bioRxivImmunologyPreprint
Hiltonol and Protamine-RNA stimulation induce an immune-activating transcriptome profile in cDC1s
Georgina Flórez‐GrauiD, Till S. M. MathaniD, Mihaela MihaylovaiD, Tom G.M. van OorschotiD, Gerty SchreibeltiD, David SanchoiD, Ignacio MeleroiD, Carl Gustav FigdoriD, I. Jolanda M. de VriesiD, Johannes C. TextoriD
Abstract
Ex-vivo stimulation of dendritic cells (DCs) is a critical step in DC-based cancer immunotherapies. In humans, conventional type 1 dendritic cells (cDC1s) are a rare myeloid dendritic cell (mDC) subset that express BDCA-3 (CD141). cDC1s promote CD8+ T cell cross-priming against tumor antigens and are therefore being explored for use in immunotherapy. We evaluated the impact of ex-vivo stimulation on human peripheral blood cDC1s. In contrast to routine evaluation, which focuses on pre-defined surface maturation markers or soluble factors released from the activated cells, we investigated the impact of stimulation on the transcriptome using both RNA-sequencing (RNA-seq) and microarrays. Specifically, we analyzed the mRNA of cDC1s upon activation with two clinical-grade adjuvants, Hiltonol (poly IC, a TLR3 ligand) and protamine-stabilized RNA (pRNA, a TLR7/8 ligand) compared to unstimulated controls. Both RNA-seq and microarray analysis showed profound and similar effects of both Hiltonol and pRNA on the transcriptome of cDC1s. A gene ontology (GO) analysis suggested that these changes were mainly related to activation and maturation pathways, including induction of type-I interferon (IFN) and interleukin (IL)-12 transcription, while pathways related to adverse effects or cell damage did not appear to be affected. Combination of both reagents did not appear to have a synergistic effect, as the transcriptome changes were similar to those induced by each stimulus alone. Together, our results indicate that both adjuvants have comparable effects on cDC1 maturation within an immunogenic short-term culture as performed in immunotherapy.
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: genetic perturbation / CRISPR
- Citations
- 0
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