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
E-mail: larsoest@rm.dk
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Disclosures
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Gilead
Pfizer
Sanofi-Pasteur
Bionor
ViiV
Roche
MSD
BMS
Janssen
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Definition of a biomarker
A biological analysis
that predicts
a clinically relevant outcome
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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”.
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What are clinical relevant outcomes in cure research ?
Having undetectable viral load is the best predictor of
“no progress” and “no transmission”
But without any “pills” the virus rebound – so the clinical relevant goal of
any cure intervention is to delay the time to rebound
With courtesy of Jonathan Li
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It is difficult to make predictions
- especially about the future !
Piet Hein. Danish author (1905-96)
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BUT – we can. However, we need to know the
exact outcome of an intervention
(i.e. time to viral rebound)
Intervention
Possible biomarker
Outcome
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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
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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
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AVAILABLE DATA
WHAT ARE THE DATA ON POTENTIAL
BIOMARKERS FROM STUDIES LOOKING
AT TIME TO VIRAL REBOUND AFTER
TREATMENT INTERRUPTIONS
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ATCG (compiled data)
ANRS
SPARTAC
CLEAR STUDY
(Biomarkers associated with elite controllers)
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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
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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
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SPARTAC trial
47 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
Frater J. CROI 2015, Fidler IAS 2015
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ANRS 116 SALTO
Assoumou AIDS 2015
95 patients treated early in their
course of HIV-infection.
12 variables tested
Total-DNA at treatment interruption > 150 pmPBMC HR: 2.08
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Panobinostat trial (Clear)
Rasmussen et al HIV Lancet 2014
9 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)
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CONCLUSION 2
PREDICTORS OF TIME TO REBOUND
• TOTAL HIV-DNA IN CD4+ CELLS
• CA-RNA
• Hs-VIRAL LOAD (single copy assay)
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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
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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
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FUTURE RESEARCH
Multiple comparisons
• Advanced statistical analyses are needed
Algorithms (combination of parameters)
• Needs to be applied on other data set.
Avoid expressing results as “associations”
• Use ROC
Collect as much material and data as possible
• Collaborate
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Thank you
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