TheranosticsSystems BiologyPeer-reviewed journal article
Network and systems based re-engineering of dendritic cells with non-coding RNAs forcancer immunotherapy
Xin LaiiD, Florian S. Dreyer, Martina CantoneiD, Martin EberhardtiD, Kerstin F. Gerer, Tanushree Jaitly, Steffen UebeiD, Christopher LischeriD, Arif Bülent EkiciiD, Jürgen WittmanniD, Hans‐Martin JäckiD, Niels SchaftiD, Jan DörrieiD, Julio VeraiD
Abstract
Dendritic cells (DCs) are professional antigen-presenting cells that induce and regulate adaptive immunity by presenting antigens to T cells. Due to their coordinative role in adaptive immune responses, DCs have been used as cell-based therapeutic vaccination against cancer. The capacity of DCs to induce a therapeutic immune response can be enhanced by re-wiring of cellular signalling pathways with microRNAs (miRNAs). Since the activation and maturation of DCs is controlled by an interconnected signalling network, we deploy an approach that combines RNA sequencing data and systems biology methods to delineate miRNA-based strategies that enhance DC-elicited immune responses. Through RNA sequencing of IKK{beta}-matured DCs that are currently being tested in a clinical trial on therapeutic anti-cancer vaccination, we identified 44 differentially expressed miRNAs. According to a network analysis, most of these miRNAs regulate targets that are linked to immune pathways, such as cytokine and interleukin signalling. We employed a network topology-oriented scoring model to rank the miRNAs, analysed their impact on immunogenic potency of DCs, and identified dozens of promising miRNA candidates with miR-15a and miR-16 as the top ones. The results of our analysis are incorporated in a database which constitutes a tool to identify DC-relevant miRNA-gene interactions with therapeutic potential (www.synmirapy.net/dc-optimization).
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 14
- FWCI
- 0.70
- Field percentile
- top 33%
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