We performed targeted gene expression profiling on moDCs electroporated with mRNA encoding green fluorescent protein (GFP), TriMix mRNA (CD40L, caTLR4 & CD70) and TetraMix mRNA (CD40L, caTLR4, IFN-γ & dIL10Rα) using the Nanostring platform. In all conditions, we electroporated 4x10⁶ moDCs with an equal amount of total mRNA (concentration in electroporation medium: 100 μg/ml). We initiated the transcriptome analysis 24 hours after electroporation, as translation of the delivered mRNA has taken place at that time, as evidenced by expression of GFP in moDCs electroporated with GFP mRNA ( Figures 1A, B ). We first assessed the purity of moDCs before electroporation and before transcriptome analysis using flow cytometry, evaluating the expression of CD11c, CD14 (monocytes), CD3 (T cells), CD19 (B cells) and CD56 (NK cells) on the cells ( Figure 1C ).

A Principal Component Analysis (PCA) was performed for exploration of the targeted transcriptome data. The first principal component explains 57% of the overall variance, clearly separating the delivery of GFP, TriMix and TetraMix mRNA to moDCs. This PCA thus indicates that the delivery of the different mRNA’s induces distinct transcriptional profiles ( Figure 2A ). Next, we performed gene ontology analysis to gain a broader understanding of the transcriptional program initiated in moDCs by TriMix versus TetraMix mRNA. We observed that changes induced by TriMix mRNA could be defined as a response to bacteria, including changes in the expression of genes involved in sensing lipopolysaccharide (LPS) and the attraction of leukocytes ( Figure 2B ). In contrast, we observed that the changes initiated by TetraMix mRNA in moDCs were characteristic of viral defense response, as evidenced by the upregulation of many IFN-stimulated genes (ISGs) coinciding with changes in the expression of genes involved in cytokine regulation and production ( Figure 2C ).

To analyze the transcriptome in more detail, differential expression of genes between moDCs electroporated with either TriMix or TetraMix mRNA and moDCs electroporated with GFP was analyzed and visualized in volcano plots. A total of 258 genes were differentially expressed between TriMixDCs and moDCs electroporated with GFP ( Figure 3A ; Table S1 ). TetraMixDCs showed 343 genes that were differentially expressed compared to moDCs electroporated with GFP ( Figure 3B ; Table S2 ). Moreover, a volcano plot was generated to scrutinize transcriptomic changes between TriMixDCs and TetraMixDCs indicating 105 differentially expressed genes ( Figure 3C ; Table S3 ). When observing the transcriptional patterns between all three conditions we found that 328 and 332 genes were up- and downregulated, respectively, in TriMixDCs and TetraMixDCs compared to moDCs electroporated with GFP mRNA. A total of 110 genes showed an opposite gene expression shift between the TriMixDCs and TetraMixDCs compared to moDCs modified to express GFP ( Figure 3D ).

Based on literature, we selected four gene groups that could be considered determinants of the immunogenicity of DCs. These were plotted in heatmaps to compare GFP, TriMix or TetraMix mRNA electroporated moDCs ( Figure 3E ). The selected genes encode cytokines (IL-6, IL-10, IL-12, IL-15 and IFN-γ), proteins involved in chemotaxis (CXCL9, CXCL10, CXCL16, CCL19, CCR7 and ICAM1), in co-stimulation (RELB, CD40, CD70, CD80, CD83 and CD86) or in co-inhibition (CD273 [PD-L2], CD274 [PD-L1], CD95 [FAS], CD154 [CTLA-4], CD200 [OX-2] and SOCS1) (11, 47). It illustrates that TetraMixDCs showed increased expression of genes encoding cytokines and proteins driving cell migration and T-cell co-stimulation compared to TriMixDCs ( Figure 3E ). We further observed that genes encoding proteins that could hamper T-cell activation were increased in TetraMixDCs, though the difference in expression compared to TriMixDCs was less evident ( Figure 3E ).

The phenotype of TriMixDCs or TetraMixDCs was evaluated to validate the findings of the transcriptome analysis, comparing to the phenotype of moDCs electroporated with mRNA encoding a truncated variant of nerve growth factor receptor (ControlDCs), which serves as a negative control.

We observed that expression of the inhibitory ligand PD-L1 was significantly enhanced compared to ControlDCs on TriMixDCs yet not TetraMixDCs ( Figure 4A ). Furthermore, we observed that the C-C chemokine receptor 7 (CCR7), which is key for the migration of DCs to the T-cell zone of lymphoid organs, was significantly upregulated only on TetraMixDCs ( Figure 4B ). We observed a decreased expression of human leukocyte antigen (HLA) class I protein, which reached significance for HLA-I in TetraMixDCs ( Figure 4C ). The targeted transcriptome analysis showed no significant difference for HLA-I genes, such as HLA-A, HLA-B and HLA-C. We observed a downregulation from HLA class II proteins (HLA -DPA1, -DPB1, -DRB3, -DRB4, -DMA, -DMB, -DRA) in transcriptome analysis ( Tables S1 , S2 ), but no significant difference from moDC phenotype screening ( Figure 4D ). Confirming that the transcriptome analysis, in which we observed that expression of co-stimulatory proteins such as CD40, CD80 and CD83 on the surface of TetraMixDCs significantly increased compared to both ControlDCs and TriMixDCs ( Figures 4E–G ). This finding was not extended to the expression of CD86. We observed a significant decrease in CD86 expression on TriMixDCs. As a result, CD86 expression was significantly different compared to TetraMixDCs mRNA, which showed similarly high levels of CD86 expression as ControlDCs ( Figure 4H ).

To support our claim that TetraMixDCs induce production of IL-12 and to validate the findings of the transcriptomic changes, we measured the levels of IL-12p70 and IL-10 secretion in the supernatants of moDCs, both between 0-24h and 24-48h post-electroporation with TriMix or TetraMix mRNA.

We expected a high amount of secreted IL-12p70 as IL-12p35 (IL12A) is in the top ten and IL12p40 (IL12B) in the top 25 upregulated genes after comparing moDCs electroporated with GFP or TetraMix mRNA ( Table S2 ). IL12A was the most significant upregulated gene by comparing TetraMixDCs and TriMixDCs whereas IL12B is in the top ten ( Figure 3C ; Table S3 ). We observed a significant increase of IL-12p70 secretion by TetraMixDCs at both time points compared to the moDCs electroporated with control mRNA ( Figure 5A ). Between 24h and 48h, a higher IL-12 secretion level was observed for TetraMixDCs compared to TriMix-DCs ( Figure 5B ), validating the differential gene expression.

Based on the transcriptome data, we expect a high secretion of IL-10 by TriMixDCs and TetraMixDCs as it can be found in the top ten of the most upregulated genes ( Tables S1 , S2 ). Indeed, both TriMixDCs and TetraMixDCs show significant secretion of IL-10 after 24h and between 24h and 48h compared with the moDCs electroporated with control mRNA ( Figures 5A, B ). Next, we compared the IL-10/IL-12 ratio; showing that this ratio is significantly lower between 24h and 48h for TetraMixDCs compared to TriMixDCs.

As TriMixDCs and TetraMixDCs showed mature phenotypes and activated cytokine production, we investigated whether these moDCs could induce tumor antigen-specific CD8⁺ T cells. Therefore, moDCs from HLA-A2⁺ healthy donors were co-electroporated with Melan-A/MART-1 (A27L) mRNA and either control mRNA (tNGFR) or, TetraMix and TriMix mRNA. Co-cultures were set up with autologous purified CD8⁺ T cells at a moDC to T cell ratio of 1 to 10 and re-stimulation was performed twice. The purity of CD8⁺ T cells after cell sorting was assessed by flow cytometry ( Figures 6A, B ). After 3 stimulation rounds, the percentage of dextramer positive, Melan-A/MART-1 (A27L)-specific CD8⁺ T cells were determined ( Figure 6C ). We observed that TetraMixDCs were the most potent in activating Melan-A/MART-1 (A27L)-specific CD8⁺ T cells compared to TriMixDCs and moDCs electroporated with control mRNA ( Figure 6D ).

We investigated if TetraMixDCs could prime CD8⁺ T_N cells and shift them into activated cytotoxic and memory T cells. CD8⁺ T_N cells, defined as CD45RA⁺CD62L⁺CD45RO^-CD95^-, were obtained with a purity of approximately 90% ( Figures 7A, B ). These were co-cultured with moDCs that were electroporated with Melan-A/MART-1 (A27L) mRNA and control mRNA (tNGFR), TriMix or TetraMix mRNA at a moDC to T cell ratio of 1 to 10. Three rounds of stimulation at a weekly interval were performed after which the stimulated CD8⁺ T cells were analyzed. We observed that both antigen presenting TriMixDCs and TetraMixDCs showed an increased capacity to activate Melan-A/MART-1 (A27L)-specific CD8⁺ T cells compared to antigen presenting moDCs co-electroporated with control mRNA ( Figure 7C ).

Next we verified the activation status of the CD8⁺ T cells through screening for known T cell activation markers: CD25, CD69, OX40 and CD137. All activation markers were upregulated for T cells stimulated with TriMixDCs and TetraMixDCs. We also observed an up-regulation of the inhibitory checkpoint proteins PD-1 and CTLA-4 in conditions where CD8⁺ T cells were stimulated with TriMixDCs or TetraMixDCs ( Figure 7D ).

Moreover, we evaluated the phenotype of the stimulated T cells by monitoring the following CD8⁺ T cells subsets (48, 49): T_N cells (CD45RA⁺CD62L⁺CD45RO^-CD95^-), T_SCM cells (CD45RA⁺CD45RO^-CD62L⁺CD95⁺), T_CM cells (CD45RA^-CD45RO⁺CD62L⁺CD95⁺), effector memory T cells (T_EM; CD45RA^-CD45RO⁺CD62L^-CD95⁺) and effector memory re-expressing CD45RA T cells (T_EMRA; CD45RA⁺CD45RO^-CD62L^-CD95⁺). We observe a gradual differentiation from CD8⁺ T_N cells to T_SCM cells, T_EM and T_CM cells in the TriMixDC and TetraMixDC conditions ( Figure 7E ).

Finally, we show that the stimulated CD8⁺ T cells were able to kill GFP⁺ 624-MEL cells, in an in vitro killing assay. The 624-MEL cell line is HLA-A2⁺ and expresses the Melan-A/MART-1 (A27L) antigen. The 3D tumor models were co-cultured with the stimulated CD8⁺ T cells in the presence of IL-15. We demonstrated that T cells stimulated with TriMixDCs and TetraMixDCs expressing Melan-A/MART-1 (A27L) could kill 624-MEL cells and inhibit tumor growth, which was in contrast to CD8⁺ T cells stimulated with moDCs co-electroporated with MelanA/MART-1 (A27L) mRNA and control mRNA ( Figure 7F ).

HLA-A*0201^POS 624-MEL were provided by S.L. Topalian (National Cancer Insitute, Baltimore, MD, USA) and were cultured in Roswell Park Memorial Institute (RPMI) 1640 medium (Sigma-Aldrich) supplemented with 10% fetal clone I serum (Thermo Scientific), 2mM L-glutamine, 100 U/ml penicillin, 100 µg/ml streptomycin, 1 mM sodium pyruvate, and nonessential amino acids (Sigma-Aldrich). The 624-MEL cells were transduced to have a high GFP expression as described in Awad et al (60).

Generation of moDCs was performed according to Good Manufacturing Practice (GMP). On day 0, a leukapheresis was performed on healthy donors at the Hematology unit of the university hospital in Brussels (UZ Brussels, Belgium) using an apheresis device (Spectra Optia® apheresis system, TerumoBCT) to collect the peripheral blood mononuclear cell (PBMC) fraction. The leukapheresis product was further processed at the DC-manufacturing unit of the Laboratory for Molecular and Cellular Therapy at the Vrije Universiteit Brussel (LMCT-VUB, Brussels, Belgium). An elutriation procedure (Elutra® Cell Separation System Elutra, TerumoBCT) was performed to enrich monocytes. These monocytes were cultured in a cell culture bag with DC-Medium (CellGenix®), supplemented with human serum albumin (1%, CAF-DCF) and cytokines: 500IU/mL recombinant IL-4 (CellGenix®) and 1000IU/mL recombinant granulocyte macrophage-colony-stimulating factor (Leukine®, Sanofi). Differentiation from monocyte to moDCs was allowed for 60-72 hours by incubating the cells at 37°C and 5% CO₂. The differentiated moDCs were harvested and, after count and viability assessment, cryopreserved in 5% dimethyl sulfoxide (DMSO) cryopreservation medium (CryoStor® CS5, Biolife Solutions). Cryovials were immediately transferred into a freezing container (Corning® CoolCell^TM Freezing container) and placed at -80°C. After overnight incubation at -80°C, vials were stored in the vapor phase of a liquid nitrogen container. From the same leukapheresis material, we stored the monocyte-depleted PBMC fraction as previously described (60).

Plasmid DNA was generated using the in-house developed plasmid pLMCT (61). gBlocks for the different inserts were purchased from IDT and cloned into pLMCT using the Gibson assembly kit™ (NEB) and XL2-Blue Ultracompetent Cells (Agilent). Cloned plasmids were sequence-verified (Eurofins Genomics) and selected clones were further amplified by MIDI DNA-preparation using QIAGEN Plasmid Kits – (QIAGEN). Each plasmid was linearized overnight by restriction enzyme digestion with BfuAI (NEB) to enable in vitro mRNA transcription. A thorough quality control was performed assessing the yield (absorbance at 260/280 nm), integrity (BioAnalyzer 2100, DNA 7500 chip) and sequence (Eurofins Genomics) of each plasmid.

The in vitro transcription (iVT) reaction was performed starting from a dsDNA template using a T7 enzyme mix containing: T7 RNA polymerase (Thermo Fisher Scientific), RNase inhibitor (Promega) and inorganic pyrophosphatase (Thermo Fisher Scientific). The reaction buffer mix included 10 mM Clean CAP AG reagent (TriLink Biotech) and 10 mM of each dNTP (adenosine-, guanosine-, cytidine- and uridine-triphosphate, Promega). The reaction was incubated at 37 °C for 2 hours. After incubation, DNaseI exonuclease (Thermo Fisher Scientific) was added to the reaction mix and incubated for 15 minutes at 37 °C for the removal of residual dsDNA template. Enzymatic activity was stopped by adding 1.5 volumes of 40 mM EDTA solution to the reaction mix. The mRNA was purified by LiCl-mediated precipitation. Half the reaction volume of 8 M LiCl (Sigma-Aldrich) was added to the mRNA solution and stored at -20 °C overnight. The mRNA sample was centrifugated (15 minutes at 12100 x g) and the obtained pellet was washed with 70% ethanol (Sigma-Aldrich) and subsequently dissolved in RNase-free water (Gibco). A second purification step was performed by NaCl/EtOH precipitation, adding 5M NaCl (Sigma-Aldrich) and absolute ethanol (Sigma-Aldrich). The mRNA was centrifugated for 15 minutes at 14.000 rpm and the obtained pellet was washed with 70% ethanol solution and dissolved in RNase-free water (Gibco). A thorough quality control was performed on the resulting mRNA, including spectrophotometric analysis of optical density for the yield determination and purity (absorbance ratio at 260/280 nm), integrity (BioAnalyzer 2100, RNA 6000 chip) and RNA/cDNA sequence verification after reverse transcription (cDNA kit, NEB & Eurofins Genomics).

Transfection of mRNA to moDCs was performed by electroporation as described in de Mey et al (61). In short cells were extensively washed in serum-free OptiMEM (Life Technologies, Belgium). The electroporation was performed in 200 µL OptiMEM medium in a 4-mm electroporation cuvette (Cell Projects) using the following parameters: square wave pulse, 500V, 2 ms, 1 pulse using the Gene Pulser Xcell^TM device (Biorad, Belgium). Electroporation of moDCs was performed with a total concentration of 100 μg/ml mRNA.

Total RNA was extracted from DCs using the RNeasy plus mini kit (Qiagen, 74134) according to manufacturers’ guidelines. A Qubit 4 Fluorometer and the Qubit RNA HS Assay Kit (Thermo Fisher Scientific) were used to assess the RNA yield (on average 81.93 ng/µL ranging from 53 to 132 ng/µL). Absorbance at 260 and 280nm was evaluated using a NanoPhotometer Classic (Implen) with an average A260/A280 value of 2.02 (ranging from 1.942 to 2.055). Samples were run on an Agilent 2100 bioanalyzer using the RNA 6000 nano (5067-1511/1512/1529) kit and the eukaryotic total RNA program. The bioanalyzer electropherograms were analyzed using Agilent 2100 Expert Software to determine the RNA size distribution, the RNA integrity number (RIN) value (on average 9.14, ranging from 8.2-9.6) and the DV200 values (percentage of RNA fragments with a length >200 nucleotides) with an average value of 98.2 (ranging from 91 to 100). RNA (100ng) was analyzed to evaluate gene expression variation using the nanoString nCounter^® technology. Samples were hybridized according to manufacturers’ recommendations using the nCounter^® Human PanCancer Immune Profiling Panel. Absolute counts were quantified by the nCounter digital analyzer (nCounter MAX Analysis System). Counts were normalized using the RUVSeq method adjusted for nanoString nCounter^® gene expression analysis as described by Bhattacharya et al (62). Further data analysis was performed in R. Differential gene expression analysis was done using the DESeq2 package. Principal Component Analysis (PCA) was performed using variance-stabilized counts. Genes were marked as differentially expressed when adjusted p-value < 0.1 and log2 fold change threshold was set above or below 1 and -1, respectively. Gene ontology analysis for biological processes, was calculated using the clusterProfiler package. Biological processes with an adjusted p-value below 0.25 were considered as statistically significant. Gene pattern analysis was performed using the DEGreport package. Plots were generated using the ggplot2, EnhancedVolcano and pheatmap packages in R.

CD8⁺ T cells were isolated from monocyte-depleted PBMCs by magnetically-activated cell sorting (MACS) using positive selection with human anti-CD8 microbeads according to the manufacturer’s instructions (Miltenyi Biotec). When indicated CD8⁺ T_N cells were isolated from monocyte-depleted PBMCs by MACS using the CD8⁺ T-cell isolation kit, anti-CD45RO and anti-CD57 microbeads (Miltenyi Biotec). In that case, the monocyte-depleted PBMCs were depleted from CD45RO and CD57 positive cells, after which a positive selection was performed for CD8⁺ T cells. The T cells were co-cultured with moDCs that were electroporated with mRNA encoding GFP, tNGFR, TriMix, TetraMix or Melan-A/MART-1 following the protocol described by Bonehill et al (53). Evaluation of the CD8⁺ T-cell specificity for Melan-A/MART-1 was assessed at different time points using flow cytometry. When indicated the CD8⁺ T cells were phenotyped by flow cytometry or used for the in vitro killing assay.

Cells were harvested and washed twice with phosphate buffered saline containing 1% bovine serum albumin (flow cytometry buffer). The following antibody cocktail was used to phenotype moDCs: anti-CD11c-AF700 (clone BLY6, Becton Dickinson), anti-HLA-DR-PE-Cy7 (clone G466, Becton Dickinson), anti-HLA-ABC-APC-Cy7 (clone W6/32, Becton Dickinson), anti-CD40-PE (clone 5C3, Biolegend), anti-CD80-BV605 (clone L307.4 Becton Dickinson), anti-CD83-BV421 (clone HB15e, Biolgend), anti-CD86-FITC (clone FUN-1, Becton Dickinson), anti-CCR7-APC (clone G043H7, Biolegend) and anti-PD-L1-PE-CF594 (clone MIH1, Becton Dickinson). T-cell dextramer staining: anti-CD8-BV421 (clone RPA-T8, Biolegend) and MHC dextramer Mel-A-PE and -APC (HLA-A*0201/ELAGIGILTV, WB2162, Immudex). T-cell phenotyping was performed using the following antibodies: anti-CD45RA-BV421 (clone HI100, Biolegend), anti-CD45RO-PerCP-Cy5.5 (clone UCHL1, Biolegend), anti-CD95-P3-CF594 (clone DX2, Biolegend), anti-CCR7-PE (clone G043H7, Biolegend), anti-CD62L-FITC (clone DREG-56, Biolegend) and anti-IL-2Rβ-APC (clone TU27, Biolegend). The antibody cocktail used for the T-cell activation panel was: anti-CD25-AF488 (clone BC96, Biolegend), anti-CD69-PerCP-Cy5.5 (clone FN50, Biolegend), anti-CD134-APC (clone Ber-ACT34, Biolegend), anti-CD137-PE (clone 4B4-1, Biolegend), anti-PD-1-BV421 (clone EH12.2H7, Biolegend) and CTLA-4-PE-Cy7 (clone L3D10, Biolegend). All cells were also stained with Fixable viability dye eflour506 (eBioScience) to discriminate live from dead cells. The whole staining procedure was performed on ice. Data were acquired on the LSR Fortessa flow cytometer and analyzed with Flowjo Software, version 10.0.

IL-12p70 and IL-10 were quantified using the human IL-12p70 (MS238) and human IL-10 (BMS215-2) sandwich ELISA from Thermo Fisher Scientific according to the manufacturer’s instructions.

The 3D culture melanoma killing assay was performed as described by Awad et al (60). In brief GFP⁺ 624-MEL cells were cultured in ultra-low attachment plates (Greiner Bio-One) in 50 µL of DMEM. After 48h stimulated CD8⁺ T cells were added to the 3D tumor models in RPMI containing 100 ng/ml IL-15 (PeproTech, USA). Green fluorescence confluence of 3D tumors was monitored using the Incucyte® ZOOM live cell imaging system (EssenBio, UK). Each 3D tumor confluence was normalized to the 3D tumor confluence at 0h.

All statistical analyses were performed using GraphPad Prism software v8.4.3. Statistical analysis for all figures was performed by Friedman’s test on ranks with uncorrected Dunn’s test. Statistical significance is indicated as follows: *p < 0.05, **p < 0.01, ***p < 0.001,****p < 0.0001.