Oral Abstract Session 01 - Global HIV Vaccine Enterprise

Topic 11: T Cell Immunity
P11.37
Identification of HIV-1-Specific Regulatory T Cells
Using HLA-Class-II Tetramers
M. Angin 1 , P.L. Klarenbeek 2 , M. King 1 , K.W. Wucherpfennig 3 ,
M.M. Addo 1
1 Ragon Institute of MGH, MIT and Harvard, Boston, MA, USA;
2 Brigham and Women’s Hospital, Boston, MA, USA; 3 Dana-
Farber Cancer Institute, Boston, MA, USA
Background: Regulatory T cells (Tregs) are potent immune
modulators whose role in HIV-1 immuno-pathogenesis remains
inadequately understood. While “bulk” Treg populations have
been studied extensively in the context of HIV-1 infection, no
reliable data is available on HIV-1 specificity of Tregs and induction
of these cells in infected individuals or vaccine recipients.
Part of the challenge in detecting antigen-specific Treg
populations relates to the limited availability of visualization
tools and the scarcity of the overall human Treg population
-representing roughly 5% of CD4+ T cells with absolute Treg
numbers further decreasing during HIV-1 disease progression.
Methods: In order to screen for HIV-1 specific regulatory
T cell populations, we first flow-sorted and expanded
CD4+CD25+CD127low Tregs ex vivo from HLA DRB1*0401
expressing HIV-1 infected individuals. Expanded Tregs underwent
analysis of function, phenotype, deep TCR sequencing and
epigenetic analysis. Treg lines were then stained with HLA class II
tetramers specific for HIV-p24-gag and appropriate controls.
Results: Expanded Tregs were highly suppressive and displayed
the phenotype of “activated” Tregs. Tregs were highly
demethylated at the TSDR as shown by epigenetic analysis
of the FOXP3 gene and showed an unskewed TCR repertoire
compared to unexpanded ex vivo-sorted Tregs. Staining with
HLA-class-II-tetramers specific for the HIV-p24-Gag epitope
DRFYKTLRAEQASQ revealed a detectable response in one
subject (an individual with chronic untreated progressive HIV-1
infection), at a frequency of 0.19% of CD4+ T cells in the nonenriched
Treg culture. After tetramer-positive T cell enrichment,
this frequency was increased to 6.14%.
Conclusion: Our data represent the first identification of HIV-1epitope-specific
Tregs in HIV-1 infected individuals. Identification
and further functional characterization of HIV-1 specific Tregs will
provide important insight for the evaluation of vaccine strategies
as these may lead to induction of not only HIV-1-specific effector
populations but also HIV-1-specific regulatory T cells, which may
negatively impact vaccine immunogenicity.
P11.38
AIDS Vaccine 2012
Posters
A High-Dimensional Immune Monitoring Model
of HIV-1-Specific CD8 T Cell Responses Accurately
Identifies Subjects Achieving Spontaneous Viral
Control
Z.M. Ndhlovu 1 , L. Chibnik 2 , J. Proudfoot 1 , S. Vine 1 , A. McMullen 1 ,
K. Cesa 1 , F. Porichis 1 , D. Alvino 1 , A. Piechocka-Trocha 1 ,
P. De Jager 3 , B.D. Walker 1 , D. Kaufmann 1
1 Ragon Institute of MGH, MIT and Harvard, Charlestown, MA,
USA; 2 Brigham and Women’s Hospital & Harvard Medical
school, Boston, MA, USA; 3 Brigham and Women’s Hospital &
Harvard Medical School, Boston, MA, USA
Background: The development of immune monitoring models
to determine HIV-1 vaccine efficacy is a major challenge. HIV-
1-specific CD8 T cells likely play a critical role in individuals
achieving spontaneous viral control (HIV-1 controllers) and will
be important in immune interventions. However, no single CD8 T
cell function is uniquely associated with controller status.
Methods: Here we describe the building of immune monitoring
models based on inter- and intra-donor analysis of HIV-1-specific
CD8 T cell proliferation and cytokine secretion assessed at
different time points after antigen stimulation. The discovery
data set used to build a palette of immune monitoring models
of HIV-1-specific CD8 T cell functions was generated on 26
controllers, 15 progressors and 23 ART-treated subjects. An
independent cohort of 10 controllers and 10 progressors was
investigated to validate our results. We used Area Under the
Receiving Operating Characteristic curves (AUC) to assess the
ability of individual variables to differentiate between controllers
and non-controllers.
Results: Our analyses identified links between HIV-1-specific
CD8 T functions, HLA-I alleles, and disease stage. The best
accuracy (AUC) values were observed for proliferation.
Early (6h) IL-2 secretion and slopes of TNF-α, IL-2 and IFN-γ
production also contributed to the models whereas gender and
age had no discriminatory value. A model incorporating five
HIV-1-specific CD8 T cell functions achieved 90% accuracy in
the discovery cohort on which it was trained, and was able to
accurately discriminate controllers from non-controllers in the
validation cohort.
Conclusion: Our multidimensional modeling approach shows
that integration of different dimensions of data leverages
independent associations and discriminates much better than
any one measure. This modeling approach is amenable to
incremental incorporation of new knowledge to build evolving
flexible tools that are usable in translational clinical research
and thus, has important applications in predictive model
development and immune monitoring of HIV-1 vaccine trials.
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POSTERS