Identifying gnostic predictors of the vaccine response.
Molecular predictors of the response to vaccination could transform vaccine development. They would allow larger numbers of vaccine candidates to be rapidly screened, shortening the development time for new vaccines. Gene-expression based predictors of vaccine response have shown early promise. However, a limitation of gene-expression based predictors is that they often fail to reveal the mechanistic basis of their ability to classify response. Linking predictive signatures to the function of their component genes would advance basic understanding of vaccine immunity and also improve the robustness of vaccine prediction. New analytic tools now allow more biological meaning to be extracted from predictive signatures. Functional genomic approaches to perturb gene expression in mammalian cells permit the function of predictive genes to be surveyed in highly parallel experiments. The challenge for vaccinologists is therefore to use these tools to embed mechanistic insights into predictors of vaccine response.
Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA. nicholas_haining@dfci.harvard.edu
W Nicholas
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Haining
Bali
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Pulendran
D000818:Animals; D015195:Drug Design; D015870:Gene Expression; D023281:Genomics; D006801:Humans; D014612:Vaccines / Q000235:genetics / Q000276:immunology*
D014612:Vaccines