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### What are the Functional Consequences of the Observed Sequence Selective Effect?

Sieve analysis of the Step trial: Evidence for vaccine-induced antigenic pressure on HIV

Allan deCamp and Peter Gilbert

Statistical Center for HIV/AIDS Research and Prevention

Fred Hutchinson Cancer Research Center

Conclusions of the Sieve Analysis

- The analysis of HIV sequences shows significant differences (vaccine vs placebo) in T cell epitope regions, suggesting that the vaccine induced immune responses that in turn put antigenic pressure on the virus
- The analysis of post-infection T cell responses shows significant anamnestic responses to MRKAd5 proteins deriving from vaccination and subsequent infection
- The analysis of acute VL data suggests that the vaccine transiently and modestly suppressed acute VL, which may have been caused by these anamnestic responses

Two Types of Potential Selective Effects for a T-Cell Based Vaccine

- Acquisition Sieve Effect
- The vaccine selectively blocks (or enhances) acquisition with specific HIV variants
- Post-Infection Selective Effect
- The vaccine drives HIV sequence evolution
- Longitudinal HIV sequences are needed to distinguish these two types of effects
- But at the moment we only have one time-point per subject

Assess the genetics of the HIVs that infected the trial participantsAre the viruses different depending on whether a subject got vaccine or placebo?

Sieve Analysis Plan

- Compare a subject’s sequences to the MRKAd5 insert sequence in 2 ways:
- Local: Evaluate each site and sets of sites separately (i.e., ‘antigen scanning’)
- Global: Summarize overall protein distance with a single

number

- Results shown by Morgane Rolland were Global

Antigen Scanning

- Test each amino acid (AA) site as a signature site:
- Signature site is a site where the frequency of AA mismatch to the MRKAd5 AA differs vaccine vs placebo
- Several statistical methods applied*

MRKAd5 sequence

Vaccinee observed sequences

Placebo observed sequences

*Including Gilbert, Wu, Jobes (2008, Biometrics)

AA Site Scanning: Departures From 0 Indicates Signature*

*Site where the frequency of AA mismatches to the MRKAd5 AA

differs in vaccine vs placebo sequences (q-value < 0.20)

8

In several A-list epitopes including position 8 in SLYNTVATL A*0201 A*0202 A*0205

LANL B

(N=324):

65% T

34% V

Gag 84 by A-List Epitope-Restricting Alleles

P-value

44%

56%

17% V 79% V

Other

A-List

Other

A-List

Placebo

Vaccine

potentially

have an allele

restricting an

epitope with

211-E

Position 9 of ETINEEAAEW A*2501

LANL B

(N=324):

93% E

6% D

protective epitope

(Walker and colleagues)

Position 1 of HTQGYFPDW B57

Only 1 B57+

vaccinee (H at

site 116)

LANL B

(N=824):

84% H

14% N

9-Mer Scanning

- For each 9-mer in Gag, Nef, and Pol, we tested for a difference (vaccine vs placebo) in protein distances to MRKAd5
- Found 4 regions with a q-value<0.2 with 3 of the 4 regions showing a greater distance to the vaccine in among the vaccinees.

* in this region vaccinee sequences are closer to the vaccine than placebo sequences

** this region overlaps the B-57 restricted HW9 epitope

Summary Measure Sieve Analysis

- Compute distance v from a subject’s set of sequences to the MRKAd5 sequence
- For simple and valid statistical tests, use one number per infected subject
- Wilcoxon tests of whether the distributions of summary measures differ between infected vaccine vs infected placebo

Complementary Distance Measures

1) Previous results presented by Morgane Rolland:

Distance = Average of protein distances across all epitopes that are predicted in both the MRKAd5 sequence and in a subject’s set of founder sequences

Distance x

MRKAd5

All epitopes identified in the cohort

Mismatch rate

2/6

X

X

2) New results presented next:

Percent Epitope Mismatch Distance = Estimated percentage of predicted epitopes in the MRKAd5 sequence that are mismatched in at least one of a subject’s observed sequences

Percent Epitope Mismatch: MRKAd5Gag/Pol/Nef

NetMHC

Epipred

The corresponding p-values based on the distances shown previously by Morgane Rolland were both significant (0.02 and 0.007 respectively)

Percent Epitope Mismatch: Gag, Pol, Nef

Epipred

Nef

Pol

Gag

NetMHC

Gag

0.005

Nef

Pol

The corresponding p-values based on the distances shown previously by Morgane Rolland were significant for Epipred/Nef (0.03) and NetMHC/Gag (<0.0001)

Percent Epitope Mismatch: HXB2non-insert proteins

Epipred

Env-Rev-Tat-Vif-Vpr-Vpu

NetMHC

Env-Rev-Tat-Vif-Vpr-Vpu

Summary of Results

- Local sieve analysis of ‘signature’ sites
- Statistical evidence for 10 AA signature sites in Gag, Nef, Pol; none in Env
- One particularly strong signature (Gag 84)
- Interpretation: There was greatest statistical power to detect site 84 as a signature, because of the large sample size (n=36 subjects with a restricting allele). Vaccine-induced selection pressure may have operated on many other sites, but there is low statistical power for sites in epitopes restricted by rare alleles.
- Global sieve analysis
- Statistical evidence that vaccinee sequences had greater epitope-based distances to MRKAd5 than placebo sequences for Gag and Nef (not Pol)

Challenges to Interpretation of Global Sieve Analysis

- While the results are statistically valid, what do they mean?
- The extent to which the global sequence differences are driven by a small number of epitope regions is not yet clear
- The interpretation of the sequence differences depends on the epitope prediction method (Epipred or NetMHC), which do different things
- Epipred predicts CTL epitopes based on all known epitope sequence motifs found in Brander’s A-list and IEDB. It uses 2-digit, 4-digit, and supertype HLA information
- NetMHC predicts CTL epitopes based on experimental binding affinity of peptides using 4-digit HLA information
- Not surprising that the results differ by algorithm

Functional Consequences: T-Cell Response

- Were there anamnestic responses to MRKAd5 proteins deriving from vaccination and subsequent infection?

Post-infection CD8 T-cell Responses to Proteins Contained in the Vaccine are Stronger in Vaccinees*

p = 0.021

positive responses

negative responses

% CD8 T cells producing IFN-g and/or IL-2

Gag/Pol/Nef

All other proteins

Plac

Vacc

Plac

Vacc

*Nicole Frahm

presented

these data

at AIDS

Vaccine 2009

- CD8 T-cell responses were measured by ICS in 87 participants (33 placebo and 54 vaccine recipients)
- Samples were obtained 1 week (8 participants) and 2 weeks (79 participants) post HIV diagnosis

Functional Consequences: Viral Load

- Did the boosted vaccine-induced T-cells suppress viral load?
- At set-point: No (except possibly for some HLA alleles)
- During acute infection: Possibly

Acute Viral Load

Acute Viral Loads

N = 29 infected subjects

have acute-phase VL

(out of 87 cases)

Acute = sample that is

HIV RNA+ and

HIV Ab Negative

(ELISA Neg and

WB Neg or Indeterm)

(n = 15) (n = 14)

Estimated mean difference:

0.27 (95% CI -0.28 to 0.83)

*Analysis by Holly Janes

Combined Viral Load and Signature Analysis

- The antigenic selection pressure may have caused a transient suppression of viral load, with the suppressive effect lost within weeks or months after HIV acquisition
- Approach
- At the identified signature sites, do subjects with matched signature sequences have lower acute VL vaccine vs placebo?

Viral Load Vaccine vs Placebo for Subjects with Insert Matched Residue at Nef 116

- Additional sequence data:
- Mullins lab measuring HIV sequences at 2-3 time-points over the first 12 months of infection
- Will allow direct assessment of whether and how vaccination alters HIV evolution and in particular the pattern or rate of escape mutations
- Additional T cell response data:
- McElrath lab is measuring post-infection T cell responses to an array of peptide targets, which will allow evaluation of whether vaccination accelerated the development of T cell responses
- Step ancillary studies

Conclusions (Sequence Data)

- The analysis of HIV sequences shows significant differences in breakthrough viruses for vaccine vs placebo recipients
- The nature of the differences supports that the vaccine selected against viruses with certain amino acids in T cell epitopes, suggesting that the vaccine induced immune responses that put antigenic pressure on the virus
- While the MRKAd5 vaccine is not clinically useful, this result may be a milestone in T-cell based vaccine research, providing guidance for the development of improved T-cell based vaccines

Conclusions (Acute Viral Load Data)

- The analysis of acute VL data suggests (nonsignificant trend) that the vaccine transiently and modestly suppressed acute VL
- The sequence analysis suggests the hypothesis that this suppression was due to a vaccine-induced acceleration of T cell evolution

Conclusions (T Cell Response Data)

- The analysis of post-infection T cell responses shows significant anamnestic responses to MRKAd5 proteins deriving from vaccination and subsequent infection, which is consistent with a transient vaccine-induced suppression of VL
- However, few vaccinees had measurable pre-infection T cell responses to the protein regions or signature sites that contributed most to the sequence differences, raising open questions
- The forthcoming additional sequence data and T cell response data are expected to provide additional insights into the vaccine effects

Acknowledgments

- McCutchan lab
- Francine McCutchan*
- Sodsai Tovanabutra
- Eric Sanders-Buell
- Meera Bose
- Andrea Bradfield
- Annemarie O’Sullivan
- Jacqueline Crossler
- Teresa Jones
- Marty Nau
- Jerome Kim

- Merck
- Danilo Casimiro
- Michael Robertson
- HVTN
- Susan Buchbinder
- Ann Duerr
- John Hural
- David Chambliss
- Patricia Dodd
- Nicole Frahm
- David Friedrich
- Dan Geraghty
- Julie McElrath
- Larry Corey

- Mullins lab
- Dana Raugi
- Stefanie Sorensen
- Jill Stoddard
- Kim Wong
- Hong Zhao
- Laura Heath
- Morgane Rolland
- Jim Mullins
- SCHARP
- Craig Magaret
- Holly Janes
- Tomer Hertz
- Fusheng Li
- Steve Self

- Plus thanks to David Nickle & David Heckerman
- *Now at the Gates Foundation

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