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HLA-driven optimization of an HIV vaccine immunogen
Conference presentation   Open access

HLA-driven optimization of an HIV vaccine immunogen

V. Jojic, N. Jojic, D. Heckerman, C. Kadie, C. Meek, C. Moore, M. John and S. Mallal
12th Conference on Retroviruses and Opportunistic Infections (Hynes Convention Center, Boston, MA, 22/02/2005–25/02/2005)
2005
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Abstract

Background: HIV diversity has been driven in large part by the intense selective pressure of HLA-restricted immune responses and is a significant challenge in HIV vaccine design. Sites of HLA-associated polymorphisms indicate potential immunogenic peptides that should be incorporated into an HIV vaccine. Method: Full-length (pretreatment) HIV sequencing and high-resolution HLA-A, -B, and -C genotyping was undertaken on 245 individuals in the Western Australian HIV Cohort Study. We determined statistically significant associations between polymorphisms in HIV sequences and HLA genotypes. Given these HLA associations we consider alternative measures of protection on the basis of the match between a viral peptide sequence and a corresponding segment of the vaccine. The measure is defined for all overlapping HIV peptides in the dataset. Each peptide contains a putative epitope and its associated flanking region. The vaccine is said to protect against a peptide sequence if the sites of HLA association in both the peptide sequence and the corresponding segment of the vaccine have nonescaped amino acids, and one of the following three criteria hold: (1), "no play"— the remaining sites in the peptide sequence and corresponding segment of the vaccine match exactly, (2), "mid-play"— the remaining sites in the sequence and vaccine differ only by conservative amino-acid substitutions, and (3) "full-play"—the remaining sites in the sequence and vaccine need have no relationship.The three criteria represent different assumptions about the degree to which T cells cross-react. An optimal vaccine immunogen of a given length is the one that contains the largest number of (possibly overlapping) protected against peptides. We provide a general machine-learning approach to optimization of such immunogens. Results: We optimized vaccines of length up to 2000 aa. The predicted efficacy of the optimized vaccine immunogens depends considerably on which criterion is used. For instance, an optimized vaccine immunogen of length 1300aa can protect against all peptides in the data under the full-play assumption, compared with 80% of all peptides under the mid-play assumption and 65% under the no-play assumption. Conclusion: These data demonstrate a novel, rational approach to optimizing the immunogenicity of an HIV vaccine against diverse circulating viruses in a human population, guided by knowledge of the population HLA.

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