Www.ias2015.org What are possible biomarkers for cure-related interventions ? Lars Ostergaard, MD, Ph.D., DMSc Prof/Head Dept of infectious diseases Aarhus.

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Presentation transcript:

What are possible biomarkers for cure-related interventions ? Lars Ostergaard, MD, Ph.D., DMSc Prof/Head Dept of infectious diseases Aarhus University Hospital, Aarhus, Denmark

Disclosures –Gilead –Pfizer –Sanofi-Pasteur –Bionor –ViiV –Roche –MSD –BMS –Janssen

Definition of a biomarker A biological analysis that predicts a clinically relevant outcome

What are clinical relevant outcomes in cure research ? “I want my disease not to progress and not being transmitted to others without taking any pills – and maybe someday I can say that I am cured”.

What are clinical relevant outcomes in cure research ? Having undetectable viral load is the best predictor of “no progress” and “no transmission” With courtesy of Jonathan Li But without any “pills” the virus rebound – so the clinical relevant goal of any cure intervention is to delay the time to rebound

It is difficult to make predictions - especially about the future ! Piet Hein. Danish author ( )

BUT – we can. However, we need to know the exact outcome of an intervention (i.e. time to viral rebound) Outcome Intervention Possible biomarker

This implies that we need intervention studies with the outcome of ”time to viral rebound” - otherwise we can not determine the predictive value of any test

CONCLUSION 1 A NEED FOR STUDIES WITH ”TIME TO VIRAL REBOUND” AS THE OUTCOME IN ORDER TO ASSESS THE PREDICTIVE VALUE OF POTENTIAL CLINICALLY RELEVANT BIOMARKERS

AVAILABLE DATA WHAT ARE THE DATA ON POTENTIAL BIOMARKERS FROM STUDIES LOOKING AT TIME TO VIRAL REBOUND AFTER TREATMENT INTERRUPTIONS ATCG (compiled data) ANRS SPARTAC CLEAR STUDY (Biomarkers associated with elite controllers)

Factors associated with elite controllers Host factors Protective alleles HLA-B*27 and B*5701 Risk alleles HLA-B*07 and B*35 CD8 cytotoxicity capacity T-helper cells Regulatory T-cells NK cells Coexpression of CD160 and 2B4 Th17 and Th17/Treg ratio Cell-intrinsic type I interferon secretion Soluble CD14 IFN-γ IP-10 IL-4 IL-10 sCD40L GM-CSF ( Viral factors Anti-APOBEC3 Vif activity NEF deletion/truncation, Residual viral activity

ATCG treament interruption trials 124 patients pooled from A5170, A5197, A5068, A5024, ATCG371 Behzad Etemad et al, CROI 2015 Low grade viremia and CA-RNA are associated with time to viral rebound

SPARTAC trial Frater J. CROI 2015, Fidler IAS patients with primary HIV. Treatment interruption after 48 weeks 18 immunological and virological parameters At the time of treatment interruption: Total - but not integrated - DNA At the time of ART initiation (acute infection) CD4/CD8 ratio, CD4 count, plasma viral load CD8 CD38, CD8 PD1, CD8 HLA DR, CD4 HLA DR, CD8 Lag-3 and d-dimer

ANRS 116 SALTO Assoumou AIDS patients treated early in their course of HIV-infection. 12 variables tested Total-DNA at treatment interruption > 150 pmPBMC HR: 2.08

Panobinostat trial (Clear) Rasmussen et al HIV Lancet patients stopped cART after panobinostat Rx Measured every third day Association between the drop in Total-DNA during panobinostat Rx and time to rebound – but not Total-DNA at time of panobinostat Drop in DNA associated with NK-cell activity Olesen et al. J. Virol (in press)

CONCLUSION 2 PREDICTORS OF TIME TO REBOUND TOTAL HIV-DNA IN CD4+ CELLS CA-RNA Hs-VIRAL LOAD (single copy assay)

CONCLUSION 2 PREDICTORS OF TIME TO REBOUND TOTAL HIV-DNA IN CD4+ CELLS CA-RNA Hs-VIRAL LOAD (single copy assay) Probably a reflection of reservoir size and ”idle”-activity

CONCLUSION 2 PREDICTORS OF TIME TO REBOUND TOTAL HIV-DNA IN CD4+ CELLS CA-RNA Hs-VIRAL LOAD (single copy assay) Probably a reflection of reservoir size and ”idle”-activity

FUTURE RESEARCH Avoid expressing results as “associations” Use ROC Multiple comparisons Advanced statistical analyses are needed Algorithms (combination of parameters) Needs to be applied on other data set. Collect as much material and data as possible Collaborate

Thank you