Skip to main content

Advertisement

SpringerLink
Log in

Two Different Patterns of Mutations are Involved in the Genotypic Resistance Score for Atazanavir Boosted Versus Unboosted by Ritonavir in Multiple Failing Patients

  • Clinical and Epidemiological Study
  • Published:
Infection Aims and scope Submit manuscript

Abstract

Objectives:

The protease inhibitor atazanavir (ATV) can be used either boosted by ritonavir (ATV300/r) or unboosted (ATV400). To date, however, genotypic resistance scores (GRSs) have been developed only for boosted-ATV. We have determined GRS associated with virologic response (VR) for both ATV300/r and ATV400 in highly pre-treated HIV-1 infected patients.

Patients and Methods:

We analyzed the results of genotypic tests available 0–3 months before the initiation of an ATV-containing regimen in 159 patients with HIV-RNA ≥ 500 copies/ml (ATV300/r group: 74; ATV400 group: 85) who were enrolled in the CARe study through an Early Access Program. The impact of baseline protease mutations on VR (≥ 1 log10copies/ml HIV-RNA decrease at 12–24 weeks) was analyzed using Fisher’s exact test. Mutated protease amino acid positions (MPP) with p < 0.20 were retained for further analysis. The GRSs were determined by a step-by-step analysis using the χ2 test for trend.

Results:

The GRSs for ATV300/r and ATV400 revealed differing sets of mutations. For ATV300/r, 12 MPPs (10C/I/V + 32I + 34Q + 46I/L + 53L + 54A/M/V + 82A/F/I/T + 84V + 90M – 15E/G/L/V – 69K/M/N/Q/R/T/Y – 72M/ T/V; p = 1.38 × 10–9) were the most strongly associated with VR (VR: 100%, 78.3%, 83.3%, 75% and 0% of patients with a score of –2/–1, 0, 1, 2, and ≥ 3, respectively); the last three MPPs (I15/H69/I72) were associated with a better VR. For ATV400, nine MPPs (16E + 20I/M/R/T/V + 32I + 33F/I/V + 53L/Y + 64L/M/ V + 71I/T/V + 85V + 93L/M; p = 9.42 × 10–8) were most strongly associated with VR (VR: 83.3%, 66.7%, 5.9%, 0% of patients with 0, 1/2, 3, and ≥ 4 MPP, respectively). Differences between GRSs for ATV300/r and ATV400 may be due to different ATV drug levels (boosted vs unboosted), favoring different pathways of escape from antiviral pressure.

Conclusions:

Both GRSs were independent predictors of response in a multivariable logistic regression model. Nevertheless, cross-validation of these GRSs on different patient databases is required before their implementation in clinical practice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. DHHS panel on antiretroviral guidelines for adults and adolescents: guidelines for the use of antiretroviral agents in HIV-1- Infected adults and adolescents 2007. Available at: http://aidsinfo.nih.gov/Guidelines/.

  2. Euro Guidelines Group for HIV Resistance: Clinical and laboratory guidelines for the use of HIV-1 drug resistance testing as part of treatment management: recommendations for the European setting. AIDS 2001; 15:309–320.

    Article  Google Scholar 

  3. Hirsch MS, Brun-Vezinet F, Clotet B, et al. Antiretroviral drug resistance testing in adults infected with human immunodeficiency virus type 1: 2003. Recommendations of an international AIDS society-USA panel. Clin Infect Dis 2003; 37: 113–128.

    Article  PubMed  Google Scholar 

  4. Brun-Vezinet F, Descamps D, Ruffault A, et al. Clinically relevant interpretation of genotype for resistance to abacavir. AIDS 2003; 17: 1795–1802.

    Article  PubMed  CAS  Google Scholar 

  5. De Meyer S, Vangeneugden T, Lefebvre E, et al. Phenotypic and genotypic determinants of resistance to TMC114: pooled analysis of POWER 1, 2 and 3 (Abstract 73). XV International HIV Drug Resistance Workshop. Sitges, June 2006.

  6. King MS, Rode R, Cohen-Codar I, et al. Predictive genotypic algorithm for virologic response to lopinavir-ritonavir in protease inhibitor-experienced patients. Antimicrob Agents Chemother 2007; 51: 3067–3074.

    Article  PubMed  CAS  Google Scholar 

  7. Marcelin AG, Lamotte C, Delaugerre C, et al. Genotypic inhibitory quotient as predictor of virological response to ritonaviramprenavir in human immunodeficiency virus type 1 protease inhibitor-experienced patients. Antimicrob Agents Chemother 2003; 47: 594–600.

    Article  PubMed  CAS  Google Scholar 

  8. Marcelin AG, Dalban C, Peytavin G, et al. Clinically relevant interpretation of genotype and relationship to plasma drug concentrations for resistance to saquinavir-ritonavir in human immunodeficiency virus type 1 protease inhibitor-experienced patients. Antimicrob Agents Chemother 2004; 48: 4687–4692.

    Article  PubMed  CAS  Google Scholar 

  9. Marcelin AG, Flandre P, Pavie J, et al. Clinically relevant genotype interpretation of resistance to didanosine. Antimicrob Agents Chemother 2005; 49: 1739–1744.

    Article  PubMed  CAS  Google Scholar 

  10. Marcelin AG, Flandre P, de Mendoza C, et al. Clinical validation of saquinavir/ritonavir genotypic resistance score in protease-inhibitor-experienced patients. Antivir Ther 2007; 12: 247–252.

    PubMed  CAS  Google Scholar 

  11. Masquelier B, Breilh D, Neau D, et al. Human immunodeficiency virus type 1 genotypic and pharmacokinetic determinants of the virological response to lopinavir-ritonavir-containing therapy in protease inhibitor-experienced patients. Antimicrob Agents Chemother 2002; 46: 2926–2932.

    Article  PubMed  CAS  Google Scholar 

  12. Masquelier B, Assoumou KL, Descamps D, et al. Genotypic determinants of the virological response to fosamprenavir/ritonavir in protease inhibitors experienced patients (Abstract 91). XV International HIV Drug Resistance Workshop. Sitges, June 2006.

  13. Pellegrin I, Breilh D, de Ragnaud JM, et al. Virological responses to atazanavir-ritonavir-based regimens: resistance-substitutions score and pharmacokinetic parameters (Reyaphar study). Antivir Ther 2006; 11: 421–429.

    PubMed  CAS  Google Scholar 

  14. Valer L, de Gonzalez Requenade D, Mendoza C, et al. Impact of drug levels and baseline genotype and phenotype on the virologic response to amprenavir/ritonavir-based salvage regimens. AIDS Patient Care STDS 2004; 18: 1–6.

    Article  PubMed  Google Scholar 

  15. Valer L, de Mendoza C, Soriano V: Predictive value of drug levels, HIV genotyping, and the genotypic inhibitory quotient (GIQ) on response to saquinavir/ritonavir in antiretroviral-experiencedHIVinfected patients. J Med Virol 2005; 77: 460–464.

    Article  PubMed  CAS  Google Scholar 

  16. Vora S, Marcelin AG, Günthard HF, et al. Clinical validation of atazanavir/ritonavir genotypic resistance score in protease inhibitor-experienced patients. AIDS 2006; 20: 35–40.

    Article  PubMed  CAS  Google Scholar 

  17. Baxter JD, Schapiro JM, Boucher CA, et al. Genotypic changes in human immunodeficiency virus type 1 protease associated with reduced susceptibility and virologic response to the protease inhibitor tipranavir. J Virol 2006; 80: 10794–10801.

    Article  PubMed  CAS  Google Scholar 

  18. Descamps D, Lambert-Niclot S, Marcelin AG, et al. Mutations associated with virologic response to darunavir/ritonavir in HIV-1-infected PI-experienced patients [PS 4/3]. 11th European AIDS Conference. Madrid, October 2007.

  19. Scherer J, Boucher CA, Baxter JD, Schapiro JM, Kohlbrenner VM, Hall DB: Improving the prediction of virologic response to tipranavir: the development of a tipranavir weighted score (poster 3.4/07). 11th European AIDS Conference. Madrid, October 2007.

  20. Gazzard B, on behalf of the BHIVA Writing Committee: British HIV Association (BHIVA) guidelines for the treatment of HIV-infected adults with antiretroviral therapy (2006). HIV Med 2006; 7: 487–503. Available at: http://www.bhiva.org/.

    Article  PubMed  CAS  Google Scholar 

  21. Goldsmith DR, Perry CM: Atazanavir. Drugs 2003; 63: 1679–1673.

    Article  PubMed  CAS  Google Scholar 

  22. Havlir DV, O’Marro SD: Atazanavir: new option for treatment of HIV infection. Clin Infect Dis 2004; 38: 1599–1604.

    Article  PubMed  CAS  Google Scholar 

  23. Flandre P, Marcelin AG, Pavie J, et al. Comparison of tests and procedures to build clinically relevant genotypic scores: application to the JAGUAR study. Antivir Ther 2005; 10: 479–487.

    PubMed  CAS  Google Scholar 

  24. Johnson VA, Brun-Vézinet F, Clotet B, et al. Update of the drug resistance mutations in HIV-1: fall 2005. Top HIV Med 2005; 13: 125–131.

    PubMed  Google Scholar 

  25. Stanford University: HIV Drug Resistance Database. Available at: http://hivdb.stanford.edu. Accessed August 2007.

  26. Brun-Vézinet F, Costagliola D, Khaled MA, et al. Clinically validated genotype analysis: guiding principles and statistical concerns. Antivir Ther 2004; 9: 465–478.

    PubMed  Google Scholar 

  27. Santoro MM, Bertoli A, Lorenzini P, et al. Viro-immunological response to ritonavir boosted or unboosted atazanavir in a large cohort of multiply treated patients: the CARe Study. AIDS Patient Care STDS 2008; 22: 7–16.

    Article  PubMed  Google Scholar 

  28. Gonzalez de Requena D, Bonora S, Cavecchia I, et al. Atazanavir Ctrough is associated with efficacy and safety at 24 weeks: definition of therapeutic range [Abstract 60]. 6th International Workshop on Clinical Pharmacology of HIV Therapy. Quebec City, April 2005.

  29. Elston R, Randall S, Xu F, et al. High plasma trough levels favour the selection of the I50V mutation pathway during development of APV resistance (Abstract 5.1). 2nd International Workshop on Clinical Pharmacology of HIV Therapy. Noordwijk, April 2001.

  30. Elston R, Randall S, Myers R, et al. Plasma trough levels correlate with distinct genetic mechanisms during the development of amprenavir resistance (Abstract 465). VIII Conference on Retroviruses and Opportunistic Infections. Chicago, February 2001.

  31. Taburet AM, Piketty C, Chazallon C, et al. Interactions between atazanavir-ritonavir and tenofovir in heavily pretreated human immunodeficiency virus-Infected patients. Antimicrob Agents Chemother 2004; 48: 2091–2096.

    Article  PubMed  CAS  Google Scholar 

  32. Johnson M, Grinsztejn B, Rodriguez C, et al. 96-week comparison of once-daily atazanavir/ritonavir and twice-daily lopinavir/ritonavir in patients with multiple virologic failures. AIDS 2006; 20: 711–718.

    Article  PubMed  CAS  Google Scholar 

  33. Naeger LK, Struble KA: Effect of baseline protease genotype and phenotype on HIV response to atazanavir/ritonavir in treatment-experienced patients. AIDS 2006; 20: 847–853.

    Article  PubMed  CAS  Google Scholar 

  34. Johnson M, Grinsztejn B, Rodriguez C, et al. Atazanavir plus ritonavir or saquinavir, and lopinavir/ritonavir in patients experiencing multiple virological failures. AIDS 2005; 19: 685–694.

    PubMed  CAS  Google Scholar 

  35. Colonno RJ, Thiry A, Limoli K, Parkin N: Activities of atazanavir (BMS-232632) against a large panel of human immunodeficiency virus type 1 clinical isolates resistant to one or more approved protease inhibitors. Antimicrob Agents Chemother 2003; 47: 1324–1333.

    Article  PubMed  CAS  Google Scholar 

  36. Gianotti N, Seminari E, Guffanti M, et al. Evaluation of atazanavir Ctrough, atazanavir genotypic inhibitory quotient, and baseline HIV genotype as predictors of a 24-week virological response in highly drug-experienced, HIV-infected patients treated with unboosted atazanavir. New Microbiol 2005; 28: 119–125.

    PubMed  CAS  Google Scholar 

  37. Svicher V, Ceccherini-Silberstein F, Erba F, et al. Characterization of novel HIV-1 protease mutations potentially involved in resistance to protease inhibitors. Antimicrob Agents Chemother 2005; 49: 2015–2025.

    Article  PubMed  CAS  Google Scholar 

  38. Flandre P, Marcelin AG, Soriano V, Yerly S, Katlama C, Calvez V: A method to estimate the weights for mutations within genotypic resistance scores: application to atazanavir and saquinavir (Abstract 167). XV International HIV Drug Resistance Workshop. Sitges, June 2006.

Download references

Author information

Authors and Affiliations

  1. Dept. of Experimental Medicine, University of Rome “Tor Vergata”, Via Montpellier 1, 00133, Rome, Italy

    M. M. Santoro, F. Ceccherini-Silberstein & C. F. Perno

  2. Molecular Virology, University Hospital Tor Vergata, Rome, Italy

    A. Bertoli

  3. INMI, Lazzaro Spallanzani, Rome, Italy

    P. Lorenzini, P. Narciso & A. Antinori

  4. Clinic of Infectious Diseases, Vita-Salute San Raffaele University, Milan, Italy

    N. Gianotti

  5. University of Modena and Reggio Emilia, Modena, Italy

    C. Mussini

  6. University of Brescia, Brescia, Italy

    C. Torti

  7. University of Turin, Turin, Italy

    G. Di Perri

  8. IRCCS, San Matteo, Pavia, Italy

    G. Barbarini & R. Maserati

  9. Institute of Infectious and Tropical Diseases, L. Sacco Hospital, Milan, Italy

    T. Bini, S. Melzi & V. Micheli

  10. Clinic of Infectious Diseases, Hospital Amedeo di Savoia, Turin, Italy

    P. Caramello

Authors
  1. M. M. Santoro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Bertoli
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. P. Lorenzini
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. F. Ceccherini-Silberstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. N. Gianotti
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. C. Mussini
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. C. Torti
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. G. Di Perri
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. G. Barbarini
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. T. Bini
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. S. Melzi
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. P. Caramello
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. R. Maserati
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. P. Narciso
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. V. Micheli
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. A. Antinori
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. C. F. Perno
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

and the CARe Study Group

Corresponding author

Correspondence to C. F. Perno.

Additional information

This work was presented in part at the 15th International HIV Drug Resistance Workshop, Sitges, Spain, 13–16 June 2006 (Abstract 89).

Rights and permissions

Reprints and permissions

About this article

Cite this article

Santoro, M.M., Bertoli, A., Lorenzini, P. et al. Two Different Patterns of Mutations are Involved in the Genotypic Resistance Score for Atazanavir Boosted Versus Unboosted by Ritonavir in Multiple Failing Patients. Infection 37, 233–243 (2009). https://doi.org/10.1007/s15010-008-8065-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s15010-008-8065-4

Keywords

Search

Navigation