Single cell profiling reveals modulatory effects of immunotherapeutic RNA approaches in cancer and autoimmune disease models
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Abstract
This work focused on establishing a single-cell RNA sequencing (scRNA-seq) pipeline for comprehensive immune cell analysis to reveal cell types and states as well as to dissect the gene expression (GE) and regulatory relationships between genes and cells in health and disease. Our scRNA-seq pipeline is based on the Chromium Controller, a device capturing and amplifying a minute amount of RNA and analysis tools for clustering (Seurat) and enriched pathways or genes (Cluster Profiler and gene set variation analysis). In this thesis, researchers used the pipeline to investigate the effects of immunotherapeutic RNA approaches in cancer and autoimmune disease models.
Chapter one demonstrates the pipeline's ability to identify cell types and the robustness of the protocol through the consistent gene expression profiles of PBMC samples from the same donors. Comparisons between 3'gene expression protocol (3'GE) and 5'GE protocols showed no significant differences in cell composition and cell-type-specific genes. Therefore, single cell analysis pipeline based on 3’GE was applied to study transcriptional dynamics of immune cells in disease models for cancer and multiple sclerosis (MS) upon RNA vaccination in three different experimental settings:
Chapter two describes the studies related to the adjuvant effect of RNA-Lipoplex (LPX) vaccination encoding the reporter gene enhanced green fluorescent protein (EGFP) on murine splenocytes, indicating an increase in the frequency of B cells and monocyte/granulocyte fraction. This led to the triggering of chemokines and inflammatory cytokines including upregulation of genes involved in interferon alpha (IFNα) and beta (INFβ) response, suggesting a heightened immune response and confirming the adjuvant effect of RNA by modulating innate immune system.
Chapter three outlines the impact of autoantigen-encoding non-immunogenic RNA-LPX vaccination in experimental autoimmune encephalomyelitis (EAE), a mouse model for MS. A successful tolerance induction in EAE sick mice was observed in form of high effector regulatory T (Treg) cell frequencies using a myelin oligodendrocyte glycoprotein peptide incorporated with 1-methylpseudouridine (MOG35_55_m1Ѱ). The main investigation for this thesis chapter was further to dissect the effect of MOG35-55_U in comparison to MOG35-55_m1Ѱ and irrelevant m1Ψ and to study functional differences with respect to inflammatory and immunosuppressive properties of the present CD4+ T cell subpopulations. MOG35-55_U in comparison to MOG35-55_ m1Ѱ led to downregulation of cell cycle genes and resulted into less cytotoxic signature but therefore higher level of stress was observed. MOG35_55_U as a more immunogenic mRNA construct did not lead to an enrichment of pathways demonstrating a (stronger) tolerance induction in EAE sick mice.
Lastly, chapter four illustrates the therapeutic potential of liposomally-formulated RNA encoding the modified IL2var alone or in combination with a monoclonal antibody against programmed cell death 1 (aPD1) in a MC38 tumor mouse model to assess the immune response in CD45+ cells. The treatment demonstrated increased tumor infiltrating lymphocytes (TILs) frequency, a strong effector phenotype, reduction of exhaustion markers and an increased expression of transcription factors, suggesting a promising therapeutic cancer vaccine potential.
In conclusion, the scRNA-seq pipeline developed in this thesis allowed in-depth analysis of individual cell subsets at single cell level and demonstrated the potential of various RNA-based treatments in cancer and autoimmune disease models. Further research is suggested to fully exploit the pipeline's capabilities and enhance therapeutic strategies.