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Birgitt Dau, M.D. Postdoctoral Fellow in Infectious Diseases

Connection Domain Mutations in Treatment-Experienced Patients in the OPTIMA (Options in Management with Antiretrovirals) Trial. Birgitt Dau, M.D. Postdoctoral Fellow in Infectious Diseases US Department of Veterans Affairs and Stanford University.

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Birgitt Dau, M.D. Postdoctoral Fellow in Infectious Diseases

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  1. Connection Domain Mutations in Treatment-Experienced Patients in the OPTIMA (Options in Management with Antiretrovirals) Trial Birgitt Dau, M.D. Postdoctoral Fellow in Infectious Diseases US Department of Veterans Affairs and Stanford University

  2. Connection Domain (CD) Background and Rationale for Analysis • Codons 316-437 of HIV reverse transcriptase • Connects the DNA polymerase (1-315) and RNase H (438-560) domains • Most clinically available genotypic resistance tests have not sequenced the CD or RNase H domains • RNase H works during reverse transcription to degrade RNA from the DNA:RNA duplex • Mutations in RNase H slow its activity, allowing time for NRTI excision, and thus NRTI resistance1 • Mutations in the CD also affect RNase H efficiency2 1. Nikolenko et al, Proc Natl Acad Sci USA 2005 2. Julias et al, J Virol 2003

  3. HIV-1 Reverse Transcriptase

  4. In Vitro and In Vivo Data on CD Mutations • Many CD mutations are associated with ARV resistance to zidovudine, lamivudine, nevirapine and efavirenzin vitro • CD mutations increase fold change caused by TAMS1 and K103N2in vitro • Appearance of N348I was associated with an increase in viral load3 • A371V is associated with a history of AZT exposure4 • GN Nikolenko et al, Proc NatlAcadSci U S A 2005 • Harrigan et al, J Virol 2002 • SH Yap et al, PLoS Med 2007 • Santos et al, PLoS One, 2008

  5. Methods • HIV-1 reverse transcriptase gene sequences (codons 1-400) and virtual phenotypes were analyzed from 345 patients randomized in the OPTIMA trial • Phenotypic susceptibility scores (PSS) were calculated by adding the score for each drug in the patient’s initial on-study ARV regimen • 0 = no activity (FC > CCO2), 0.5 = partial activity (FC > CCO1 and < CCO2), 1 = full activity (< CCO1) • Virologic response was defined as a HIV viral load reduction of > 1 log10/mL after 24 weeks of ARV treatment • Statistical analysis • Fisher’s Exact Test, Logistic regression, Chi-square

  6. OPTIMA Trial1: Introduction • OPTIMA is a large treatment interruption trial from 2001-2006 • Open, randomized, prospective, multi-center management trial in patients with MDR who failed at least two ARV regimens • A 2 x 2 factorial design: • randomized to ARV drug free period (ARDFP) for 3 months or not (no ARDFP); • and to treatment by either standard antiretroviral therapy (ART) (< 4 ARV drugs) or Mega-ART (> 5 ARV drugs) • Primary outcomes: time to a new or recurrent AIDS event or death • Secondary outcomes: changes in CD4 count and HIV-1 viral load • Minimum follow-up = 1 year 1. See Poster LBPE1145

  7. OPTIMA1 Trial: Results • 368 subjects randomized: 98% male, mean age 49 years, mean CD4 130/mm3 and viral load 4.71 log10 copies/mL • Prior ARV use • 96% > 3 NRTI (median 5) • 97% 1 NNRTI (median 1) • 63% > PIs (median 3) • 2.5% were enfuvirtide experienced. • Baseline PSS: standard ART 1.8, Mega-ART 2.4 • Median ARDFP was 12 weeks (IQR: 12-14 weeks) • Comparing standard vs. Mega-ART; or ARDFP vs. No-ARDFP • No significant difference in time to primary outcome for AIDS or death • No significant difference in CD4 count or HIV viral load changes between the treatment arms 1. See poster LBPE1145

  8. Epidemiology of CD Mutations 1. Stanford HIV Database

  9. Association of CD Mutations with Primary ARV Mutations * CD mutations were not significantly associated with each other

  10. Univariate Analysis: Association of CD Mutations with Diminished Virologic Response to ART

  11. Multivariate Analysis: Factors Affecting Virologic Response 1. The PSS incorporates CD and other mutations

  12. Conclusions • CD mutations are far more frequent in treatment-experienced populations than in untreated populations • CD mutations are associated with primary RT mutations- • Likely shared selection pressure (treatment history) • Functional dependency, i.e. compensatory mutations, is possible • Additive effect of CD mutations above primary RT mutations in clinical practice is unknown

  13. Limitations • Linkage of CD and primary ARV mutations cannot be directly established without clonal analysis • Population sequencing underestimates the frequency of mutations present • RNase H mutations were not analyzed • The complicated background of mutations and suboptimal ARV treatment regimens made it hard to distinguish the effect of single mutations • Given extensive ARV resistance and limited treatment options, patients were unlikely to fully respond to any regimen, making it difficult to differentiate treatment response between groups of patients

  14. Future Directions • Ultra deep sequencing • Comparison of plasma vs. PBMC sample sequences • Clonal analysis to establish linkage between CD mutations and primary ARV-associated HIV RT mutations

  15. Tri-National Trials Collaboration Canadian Institutes of Health Research (CIHR) US Department of Veterans Affairs (VA) Medical Research Council (MRC) of the United Kingdom (UK). Collaborators Dieter Ayers Joel Singer Richard Harrigan Sheldon Brown Tassos Kyriakides Bill Cameron Brian Angus Mark Holodniy Acknowledgments

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