phenotypic susceptibility by linear regression modeling that uses a large correlative database of genotype-phenotype pairs. Phenotypic testing measures the ability of the virus to replicate in the presence of a drug and provides a direct measurement of drug susceptibility in vitro. Since phenotypic analysis is laborious and time consuming (28 days), genotypic resistance testing is currently the standard reference method used for HIV-1 resistance testing. However, a phenotypic test is important when a patient harbors virus with complex genetic patterns, or when the mutational resistance profile for a particular drug is not well-characterized. RESULTS AND
CONCLUSIONS: Some of the currently used resistance tests are partially automated enabling laboratories to increase overall efficiency. However, maximum automation and standardization of the process, instruments and software that we have described here can overcome many of the problems encountered with current tests and aims at having a compliant, high-throughput, diagnostic laboratory, which can guarantee sample integrity from sample reception to result reporting. We also describe in detail the development and performance of virco®TYPE HIV-1 (genotype) and Antivirogram® (phenotype) assay on PR and RT genes to evaluate antiretroviral resistance.
Copyright © 2012 S. Karger AG, Basel.

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Year:  2012        PMID: 22286884     DOI: 10.1159/000332013

Source DB:  PubMed          Journal:  Intervirology        ISSN: 0300-5526            Impact factor:   1.763


  9 in total

1.  Laboratory Optimization Tweaks for Sanger Sequencing in a Resource-Limited Setting.

Authors:  Chika K Onwuamah; Azuka P Okwuraiwe; Rahaman A Ahmed; Judith O Sokei; Jamda Ponmak; Leona C Okoli; Brian A Kagurusi; Joseph Anejo-Okopi
Journal:  J Biomol Tech       Date:  2020-12

2.  Comparison of genotypic and virtual phenotypic drug resistance interpretations with laboratory-based phenotypes among CRF01_AE and subtype B HIV-infected individuals.

Authors:  Awachana Jiamsakul; Romanee Chaiwarith; Nicolas Durier; Sunee Sirivichayakul; Sasisopin Kiertiburanakul; Peter Van Den Eede; Rossana Ditangco; Adeeba Kamarulzaman; Patrick C K Li; Winai Ratanasuwan; Thira Sirisanthana
Journal:  J Med Virol       Date:  2015-07-17       Impact factor: 2.327

3.  Connection domain mutations during antiretroviral treatment failure in Mali: frequencies and impact on reverse transcriptase inhibitor activity.

Authors:  Almoustapha Issiaka Maiga; Sudhir Penugonda; Drissa Katile; Fodie Diallo; Djeneba Bocar Fofana; Baiba Berzins; Moussa Youssouffa Maiga; Aliou Sylla; Hamar Alassane Traore; Anne-Genevieve Marcelin; Vincent Calvez; Anatole Tounkara; Nobel Bellosillo; Robert Murphy; Babafemi Taiwo
Journal:  J Acquir Immune Defic Syndr       Date:  2012-11-01       Impact factor: 3.731

4.  Humanized mice recapitulate key features of HIV-1 infection: a novel concept using long-acting anti-retroviral drugs for treating HIV-1.

Authors:  Marc Nischang; Roger Sutmuller; Gustavo Gers-Huber; Annette Audigé; Duo Li; Mary-Aude Rochat; Stefan Baenziger; Ursula Hofer; Erika Schlaepfer; Stephan Regenass; Katie Amssoms; Bart Stoops; Anja Van Cauwenberge; Daniel Boden; Guenter Kraus; Roberto F Speck
Journal:  PLoS One       Date:  2012-06-13       Impact factor: 3.240

5.  A simple and cost-saving phenotypic drug susceptibility testing of HIV-1.

Authors:  Yunceng Weng; Ling Zhang; Jianfeng Huang; Jin Zhao; Peifang Luo; Siyuan Bi; Zhengrong Yang; Hai Zhu; Jean-Pierre Allain; Chengyao Li
Journal:  Sci Rep       Date:  2016-09-19       Impact factor: 4.379

6.  Characterization of the Drug Resistance Profiles of Patients Infected with CRF07_BC Using Phenotypic Assay and Ultra-Deep Pyrosequencing.

Authors:  Szu-Wei Huang; Wei-You Li; Wen-Hung Wang; Yu-Ting Lin; Chih-Hung Chou; Marcelo Chen; Hsien-Da Huang; Yen-Hsu Chen; Po-Liang Lu; Sheng-Fan Wang; Shinichi Oka; Yi-Ming Arthur Chen
Journal:  PLoS One       Date:  2017-01-20       Impact factor: 3.240

7.  Targeted resequencing of HIV variants by microarray thermodynamics.

Authors:  Wahyu W Hadiwikarta; Bieke Van Dorst; Karen Hollanders; Lieven Stuyver; Enrico Carlon; Jef Hooyberghs
Journal:  Nucleic Acids Res       Date:  2013-08-08       Impact factor: 16.971

8.  A polymorphism at position 400 in the connection subdomain of HIV-1 reverse transcriptase affects sensitivity to NNRTIs and RNaseH activity.

Authors:  David W Wright; Ilona P Deuzing; Philippe Flandre; Peter van den Eede; Micheline Govaert; Laurentia Setiawan; Peter V Coveney; Anne-Geneviève Marcelin; Vincent Calvez; Charles A B Boucher; Nancy Beerens
Journal:  PLoS One       Date:  2013-10-02       Impact factor: 3.240

9.  Comparison of predicted susceptibility between genotype and virtual phenotype HIV drug resistance interpretation systems among treatment-naive HIV-infected patients in Asia: TASER-M cohort analysis.

Authors:  Awachana Jiamsakul; Rami Kantor; Patrick C K Li; Sunee Sirivichayakul; Thira Sirisanthana; Pacharee Kantipong; Christopher K C Lee; Adeeba Kamarulzaman; Winai Ratanasuwan; Rossana Ditangco; Thida Singtoroj; Somnuek Sungkanuparph
Journal:  BMC Res Notes       Date:  2012-10-24
  9 in total

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