Characterization of human immune phenotypes using a novel transcriptome analysis approach (IRM6P.656)

To test the hypothesis that complex immune phenotypes can be defined by stable gene expression profiles we are using a RNAseq-based transcriptome analysis to relate phenotypes of activated peripheral blood CD4 + cells from healthy subjects and stage IV melanoma patients to their freshly-isolated counterparts. We have defined molecular immune response signatures (MIRS) containing genes that consistently differentiate individuals from one another. Two different phenotypic groups are defined using this approach, both of which are mathematically distinct from randomly-selected groups. First, a MIRS generated using healthy donor T cells stimulated with α-CD3/CD28 beads defines a distinct response phenotype and successfully predicts 17 independent healthy subject and melanoma patient responses, demonstrating the predictive capability of the approach. Second, our comparison of melanoma patient signatures with those of healthy subjects revealed a group of healthy individuals with distinct expression signatures that did not cluster with those of any of the melanoma patients. These results indicate that our RNAseq-based transcriptome analysis has the potential to identify phenotypic groups as well as gene sets that have response-predictive capabilities. Our work has both discovery and translational implications, as our approach can be used to investigate complex genetic contributions to immune responses and predict how individual patients will respond to therapeutic interventions.