Comparison of mRNA and protein measures of cytokines following vaccination with human papillomavirus-16 L1 virus-like particles

TLDR: The degree of correlation between gene expression and protein levels varied among different cytokines/chemokines, and researchers should be cautious when using mRNA expression array results as a proxy for protein levels using existing technologies.

Abstract: Background: mRNA expression signatures are frequently used as surrogate measures of cellular function and pathway changes. Few studies have directly compared results obtained using gene expression and multiplex protein assays for corresponding gene products. Methods: We used data available from a clinical trial of a human papillomavirus-16 vaccine that tracked gene expression and cytokine/chemokine production by peripheral blood mononuclear cells stimulated in culture with various antigens to evaluate the degree to which gene expression levels reflect observed levels of cytokines/chemokines. Twenty-six women enrolled in a phase II clinical trial of a human papillomavirus-16 vaccine were evaluated for gene expression (using the Affymetrix Human Genome Focus Array) and cytokine/chemokine levels (using a bead-based 22-plex cytokine assay developed by Linco Research, Inc.) before and after vaccination. Results: Our results suggest the presence of a wide range of correlations between mRNA expression and secreted protein levels. The strongest correlation was observed for IFN-γ ( R = 0.90 overall levels; R = 0.69 when vaccine induced changes were evaluated). More modest overall correlations ranging from 0.40 to 0.80 were observed for MIP1A, IP10, TNF-α, MCP1, IL-2, GM-CSF, IL-5, RANTES, and IL-8. Weaker or no correlation was observed between gene expression and protein levels for the remaining cytokines/chemokines evaluated. Conclusion: The degree of correlation between gene expression and protein levels varied among different cytokines/chemokines. Impact: Researchers should be cautious when using mRNA expression array results as a proxy for protein levels using existing technologies. Cancer Epidemiol Biomarkers Prev; 19(4); 978–81. ©2010 AACR.