IL-10 MUTEINS
20230203117 · 2023-06-29
Inventors
Cpc classification
C07K2319/30
CHEMISTRY; METALLURGY
International classification
Abstract
The present disclosure relates to modified forms, or muteins, of IL-10, as well as variants thereof, which display improved features as compared to wild-type IL-10. The present invention further relates to the use of such modified forms, or muteins, of IL-10, as well as variants thereof in methods, including therapeutic methods.
Claims
1. An IL-10 mutein, wherein the IL-10 mutein comprises at least one amino acid substitution at positions 18, 92 and 99, as compared to full-length mature wild-type IL-10.
2. The IL-10 mutein according to claim 1, wherein the IL-10 mutein comprises at least two amino acid substitutions at positions 18, 92 and 99.
3. The IL-10 mutein according to claim 1, wherein the IL10 mutein comprises amino acid substitutions at all three positions, 18, 92 and 99.
4. The IL-10 mutein according to claim 1, comprising a substitution at position 18 and the substitution is Y or I (lettering according to recognised one-letter amino acid codes).
5. The IL-10 mutein according to claim 1, comprising a substitution at position 92 and the substitution is I.
6. The IL-10 mutein according to claim 1, comprising a substitution at position 99 and the substitution is N.
7. The IL-10 mutein according to claim 1, comprising one or more further substitutions, but typically less than 10, 9, 8, or 7 substitutions as compared to the wild-type IL-10 sequence.
8. The IL-10 mutein according to claim 7, wherein said one or more further substitutions is at positions 55, 69, 97, 110, 111 and/or 148.
9. The IL-10 mutein according to claim 1, wherein the IL-10 mutein is at least 97, 98, 99% or 100% identical to the sequence according to SEQ ID NO:5, 7, 11 or 15, but comprises at least the amino acid substitutions identified in SEQ ID NO:5, 7, 11 or 15, which differ with respect to the corresponding wild-type IL-10 sequence (SEQ ID NO: 1).
10. A fusion protein comprising an IL-10 mutein according to claim 1, fused to a further different protein molecule or portion of a protein molecule.
11. The fusion protein according to claim 10, wherein the further molecule is a different cytokine, such as an interleukin (IL) molecule or a wild-type or mutant IL-4 molecule.
12. (canceled)
13. The fusion protein according to claim 10, wherein the fusion protein comprises the sequence, which is at least 97, 98, 99%, or 100% identical to the sequence as identified in SEQ ID NO: 17, 19, 21, or 23, but comprises at least the amino acid substitutions identified in SEQ ID NO: 11 which differ with respect to the wild-type IL-10 sequence
14. The IL-10 mutein according to claim 1, wherein the IL-10 molecule is further modified by PEGylation, phosphorylation, amidation and/or glycosylation.
15. A pharmaceutical composition comprising an IL-10 mutein according to claim 1, together with a pharmaceutically acceptable excipient.
16. The pharmaceutical composition according to claim 15 together with a further pharmaceutically active agent, such as an anti-cancer agent, anti-inflammatory agent, or an immune tolerance promoting agent.
17. The pharmaceutical composition according to claim 16 wherein the further pharmaceutically active agent is an immune cell, such as a CAR T cell, or an anti-cancer or anti-inflammatory antibody.
18. (canceled)
19. A method of treating inflammation, autoimmune diseases, graft vs host disease, inflammatory bowel disease/Crohn's disease or cancer; comprising administering the IL-10 mutein, according to claim 1, to a subject in need thereof.
20. A polynucleotide encoding the IL-10 mutein according to claim 1, such as a DNA or RNA molecule.
21. A plasmid, virus, cell, lipid nanoparticle, or lipoplex comprising the polynucleotide according to claim 20.
22. The IL-10 mutein according to claim 1, wherein the IL-10 mutein binds to IL-10Rβ with a Kd which is 100-fold, preferably 1000-fold lower compared to the binding of wild type IL-10 to IL-10Rβ.
23. The IL-10 mutein according to claim 1, wherein the IL-10 mutein forms a dimer.
24. The fusion according to claim 10, wherein the IL-10 mutein is fused to at least one polypeptide binding domain, preferably an antibody or fragment thereof, most preferably a single chain antibody, for example a VHH.
25. The fusion according to claim 24, wherein the polypeptide binding domains binds to at least one checkpoint molecule selected from CD27, CD137, 2B4, TIGIT, CD155, ICOS, HVEM, CD40L, LIGHT, OX40, DNAM-1, PD-L1, PD1, PD-L2, CTLA-4, CD8, CD40, CEACAM1, CD48, CD70, A2AR, CD39, CD73, B7-H3, B7-H4, BTLA, IDO1, ID02, TDO, KIR, LAG-3, TIM-3, and/or VISTA, preferably PD-L1, PD1, wherein the polypeptide binding domains binds to at least one dendritic cell surface marker selected from CD1a, CD1c, CD11c, CD14, CD32b, CD123, CD141, CD206 (MR), CD2007 (Langerin), BDCA-1, BDCA-2, BDCA-3, BDCA-4, CADM1 (Necl2), Clec9A, DEC-205, DC-SIGN, DCIR2 (Clec4A4), LSP-1, SIRP alpha, and/or XCR1, or wherein the polypeptide binding domains binds to at least one inflammatory tissue marker selected from alpha(v) integrins (such as αvβ1, αvβ3, αvβ5 and αvβ8), CHI3L1 (YKL-40), CXCR4, E-Selectin, FAP, EDA and EDB Fibronectin, Galectin-3, ICAM-1, IGF2R (CI-MPR), LFA-1, MadCAM-1 (Adressin), MUC2, MUC4, PDGFR alpha, PDGFR beta, PSGL-1, STRA6 (RBP receptor), and/or VCAM-1.
26. (canceled)
27. (canceled)
28. The fusion protein according to claim 24, wherein the polypeptide binding domains binds to at least one microglia marker selected from CD11b, CD40, CD45, CD68, CX3CR1, EMR1 (F4/80), Iba1, and/or TMEM19.
29. The fusion protein according to claim 24, wherein the polypeptide binding domains binds to at least one tumor antigen selected from EpCAM, EGFR, HER-2, HER-3, c-Met, FoIR, PSMA, CD38, BCMA, CEA, 5T4, AFP, B7-H3, Cadherin-6, CAIX, CD117, CD123, CD138, CD166, CD19, CD20, CD205, CD22, CD30, CD33, CD40, CD352, CD37, CD44, CD52, CD56, CD70, CD71, CD74, CD79b, CLDN18.2, DLL3, EphA2, ED-B fibronectin, FAP, FGFR2, FGFR3, GPC3, gpA33, FLT-3, gpNMB, HPV-16 E6, HPV-16 E7, ITGA2, ITGA3, SLC39A6, MAGE, mesothelin, Muc1, Muc16, NaPi2b, Nectin-4, P-cadherin, NY-ESO-1, PRLR, PSCA, PTK7, ROR1, SLC44A4, SLTRK5, SLTRK6, STEAP1, TIM1, Trop2, and/or WT1
30. The fusion according to claim 24, wherein the IL-10 mutein is fused to half-life extending molecule, preferably an immunoglobulin fragment such as an Fc molecule, or a polypeptide binding domain against a blood serum protein, preferably against albumin.
Description
[0066] The present invention will now be further described by way of example and with reference to the figures, which show:
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[0083] Material and Methods
[0084] Protein Expression and Purification
[0085] Monomeric wild type IL-10 (Josephson et al., 2000), monomeric high affinity variants and IL-10Ra ectodomain (amino acids 22-235) were cloned and expressed as described in (Martinez-Fabregas et al., 2019). Briefly, protein sequences were cloned into the pAcGP67-A vector (CD Biosciences) in frame with an N-terminal gp67 signal sequence, driving protein secretion, and a C-terminal hexahistidine tag. The baculovirus expression system was used for protein production as outlined in (LaPorte et al., 2008). Spodoptera frugiperda (SF9) cells, grown in SF90011 media (Invitrogen), were transfected to produce Po baculovirus stocks that were then expanded in SF9 cells to produce Pi virus stock. Protein expression was performed using Trichoplusiani ni (High Five) with cells grown in InsectXpress media (Lonza).
[0086] Purification was performed using the method described in Sprangler et al (2019). Briefly, the cells were pelleted with centrifugation at 2000 rpm, prior to a precipitation step through addition of Tris pH 8.0, CaCl.sub.2 and NiCl to final concentrations of 200 mM, 50 mM and 1 mM. The precipitate formed was then removed through centrifugation at 6000 rpm. Nickel-NTA agarose beads (Qiagen) were added and the target proteins purified through batch binding followed by column elution in HBS, 200 mM imidazole, pH 7.2. Target proteins were concentrated and further purified by size exclusion chromatography on an ENrich SEC 650 300 column (Biorad), equilibrated in 10 mM HEPES (pH 7.2), 150 mM NaCl. IL-10Rα was biotinylated using EZ=Link NHS biotinylation kit (Thermo) according to the manufacturer's protocols.
[0087] For expression of biotinylated IL-10Rβ the ectodomain (amino acids 20-220) was cloned into the pAcGP67-A vector carrying a C-terminal biotin acceptor peptide (BAP)-LNDIFEAQKIEWHW followed by a hexahistidine tag. The purified protein was biotinylated with BirA ligase.
[0088] For expression of dimeric wild type IL-10 and dimeric high affinity variants, synthesised gene blocks (IDT) were cloned into the pET21 vector in frame with an N-terminal hexahistidine tag and a lac promotor, and transformed into E. Coli BL21 cells. Protein production was induced using 1 mM final concentration of IPTG (Formedium) followed by incubation at 37° C. for 3 to 5 hours. Cells were harvested by centrifugation at 6000×g for 15 minutes. The cell pellets were resuspended in 50 mM Tris-HCl (pH 8.0), 25% (w/v) sucrose, 1 mM Na EDTA, 10 mM DTT, 0.2 mM PMSF per litre of original culture and frozen at −80° C. overnight.
[0089] The recombinant protein was expressed as inclusion bodies, purification of which was performed as follows. Cells were lysed in 100 mM Tris-HCl (pH 8.0), 2% (v/v) TritonX-100, 200 mM NaCl, 2500 units Benzonase, 10 mM DTT, 5 mM MgCl2, 0.2 mM PMSF and incubated for 20 minutes with stirring at room temperature. 10 mM EDTA final concentration was then added to the suspension and the cells were sonicated (8-10 cycles of 15 seconds on/off, 15 microns, Soniprep 150) in an ice bath. The solution was centrifuged at 7000×g for 15 mins (4° C.) and resuspended in 50 mM Tris-HCl pH 8.0, 0.5% Triton X-100, 100 mM NaCl, 1 mM Na EDTA, 1 mM DTT, 0.2 mM PMSF. This step was repeated for a total of at least three washes until the preparation appeared white. The final pellet was then washed once in detergent free buffer (50 mM Tris-HCl pH 8.0, 1 mM Na EDTA, 1 mM DTT, 0.2 mM PMSF).
[0090] The purified inclusion bodies were solubilised in 10 mls of 6M GuHCl per litre of original culture, for 30 minutes at room temperature. The solution was clarified by a centrifugation at 7000 rcf for 15 minutes and the solubilised protein carefully decanted. Refolding was performed through dropwise addition of the solubilised protein solution into refolding buffer (50 mM Tris-HCl, pH 8.0, 50 mM NaCl, 5 mM EDTA, 2 mM reduced glutathione (GSH) and 0.2 mM oxidized glutathione (GSSG)) at a ratio of 1:20 solution:buffer at 4° C. followed by incubation with gentle stirring overnight at 4° C.
[0091] The solution was then filtered to remove any precipitant and dialysis performed against 10 mM HEPES (pH 7.2), 150 mM NaCl, using dialysis membrane with a 14 kDa Mwt cut off.
[0092] After dialysis protein was then further purified using Ni-NTA beads and by size exclusion on a Superdex75 increase 10/300 column (GE Healthcare). Endotoxin removal was then performed. 1 mL of Ni-NTA agarose was added to a polyprep column and equilibrated with 10 mls of HBS before addition of the protein. The column was washed with 50 column volumes of ice-cold HBS, 150 mM NaCl, 20 mM imidazole, 0.1% Triton-X114 (pH X) to remove endotoxin. The column was then washed with a further 20 column volumes of HBS, 20 mM imidazole (pH X). The now endotoxin-free protein was eluted using 4 column volumes of HBS, 200 mM imidazole (pH X). The protein was buffer exchanged into 10 mM HEPES, 150 mM NaCl (pH 7.2), using PD-10 columns (GE Healthcare). Endotoxin levels were measured using Pierce LAL Chromogenic Endotoxin Quantitation Kit (Thermo) following the manufacturer's protocol. For all proteins endotoxin levels were below detection levels of the kit.
[0093] Surface Plasmon Resonance
[0094] Surface plasmon resonance was used to determine the binding affinity of the recombinantly produced monomeric IL-10 wild type and variants to IL-10Rβ in the presence or absence of IL-10Rα. Biotinylated IL-10Rβ was immobilised onto the chip surface via streptavidin. Series S Sensor SA (GE Healthcare) chips were primed in 10 mM HEPES, 150 mM NaCl, 0.02% TWEEN-20, prior to immobilisation of the biotinylated receptor. Analysis runs were then performed in 10 mM HEPES, 150 mM NaCl, 0.05% TWEEN-20 and 0.5% BSA. A Biacore T100 (T200 Sensitivity Enhanced) was used for measurement with Biacore T200 Evaluation Software 3.0 used for data analysis.
[0095] Cell Culture
[0096] Human buffy coats were obtained from the Scottish Blood Transfusion Service and peripheral blood mononuclear cells (PBMCs) were isolated by density gradient centrifugation (Lymphoprep, StemCell Technologies). PBMCs were grown in RPMI-1640, 10% v/v FBS, 100 U/mL penicillin-streptomycin (Gibco) and cytokines for proliferation and activation. For three days media was supplemented with 100 ng/mL anti-CD3 (human UltraLEAF, Biolegend) and 20 ng/mL IL-2 (Proleukin, Novartis) in the absence or presence of IL-10 variants. After three days activation cells were centrifuged and resuspended in media supplemented with 20 ng/mL of IL-2 plus or minus IL-10 variants. Cell populations were allowed to expand for 2-3 days.
[0097] Monocytes were isolated from PBMC populations using CD14 positive selection. Anti-CD14.sup.FITc antibody (Biolegend #367116) was used to stain cells and isolation was done by magnetic separation following manufacturer's protocol (MACS Miltenyi). Monocytes were then cultured in complete RPMI (as above) supplemented with M-CSF (20 ng/mL, Biolegend). Cells were then stimulated with IL-10 variants for twenty-four hours before analysis.
[0098] CD8 T cells were isolated from PBMCs by magnetic separation (MACS Miltenyi) after staining with anti-CD8a.sup.FITC antibody (Biolegend #30906). For activation of purified CD8 T cells ImmunoCult Human CD3/CD28 T cell Activator (Stem Cell) was used following manufacturer's protocol as well as the addition of 20 ng/mL IL-2 and IL-10 variants. Cells were activated for 3 days and then the media was replaced with complete RPMI supplemented with 20 ng/mL IL-2 as well as IL-10 variants for 2-3 days.
[0099] Flow Cytometry Staining and Antibodies
[0100] For live cell surface staining of HLA-DR.sup.PE (Biolegend #307605) non-adherent monocytes were removed from culture by centrifugation and resuspension in cold PBS. Adherent monocytes were detached using Acutase (StemCell Technologies) at room temperature for 5 to 10 minutes. Cells were kept at 4° C. or on ice during live cell surface marker staining and staining was done in 96-well v-bottom plates (Griener) unless otherwise stated. Non-adherent and detached cells were combined and resuspended in FcR blocking reagent (Miltenyi) for 10 minutes at 4° C. in a volume of 50 μL per condition. Cells were washed in PBS/0.5% BSA and resuspend in 50 μL of antibody mixture diluted 1/100 in FcR blocking reagent. Antibody incubation was done for 30 to 60 minutes at 4° C. in the dark. Cells were washed twice before resuspension in 100 μL per well for analysis on the CytoFlex flow cytometer (Beckman Coulter). Mean fluorescence intensity (MFI) was quantified for all populations. Data was normalised within each donor by dividing MFI of IL-10 treated cells by a non-IL-10 treated control from the same donor to calculate fold change.
[0101] For granzyme B intracellular staining either PBMCs or CD8 cells on day 6 of activation were fixed with 2% paraformaldehyde for 10 minutes at room temperature before washing in PBS. Cells were permeabilised in 0.1% Triton-X100/PBS for 10 minutes and washed in PBS/0.5% BSA. Cells were stained with anti-CD8a.sup.AlexaFluor700 (Biolegend #300920), anti-CD4.sup.PE (Biolegend #357404), anti-CD3.sup.BrilliantViolet510 (Biolegend #300448) and anti-granzyme B.sup.FITC (Biolegend #515403) at 1/100 dilution for one hour before washing. MFI was quantified for all populations and normalisation was done as described above.
[0102] For phospho-flow analysis of STAT1 and STAT3 cells were plated at 50 μL of cell suspension per well at a density of 2×10.sup.4 cells per well in 96-well V bottom plates. For does response studies cells were simulated with 7-fold serially diluted IL-10 variants and an unstimulated control (50 μL per well) for 15 minutes at 37° C. before fixation with 2% paraformaldehyde for 10 minutes at room temperature. For kinetic studies, cells were stimulated with a saturating concentration of IL-10 variants (50 nM) at defined time points before fixation simultaneously with 2% paraformaldehyde. Cells were washed in PBS and permeabilised in ice-cold 100% methanol and incubated on ice for a minimum of 30 minutes. Cells were fluorescently barcoded as described in (Krutzik and Nolan, 2006; Martinez-Fabregas et al., 2019). Briefly, a panel of 16 combinations of two NHS-dyes (Pacific Blue and DyLight800, Thermo) were used to stain individual wells on ice for 35 minutes before stopping the reaction by washing in PBS/0.5% BSA. Once barcoded the 16 populations were be pooled together for antibody staining. PBMCs, CD8 cells and monocytes were stained with the cell surface markers described above as well as anti-pSTAT3.sup.Alexa488 (Biolegend #651006) and anti-pSTAT1.sup.Alexa647 (Cell Signalling Technologies #8009). During acquisition individual populations were identified according to the barcoding pattern and pSTAT3.sup.Alexa488 and pSTAT1.sup.Alexa647 MFI was quantified for all populations. MFI was plotted and sigmoidal dose response curves were fitted using Prism software (Version 7, GraphPad). Data was normalised by assigning the highest MFI of the top concentration of all stimuli as 100% and the lowest MFI as 0% within each donor group.
[0103] Yeast Display Library
[0104] Yeast surface display protocol was adapted from previous protocols (Boder and Wittrup, 1997; Martinez-Fabregas et al., 2019). To create an IL-10 yeast display library the monomeric IL-10 gene (Josephson et al., 2000) was subject to error-prone PCR as described in (Mendoza et al., 2017). This product was then amplified and transformed along with a linearized pCT302 vector into the Saccharomyces cerevisiae stain EBY100 and grown in selective dextrose casamino acids (SDCAA) media at 30° C. for two days. Yeast cells were then place in selective galactose casamino acids (SGCAA) at 20° C. for two days to induce cell surface expression of IL-10 variants as described in (Chao et al., 2006). Magnetic activated cell sorting (MACS, Miltenyi) was used to select for IL-10 variants with increased binding affinity for IL-10Rβ as described previously for other systems (Moraga et al., 2015b). Briefly, the first round of selection was performed using high concentrations of streptavidin beads to remove any yeast which displayed variants capable of binding streptavain. The second round of selection selected for yeast which display variants with the c-myc tag at their C-terminus, ensuring that displayed proteins were properly folded. The subsequent rounds of selection were carried out by incubating induced yeast with decreasing concentrations of recombinantly produced biotinylated IL-10Rβ for 2 hours followed by a 15 minute incubation with fluorescently labelled streptavidin (AlexaFluor647). Magnetic activated cell sorting (MACS, Miltenyi) selected for yeast which displayed IL-10 variants capable of binding IL-10Rβ. Once the concentration of IL-10Rβ needed for binding was decreased sufficiently compared to wild type monomeric IL-10, the yeast were plated on SDCAA agar and single colonies were isolated for dose response studies to determine the EC50 values of the mutants.
[0105] Yeast colonies displaying promising IL-10 variants were subject to Zymoprep (ZymoResearch) to isolate the plasmid which was then heat shocked into competent DH5a E. coli and plasmids were sequenced to observe where mutations had occurred in the monomeric IL-10 gene. These genes were then cloned into the baculovirus expression vector pACgp67BN and recombinantly expressed as described above.
[0106] Measurement of IL-6 Secretion
[0107] Monocytes were stimulated with LPS (100 ng/mL) (E. coli 026:B6, Sigma) plus IL-10 variants at various concentration for 8 hours. Supernatant was then removed and used for enzyme linked immunosorbent assay (ELISA) for IL-6 detection (Biolegend, #430501). Manufacturer's protocol was followed. 96-well half-area plates (Sigma) were coated in capture antibody and incubated overnight at 4° C. Plates were washed in PBS/0.05% Tween-20 and blocked for 1 hour in assay diluent and washed. Supernatant was diluted 1 to 10 in assay buffer before addition to the plate. The plates were incubated at room temperature for two hours with shaking. Plates were washed again and incubated for 1 hour with detection antibody. After washing, avidin-HRP was added and incubated for 30 minutes followed by incubation with TMB substrate solution for 15 minutes. The reaction was stopped by addition of H.sub.2SO.sub.4 and absorbance was measured at 450 nm and 570 nm with absorbance at 570 nm being subtracted from 450 nm.
[0108] RNA Transcriptome Sequencing
[0109] Human primary monocytes and CD8 T cells from three donors each (StemCell Technologies) were stimulated as described in above. Cells were washed in Hank's balanced salt solution (H BSS, Gibco) and snap frozen for storage. RNA was isolated using the RNeasy Kit (Quiagen) according to manufacturer's protocol. All RNA 260/280 ratios were above 1.9. 1 μg of RNA was used per sample. Transcriptomic analysis was done by Novogene as follows. Sequencing libraries were generated using NEBNext® Ultra™ RNALibrary Prep Kit for Illumina® (NEB, USA) following manufacturer's recommendations and index codes were added to attribute sequences to each sample. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads. Fragmentation was carried out using divalent cations under elevated temperature in NEBNext First StrandSynthesis Reaction Buffer (5×). First strand cDNA was synthesized using random hexamer primer and M-MuLV Reverse Transcriptase (RNase H−). Second strand cDNA synthesis was subsequently performed using DNA Polymerase I and RNase H. Remaining overhangs were converted into blunt ends via exonuclease/polymerase activities. After adenylation of 3′ ends of DNA fragments, NEBNext Adaptor with hairpin loop structure were ligated to prepare for hybridization. In order to select cDNA fragments of preferentially 150-200 bp in length, the library fragments were purified with AMPure XP system (Beckman Coulter, Beverly, USA). Then 3 μl USER Enzyme (NEB, USA) was used with size-selected, adaptor-ligated cDNA at 37° C. for 15 min followed by 5 min at 95° C. before PCR. Then PCR was performed with Phusion High-Fidelity DNA polymerase, Universal PCR primers and Index (X) Primer. At last, PCR products were purified (AMPure XP system) and library quality was assessed on the Agilent Bioanalyzer 2100 system.
[0110] RNA Sequencing Data Analysis
[0111] Primary data analysis for quality control, mapping to reference genome and quantification was conducted by Novogene as outlined below.
[0112] Quality control: Raw data (raw reads) of FASTQ format were firstly processed through in-house scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapter and poly-N sequences and reads with low quality from raw data. At the same time, Q20, Q30 and GC content of the clean data were calculated. All the downstream analyses were based on the clean data with high quality.
[0113] Mapping to reference genome: Reference genome and gene model annotation files were downloaded from genome website browser (NCBI/UCSC/Ensembl) directly. Paired-end clean reads were mapped to the reference genome using HISAT2 software. HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome. These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads.
[0114] Quantification: HTSeq was used to count the read numbers mapped of each gene, including known and novel genes. And then RPKM of each gene was calculated based on the length of the gene and reads count mapped to this gene. RPKM, (Reads Per Kilobase of exon model per Million mapped reads), considers the effect of sequencing depth and gene length for the reads count at the same time and is currently the most commonly used method for estimating gene expression levels.
[0115] Statistical analysis was done by the authors in Excel. The fold change was calculated by dividing the IL-10 stimulated expression levels by the unstimulated control within each donor. The average fold change was calculated for each stimulation across the three donors and the log.sub.2 of this average was then calculated. For calculation of significantly changed genes, the log.sub.2 of the fold change between IL-10 stimulated and unstimulated expression levels of each donor was calculated, separately and an unpaired, two tailed t test was used to generate the p value. The logo of this p value was then plotted against the previously calculated log.sub.2 average fold change. Genes which were significantly (p≤0.05) changed greater than 0.6 or less than −0.6 log.sub.2 fold change in the wild type IL-10 dimer (WTD) 50 nM condition were taken as a set list of genes against which all other IL-10 stimulations were compared. Upregulated genes were denoted as genes ≥0.6 log.sub.2 fold change and downregulated genes were denoted as genes ≤−0.6 log.sub.2 fold change. For comparison of WTD to other IL-10 variant stimulations the average log.sub.2 fold changes of the variant was divided by the average log.sub.2 fold change of WTD. Genes with an RPKM of less than 1 in two or more donors were excluded from analysis so as to remove genes with abundance near detection limit.
[0116] Functional annotation of genes (KEGG pathways, GO terms) was done using DAVID Bioinformatics Resource functional annotation tool (Huang da et al., 2009a, b). Clustered heatmap was generated using R Studio Pheatmap package.
[0117] Live-Cell Dual Colour Single Molecule Imaging Studies
[0118] Receptor homo- and heterodimerization was quantified by two-colour single-molecule co-tracking as described previously (Moraga et al., 2015c, Wilmes et al., 2015, Wlmes et al., 2020). Receptor dimerization experiments were performed in HeLa cells transiently expressing IL-10Rα and IL-10Rβ with N-terminally fused variants of monomeric ECFP and EGFP, respectively. Cell surface Labelling was achieved using anti-GFP nanobodies Minimizer (MI) and Enhancer (EN), respectively, site-specifically conjugated with photostable fluorophores via an engineered cysteine residue. For quantification of receptor heterodimerization, IL-10Rα and IL-10Rβ were labelled with MI.sup.Rho11 (ATTO Rho11, ATTO-TEC GmbH) and EN.sup.AT643 (ATTO 643, ATTO-TEC GmbH), respectively. For quantification of homodimerization, either IL-10Rα was labelled with MI.sup.Rho11 and MI.sup.AT643, or IL-10Rβ was labelled with EN.sup.Rho11 and EN.sup.AT643. Over-expression of the corresponding other receptor subunit was ensured by labelling with EN.sup.AT488 or MI.sup.AT488 (ATTO 488, ATTO-TEC GmbH), respectively. Time-lapse dual-color imaging of individual IL-10Rα and IL-10Rβ in the plasma membrane was carried out by total internal reflection fluorescence microscopy with excitation at 561 nm and 640 nm and detection with a single EMCCD camera (Andor iXon Ultra 897, Andor) using an image splitter (QuadView QV2, Photometrics). Molecules were localized using the multiple-target tracing (MTT) algorithm (Serge et al., 2008). Receptor dimers were identified as molecules that co-localized within a distance threshold of 150 nm for at least 10 consecutive frames as described in detail previously (Moraga et al., 2015c, Wilmes et al., 2015, Wilmes et al., 2020).
[0119] Results:
[0120] Engineering IL-10 Variants with Enhanced Affinity Towards IL-10Rβ
[0121] IL-10 engages its tetrameric receptor complex in a two-step binding process. In a first step one molecule of IL-10 binds two copies of IL-10Rα with high affinity and in a second step, two copies of IL-10Rβ are recruited to the tetrameric IL-10/IL-10Rα complex to initiate signalling (
[0122] First, we transfected yeast with the monomeric IL-10 construct to test whether binding to IL-10Rα and IL-10Rβ receptor subunits was preserved in the context of the yeast surface. We used biotinylated IL-10Rα and IL-10Rβ receptors in combination with Alexa-647 fluorescently labelled streptavidin to measure receptor binding by flow cytometry (
[0123] Biophysical Characterisation of Isolated IL-10 Variants
[0124] Next we recombinantly expressed the isolated IL-10 variants and characterized their biophysical properties. Importantly, the IL-10 variants behave as monomers when run in a gel filtration column confirming their monomeric nature (
[0125] IL-10 displays cooperative binding kinetics whereby its affinity for IL-10Rβ is enhanced once pre-bound to IL-10Rα (Walter, 2014). Thus, we investigated whether our mutants preserved this property. For that, we performed new SPR measurements using the high affinity IL-10 variants pre-bound to soluble IL-10Rα (
[0126] Enhanced IL-10Rβ Binding Affinity Improves Receptor Complex Assembly.
[0127] Thus far we had carried out the biophysical characterisation of our high affinity IL-10 variants in the monomeric conformation of the cytokine as this was necessary for the protein engineering methodologies used. In order to recapitulate the native IL-10/IL-10 receptor complex stoichiometry we recombinantly expressed our high affinity IL-10 mutant, R5A11, in the dimeric form (R5A11D) in addition to the monomeric form (R5A11M) (
[0128] In order to test how increasing the binding affinity to IL-10Rβ altered the dynamics of receptor assembly at the plasma membrane of live cells, we probed diffusion and interaction of both receptor chains by dual colour total internal reflection fluorescence (TIRF) microscopy. To this end, we expressed in HeLa cells IL-10Rα and IL-10Rβ tagged with engineered variants of non-fluorescent (Y67F) mEGFP. The tags were designed to specifically recognise either one of two different anti-GFP nanobodies ((Kirchhofer et al., 2010) pdb: 3K1K and 3G9A). These nanobodies (NBs) were conjugated to photostable organic fluorophores RHO11 and Dy649 suitable for simultaneous dual-colour single molecule tracking of IL-10Rα.sup.DY649 and IL-10Rβ.sup.RHO11 on the surface of live cells as shown previously in other cytokine receptor systems (Martinez-Fabregas et al., 2019, Wilmes et al., 2020, Moraga et al., 2015a) (
[0129] After cell surface labelling we found both receptor subunits freely diffusing in the plasma membrane. Receptors were considered as dimerized if two individual particles were persistently found in both spectral channels for ≥10 consecutive steps (˜320 ms) in a proximity of 100 nm. These co-localization/co-tracking thresholds allowed the elimination of density-dependent random encounter co-localizations. In the absence of IL-10, we did not observe heterodimerization of IL-10Rα and IL-10Rβ above background (
[0130] IL-10 Variants Exhibit Enhanced Signalling Activities in Human Primary Monocytes
[0131] IL-10 inhibits inflammatory processes by modulating the activities of different innate cells including monocytes. We next performed a battery of signalling and activity assays in human monocytes to investigate the anti-inflammatory potential of our engineered variants. Monocytes (CD14+ cells) were isolated from human buffy coats and rested for two days before stimulation with IL-10 wt and high affinity monomer and dimers (
[0132] IL-10 exerts its anti-inflammatory properties by inhibiting antigen presentation in innate cells such as monocytes and dendritic cells (Mittal and Roche, 2015). Thus, we next studied whether IL-10 binding affinity to IL-10Rβ influences its ability to decrease HLA-DR expression in human primary monocytes. WTD and R5A11D reduced the HLA-DR surface levels to similar extent (50%) at saturating doses, in agreement with their comparable signalling profiles (
[0133] Increased Receptor Affinity Enhances Transcriptional Activity of IL-10 in Monocytes
[0134] Our initial studies in monocytes were focused on two classical markers regulated by IL-10, i.e. HLA-DR levels and IL-6 expression. To gain a broader understanding of how our variants regulate human monocytes activities, we performed detailed transcriptional analysis of human monocytes stimulated with the different IL-10 ligands for 24 hrs. Monocytes were isolated and treated as in
[0135] Next we studied how the engineered IL-10 variants regulated gene expression programs in monocytes. WTM induced a very poor transcriptional response, in line with its weak signal activation profile (
[0136] IL-10 Variants Exhibit Enhanced Signalling Activities in Human Primary CD8 T Cells
[0137] In addition to its potent anti-inflammatory effects IL-10 stimulates cytotoxic CD8 T cells under certain circumstances, enhancing production of effector molecules and increasing their cytotoxic activity (Oft, 2014). We next investigated whether the enhanced activities exhibited by our affinity-matured variants in monocytes would translate into CD8 T cells. Human primary CD8 T cells were grown and activated as shown in
[0138] Granzyme B is a potent cytotoxic effector molecule which has been shown to be increased in CD8 T cells upon IL-10 stimulation (Naing et al., 2018). Next, we studied how granzyme B production by CD8 T cells was regulated by the different IL-10 ligands. For that, PBMCs or isolated CD8 T cells were activated following the workflow illustrated in
[0139] Increased Receptor Affinity Enhances Transcriptional Activity of IL-10 in CD8 T Cells
[0140] To obtain a more complete understanding of how IL-10 regulates CD8 T cells responses, we next performed transcriptional studies on CD8 T cell treated with the different IL-10 ligands. Human CD8 T cells were purified by positive selection and activated in the presence of IL-10 wt and variants over 6 days as shown in
[0141] As seen for monocytes, WTM showed very poor induction of gene expression (
[0142] Differential Gene Expression Program Regulated by IL-10 in Monocytes and CD8 T Cells
[0143] Our study provides a high detailed description of transcriptional changes induced by IL-10 in monocytes and CD8 T cells. Despite the obvious discrepancies in the manner that the two cell types were stimulated with IL-10, we decided to investigate similarities of the transcriptional program induced by IL-10 in the two cell subsets, as a proxy to understand STAT3 transcriptional activities. To minimize variability resulting from the different treatments, we focused on genes that were regulated by IL-10 treatment in both monocytes and CD8 T cells. Interestingly, 181 genes were regulated by IL-10 in monocytes and CD8 T cells (
[0144] Production of Pentameric IL-10 Mutein and IL-10 Mutein/IL-4 Fusions
[0145] Our data have shown that a stabilization of the IL-10/receptor complex results in more potent immuno-modulatory activities by IL-10. Thus, we hypothesize that further stabilizing the IL-10/receptor complex by increasing the binding valency of IL-10 would result in a significant improvement on the activities induced by this ligand. For that, we took advantage of the pentameric BTB domain from KCTD protein to engineer a fusion protein comprised of the pentameric BTB domain and the monomeric R5A11 (Fig. X and Seq. ID. Y). We have recombinantly expressed high levels of this chimeric protein proving the feasibility of the approach (Figure X).
[0146] There are very few anti-inflammatory ligands described in the literature. One of them is IL-10, which we have engineered in this invention. An additional anti-inflammatory cytokine is IL-4. Here we have hypothesized that a synthetic cytokines comprising these two molecules would have exceptional anti-inflammatory properties. For that we have used our monomeric high affinity IL-10 variant as a scaffold and fuse it to three different IL-4 variants. IL-4 variant 1 correspond to the wild type molecule. IL-4 variant 2 correspond to an IL_4 variant that does not bind Gc or IL-13Ra1 and act as an antagonist. Variant 3 correspond to an IL-4 variant that exhibits reduced affinity for IL-4Ra. We expect that these mutations will affect the biodistribution of the synthetic molecules and target them to interesting immune cell subsets.
[0147] IL-10 in CART Cancer Therapy
[0148] Our data support a positive role of IL-10 in boosting CD8 T cell cytotoxic activities. IL-10 treatment induced the upregulation of Granzyme B by CD8 T cells and reduced their exhaustion gene signature, overall increasing the fitness. Based on this findings we next decided to explore the potential use of IL-10 to enhance CAR T cell therapies. CAR T cells are T cells that have been engineered to express an artificial receptor that allow them to specifically target tumor cells of interest. In recent years this therapy have shown a lot of potential and have revolutionized cancer immuno-therapy. However, CAR T cells still suffer from some drawbacks that reduce their efficacy, including the exhaustion of engineered CAR T cells due to over activation. Incubating CAR T cells with IL-10 before the administration to the patient could improve their fitness and therefore enhance their tumor killing potential. Here we provide some preliminary results that support this hypothesis. CAR T cells treated with either IL-10 wt or our engineered IL-10 variant (R5A11) show stronger killing activity in vitro (
[0149] Discussion:
[0150] IL-10 is an important immuno-modulatory cytokine that regulates inflammatory responses and enhances CD8 T cells cytotoxic activities (Moore et al., 2001; Oft, 2014; Walter, 2014). Despite its central role preserving immune homeostasis, there is still a dearth of knowledge of the exact molecular mechanisms through which IL-10 carries out its functions. We postulate that the weak binding affinity that IL-10 exhibits for IL-10Rβ critically contributes to its functional fitness, by limiting the range of concentrations at which IL-10 elicits its full immuno-modulatory potential. Here we have engineered IL-10 to enhance its affinity for IL-10Rβ to investigate whether the stability of the IL-10 receptor complex determines IL-10 bioactivity potencies. Two main findings arise from our study: (1) Affinity-enhanced IL-10 variants trigger more robust responses at a wide range of ligand concentrations and in different immune cell subsets than wildtype IL-10, and (2) the stoichiometry of the IL-10-receptor complex contributes to IL-10 bioactivity potencies beyond regulation of STAT activation levels. More generally, this work outlines a strategy to improve the potency of low receptor binding affinity cytokines and presents new molecular and cellular data with the potential to revitalise failed IL-10 therapies.
[0151] IL-10 exerted a profound regulation of the monocytic transcriptional program in our studies, agreeing with previous observations (Moore et al., 2001). IL-10 treatment inhibited antigen presentation by monocytes, limited their ability to recruit inflammatory immune cell subsets through regulation of chemokines and chemokine receptor expression, and boosted their phagocytic activity through the upregulation of scavenger receptors such as CD93, CD47, CD163 and cytokine receptors such as IL-21Ra. In addition, IL-10 treatment modulated the metabolic activity of monocytes by altering their glycolytic and lipid biosynthesis potential, in line with recent studies (Ip et al., 2017). Interestingly, IL-10 effects were slightly biased towards gene repression, with 59% of genes regulated by IL-10 being downregulated. Indeed, several studies have reported the ability of STAT3 to inhibit transcription induced by other STATs (Costa-Pereira et al., 2002; Ray et al., 2014; Yang et al., 2011), suggesting that STAT3 activating cytokines may elicit their functions by disrupting transcriptional programs induced by other cytokines. In agreement with this model, we recently reported that IL-6, another STAT3 activating cytokine, promoted strong STAT3 binding to chromatin, but poor gene expression (Martinez-Fabregas et al., 2019).
[0152] The vast majority of reports in the literature describing IL-10 activities have focused on myeloid cells and use a single dose of IL-10, often at saturation (de Waal Malefyt et al., 1991a; Ding et al., 1993; Fiorentino et al., 1991a). However, we have a poor understanding regarding the range of IL-10 doses at which this cytokine elicits a full response in myeloid cells, a critical aspect when considering translation of this cytokine to the clinic. Here we provide transcriptional data from monocytes stimulated with two different doses of IL-10, one saturating and the second sub-saturating, with the latter more closely resembling the doses achieved during IL-10 therapies (Naing et al., 2018). Interestingly, 27% of genes regulated by IL-10 were affected when sub-saturating doses of IL-10 were used. The vast majority of affected genes (95%) were genes downregulated by IL-10 and encoded proteins critically contributing to establish an inflammatory environment i.e. key chemokines and cytokines such as IL-24, CXCL10, CXCL11, CCL22. This data suggests that IL-10 anti-inflammatory activities specifically require high and sustained doses to reach their full effect, explaining in part the failing of IL-10 therapies. Our engineered IL-10 variant exhibited a more robust activity at sub-saturating doses and induced potent inhibition of pro-inflammatory chemokines and cytokines, i.e. IL-24, CXCL10, CXCL11, CCL22. It is thus tempting to speculate that our engineered variant could rescue failed IL-10 therapies by promoting anti-inflammatory activities at low ligand doses.
[0153] The anti-inflammatory activities elicited by IL-10 and its effects on monocytes and macrophages are very well documented. How IL-10 regulates the activity of CD8 T cells on the other hand is less clear and more controversial (Oft, 2014). While some studies have reported that IL-10 enhances the function of CD8 T cells and their ability to kill tumour cells (Emmerich et al., 2012), others report that the presence of IL-10 in the tumour microenvironment predicts poor responses by inhibiting T cell activation (Zhao et al., 2015). Our results agree with a positive effect of IL-10 treatment in CD8 T cells cytotoxic activities. CD8 T cells stimulated in the presence of IL-10 exhibited enhanced levels of effector molecules such as granzyme B, agreeing with recent clinical trials that show an improvement in the tumour response of patients treated with Pegylated-IL-10 (Naing et al., 2019). However, the molecular bases by which IL-10 boosts the anti-tumour CD8 T cell response remains poorly defined. Our transcriptional studies highlighted that CD8 T cells stimulated with IL-10 exhibited a reduced exhaustion gene signature and were more functionally fit. IL-10 treated CD8 T cells also expressed lower levels of IL-2Ra, which correlated with a reduced IL-2 gene signature in these cells. Altogether, our data agree with a model where IL-10, by reducing the sensitivity of CD8 T cells to IL-2, may prevent their over-activation and decrease their transition towards an exhausted phenotype. Remarkably, IL-10 preferentially repressed gene expression in CD8 T cells, with 79% of the genes controlled by IL-10 being downregulated, suggesting that STAT3 activation by IL-10 may compete with other STATs for binding to relevant gene promoters, fine-tuning CD8 T cell responses. Indeed, previous studies have reported a competition between STAT3 and STAT5 proteins for binding to gene promoters that influence cell sensitivity to IL-2 and inflammation (Yang et al., 2011). Our engineered IL-10 variant outperformed IL-10 wildtype in every read out tested when sub-saturating doses were used, reproducing our observations in monocytes and highlighting its potential to boost anti-tumour responses at therapeutical doses.
[0154] The importance of the dimeric IL-10 architecture for generating its biological responses is not yet well understood. WTD binds IL-10Rα 60-fold more avidly than WTM, which contributes to its more efficient recruitment of IL-10Rβ to the signaling complex and its more potent activities (ref). Paradoxically, R5A11M, which binds IL-10Rβ with higher affinity and elicits more efficient receptor assembly than WTD, triggers weaker transcriptional responses, despite activating STATs to a very similar extent than WTD. In addition, viral IL-10 (also a dimeric ligand) induces the same specific activity than WTD even though binds IL-10Rα with lower affinity than WTM (Tan et al., 1993). Overall these observations suggest that in addition to receptor binding affinity, the stoichiometry of the IL-10-receptor complex contributes to fine-tune IL-10 bioactivity potencies. We recently showed that the number of phospho-tyrosines available in cytokine receptor intracellular domains critically contribute to defining signalling identity by cytokines (Martinez-Fabregas et al., 2019). IL-6 variants that triggered partial phosphorylation of Tyr available in the gp130 intracellular domain exhibited a biased STAT3 versus STAT1 activation (Martinez-Fabregas et al., 2019). A similar model could be invoked to explain functional differences between monomeric and dimeric IL-10 ligands. The dimeric IL-10 variants engage two molecules of IL-10Rα and IL-10Rβ, providing twice as many Tyr available for phosphorylation than the monomeric ligands. This in turn would result in an increase local concentration of phosphorylated Tyr that potentially could engaged additional signaling molecules not recruited by the monomeric ligands, and provide functional specificity. In agreement with this model, WTM and R5A11M elicited biased STAT3 activation in CD8 T cells. Future studies will need to address whether the higher number of Tyr available in the hexameric complex engaged by WTD contribute to define its signaling signature and biological identity.
[0155] Our study provides a detailed description of how sub-optimal concentrations of IL-10, such as the one achieved during therapeutic interventions, differentially affects IL-10 immuno-modulatory properties. As concentrations of IL-10 decrease critical anti-inflammatory activities induced by this cytokine are lost. IL-10 therapies have been administrated to patients with a wide range of inflammatory disorders, but for the most part only produced disappointing results (Buruiana et al., 2010; Colombel et al., 2001). It is believed that local concentrations of IL-10 reached in the affected tissues during therapies are too low to trigger adequate anti-inflammatory responses (Buruiana et al., 2010; Colombel et al., 2001). In addition, the levels of IL-10 receptor significantly change across different myeloid cell populations, altering their sensitivity to IL-10 and possibly contributing to the poor responses observed in IL-10 therapies (Ding et al., 2001). Importantly, administration of IL-10 is well tolerated by patients, with only some mild side effects when high doses of IL-10 are used (Buruiana et al., 2010; Colombel et al., 2001). Our high affinity IL-10 variant has the potential to overcome these limitations and reinvigorate IL-10 therapies by eliciting strong anti-inflammatory and anti-cancer responses at therapeutically relevant doses, for example 100 μM-10 nM.
REFERENCES
[0156] BENGSCH, B., OHTANI, T., KHAN, O., SETTY, M., MANNE, S., O'BRIEN, S., GHERARDINI, P. F., HERATI, R. S., HUANG, A. C., CHANG, K. M., NEWELL, E. W., BOVENSCHEN, N., PE'ER, D., ALBELDA, S. M. & WHERRY, E. J. 2018. Epigenomic-Guided Mass Cytometry Profiling Reveals Disease-Specific Features of Exhausted CD8 T Cells. Immunity, 48, 1029-1045 e5. [0157] BENNETT M L, BENNETT F C, LIDDELOW S A, AJAMI B, ZAMANIAN J L, FERNHOFF N B, MULINYAWE S B, BOHLEN C J, ADIL A, TUCKER A, WEISSMAN I L, CHANG E F, L I G, GRANT G A, HAYDEN GEPHART M G, BARRES B A. New tools for studying microglia in the mouse and human CNS. Proc Natl Acad Sci USA. 2016 Mar. 22; 113(12):E1738-46 [0158] BODER, E. T. & WITTRUP, K. D. 1997. Yeast surface display for screening combinatorial polypeptide libraries. Nat Biotechnol, 15, 553-7. [0159] BRAAT, H., ROTTIERS, P., HOMMES, D. W., HUYGHEBAERT, N., REMAUT, E., REMON, J. P., VAN DEVENTER, S. J., NEIRYNCK, S., PEPPELENBOSCH, M. P. & STEIDLER, L. 2006. A phase I trial with transgenic bacteria expressing interleukin-10 in Crohn's disease. Clin Gastroenterol Hepatol, 4, 754-9. [0160] BURUIANA, F. E., SOLA, I. & ALONSO-COELLO, P. 2010. Recombinant human interleukin 10 for induction of remission in Crohn's disease. Cochrane Database Syst Rev, CD005109. [0161] CARDOSO, A., GIL CASTRO, A., MARTINS, A. C., CARRICHE, G. M., MURIGNEUX, V., CASTRO, I., CUMANO, A., VIEIRA, P. & SARAIVA, M. 2018. The Dynamics of Interleukin-10-Afforded Protection during Dextran Sulfate Sodium-Induced Colitis. Front Immunol, 9, 400. [0162] CHAO, G., LAU, W. L., HACKEL, B. J., SAZINSKY, S. L., LIPPOW, S. M. & WITTRUP, K. D. 2006. Isolating and engineering human antibodies using yeast surface display. Nat Protoc, 1, 755-68. [0163] COLLIN M, BIGLEY V. Human dendritic cell subsets: an update. Immunology. 2018 May; 154(1):3-20. [0164] COLOMBEL, J. F., RUTGEERTS, P., MALCHOW, H., JACYNA, M., NIELSEN, O. H., RASK-MADSEN, J., VAN DEVENTER, S., FERGUSON, A., DESREUMAUX, P., FORBES, A., GEBOES, K., MELANI, L. & COHARD, M. 2001. Interleukin 10 (Tenovil) in the prevention of postoperative recurrence of Crohn's disease. Gut, 49, 42-6. [0165] CORREA, I., VENY, M., ESTELLER, M., PIQUE, J. M., YAGUE, J., PANES, J. & SALAS, A. 2009. Defective IL-10 production in severe phenotypes of Crohn's disease. J Leukoc Biol, 85, 896-903. [0166] COSTA-PEREIRA, A. P., TINININI, S., STROBL, B., ALONZI, T., SCHLAAK, J. F., IS'HARC, H., GESUALDO, I., NEWMAN, S. J., KERR, I. M. & POLI, V. 2002. Mutational switch of an IL-6 response to an interferon-gamma-like response. Proc Natl Acad Sci USA, 99, 8043-7. [0167] DALLAGI, A., GIROUARD, J., HAMELIN-MORRISSETTE, J., DADZIE, R., LAURENT, L., VAILLANCOURT, C., LAFOND, J., CARRIER, C. & REYES-MORENO, C. 2015. The activating effect of IFN-gamma on monocytes/macrophages is regulated by the LIF-trophoblast-IL-10 axis via Stat1 inhibition and Stat3 activation. Cell Mol Immunol, 12, 326-41 [0168] DE WAAL MALEFYT, R., ABRAMS, J., BENNETT, B., FIGDOR, C. G. & DE VRIES, J. E. 1991a. Interleukin 10 (IL-10) inhibits cytokine synthesis by human monocytes: an autoregulatory role of IL-10 produced by monocytes. J Exp Med, 174, 1209-20. [0169] DE WAAL MALEFYT, R., HAANEN, J., SPITS, H., RONCAROLO, M. G., T E VELDE, A., FIGDOR, C., JOHNSON, K., KASTELEIN, R., YSSEL, H. & D E VRIES, J. E. 1991b. Interleukin 10 (IL-10) and viral IL-10 strongly reduce antigen-specific human T cell proliferation by diminishing the antigen-presenting capacity of monocytes via downregulation of class II major histocompatibility complex expression. J Exp Med, 174, 915-24. [0170] DING, L., LINSLEY, P. S., HUANG, L. Y., GERMAIN, R. N. & SHEVACH, E. M. 1993. IL-10 inhibits macrophage costimulatory activity by selectively inhibiting the up-regulation of B7 expression. J Immunol, 151, 1224-34. [0171] DING, Y., QIN, L., ZAMARIN, D., KOTENKO, S. V., PESTKA, S., MOORE, K. W. & BROMBERG, J. S. 2001. Differential IL-10R1 expression plays a critical role in IL-10-mediated immune regulation. J Immunol, 167, 6884-92. [0172] EMMERICH, J., MUMM, J. B., CHAN, I. H., LAFACE, D., TRUONG, H., MCCLANAHAN, T., GORMAN, D. M. & OFT, M. 2012. IL-10 Directly Activates and Expands Tumor-Resident CD8(+) T Cells without De Novo Infiltration from Secondary Lymphoid Organs. Cancer Research, 72, 3570-3581. [0173] FARKAS S, HORNUNG M, SATTLER C, EDTINGER K, STEINBAUER M, ANTHUBER M, SCHLITT H J, HERFARTH H, GEISSLER E K. Blocking MAdCAM-1 in vivo reduces leukocyte extravasation and reverses chronic inflammation in experimental colitis. Int J Colorectal Dis. 2006 January; 21(1):71-8. [0174] FINBLOOM, D. S. & WINESTOCK, K. D. 1995. IL-10 induces the tyrosine phosphorylation of tyk2 and Jak1 and the differential assembly of STAT1 alpha and STAT3 complexes in human T cells and monocytes. J Immunol, 155, 1079-90. [0175] FIORENTINO, D. F., ZLOTNIK, A., MOSMANN, T. R., HOWARD, M. & O'GARRA, A. 1991a. IL-10 inhibits cytokine production by activated macrophages. J Immunol, 147, 3815-22. [0176] FIORENTINO, D. F., ZLOTNIK, A., VIEIRA, P., MOSMANN, T. R., HOWARD, M., MOORE, [0177] K. W. & O'GARRA, A. 1991b. IL-10 acts on the antigen-presenting cell to inhibit cytokine production by Th1 cells. J Immunol, 146, 3444-51. [0178] FRAIETTA, J. A., LACEY, S. F., ORLANDO, E. J., PRUTEANU-MALINICI, I., GOHIL, M., LUNDH, S., BOESTEANU, A. C., WANG, Y., O'CONNOR, R. S., HWANG, W. T., PEQUIGNOT, E., AMBROSE, D. E., ZHANG, C., WILCOX, N., BEDOYA, F., DORFMEIER, C., CHEN, F., TIAN, L., PARAKANDI, H., GUPTA, M., YOUNG, R. M., JOHNSON, F. B., KULIKOVSKAYA, I., LIU, L., XU, J., KASSIM, S. H., DAVIS, M. M., LEVINE, B. L., FREY, N. V., SIEGEL, D. L., HUANG, A. C., WHERRY, E. J., BITTER, H., BROGDON, J. L., PORTER, D. L., JUNE, C. H. & MELENHORST, J. J. 2018. Determinants of response and resistance to CD19 chimeric antigen receptor (CAR) T cell therapy of chronic lymphocytic leukemia. Nat Med, 24, 563-571. [0179] GONEN T, GUZEL S, KESKINBORA K H. YKL-40 is a local marker for inflammation in patients with pseudoexfoliation syndrome. Eye (Lond). 2019 May; 33(5):772-776. [0180] HUANG DA, W., SHERMAN, B. T. & LEMPICKI, R. A. 2009a. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res, 37, 1-13. [0181] HUANG DA, W., SHERMAN, B. T. & LEMPICKI, R. A. 2009b. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc, 4, 44-57. [0182] IP, W. K. E., HOSHI, N., SHOUVAL, D. S., SNAPPER, S. & MEDZHITOV, R. 2017. Anti-inflammatory effect of IL-10 mediated by metabolic reprogramming of macrophages. Science, 356, 513-519. [0183] ITO, S., ANSARI, P., SAKATSUME, M., DICKENSHEETS, H., VAZQUEZ, N., DONNELLY, R. P., LARNER, A. C. & FINBLOOM, D. S. 1999. Interleukin-10 inhibits expression of both interferon alpha- and interferon gamma-induced genes by suppressing tyrosine phosphorylation of STAT1. Blood, 93, 1456-63. [0184] JIN K, LUO Z, ZHANG B, PANG Z. Biomimetic nanoparticles for inflammation targeting. Acta Pharm Sin B. 2018 January; 8(1):23-33. [0185] JOSEPHSON, K., DIGIACOMO, R., INDELICATO, S. R., IYO, A. H., NAGABHUSHAN, T. L., PARKER, M. H., WALTER, M. R. & AYO, A. H. 2000. Design and analysis of an engineered human interleukin-10 monomer. J Biol Chem, 275, 13552-7. [0186] KELLY T, HUANG Y, SIMMS AE, MAZUR A. Fibroblast activation protein-α: a key modulator of the microenvironment in multiple pathologies. Int Rev Cell Mol Biol. 2012; 297:83-116. [0187] KIRCHER M, HERHAUS P, SCHOTTELIUS M, BUCK A K, WERNER R A, WESTER H J, KELLER U, LAPA C. CXCR4-directed theranostics in oncology and inflammation. Ann Nucl Med. 2018 October; 32(8):503-511. [0188] KIRCHHOFER, A., HELMA, J., SCHMIDTHALS, K., FRAUER, C., CUI, S., KARCHER, A., PELLIS, M., MUYLDERMANS, S., CASAS-DELUCCHI, C. S., CARDOSO, M. C., LEONHARDT, H., HOPFNER, K. P. & ROTHBAUER, U. 2010. Modulation of protein properties in living cells using nanobodies. Nature Structural & Molecular Biology, 17, 133-U162. [0189] KRUTZIK, P. O. & NOLAN, G. P. 2006. Fluorescent cell barcoding in flow cytometry allows high-throughput drug screening and signaling profiling. Nat Methods, 3, 361-8. [0190] LAPORTE, S. L., JUO, Z. S., VACLAVIKOVA, J., COLF, L. A., QI, X., HELLER, N. M., KEEGAN, A. D. & GARCIA, K. C. 2008. Molecular and structural basis of cytokine receptor pleiotropy in the interleukin-4/13 system. Cell, 132, 259-72. [0191] LEMAŃSKA-PEREK A, ADAMIK B. Fibronectin and its soluble EDA-FN isoform as biomarkers for inflammation and sepsis. Adv Clin Exp Med. 2019 November; 28(11):1561-1567. [0192] LOGSDON, N. J., JONES, B. C., JOSEPHSON, K., COOK, J. & WALTER, M. R. 2002. Comparison of interleukin-22 and interleukin-10 soluble receptor complexes. J Interferon Cytokine Res, 22, 1099-112. [0193] MANNINO, M. H., ZHU, Z., XIAO, H., BAI, Q., WAKEFIELD, M. R. & FANG, Y. 2015. The paradoxical role of IL-10 in immunity and cancer. Cancer Lett, 367, 103-7. [0194] MARTINEZ-FABREGAS, J., WILMES, S., WANG, L., HAFER, M., POHLER, E., LOKAU, J., GARBERS, C., COZZANI, A., FYFE, P. K., PIEHLER, J., KAZEMIAN, M., MITRA, S. & MORAGA, I. 2019. Kinetics of cytokine receptor trafficking determine signaling and functional selectivity. Elife, 8. [0195] MEJIAS-LUQUE R, LINDÉN S K, GARRIDO M, TYE H, NAJDOVSKA M, JENKINS B J, IGLESIAS M, ERNST M, DE BOLOS C. Inflammation modulates the expression of the intestinal mucins MUC2 and MUC4 in gastric tumors. Oncogene. 2010 Mar. 25; 29(12):1753-62. [0196] MENDOZA, J. L., SCHNEIDER, W. M., HOFFMANN, H. H., VERCAUTEREN, K., JUDE, K. M., XIONG, A., MORAGA, I., HORTON, T. M., GLENN, J. S., DE JONG, Y. P., RICE, C. M. & GARCIA, K. C. 2017. The IFN-λ-IFN-λR1-IL-10Rβ Complex Reveals Structural Features Underlying Type III IFN Functional Plasticity. Immunity, 46, 379-392. [0197] MITTAL, S. K. & ROCHE, P. A. 2015. Suppression of antigen presentation by IL-10. Curr Opin Immunol, 34, 22-7. [0198] MOORE, K. W., DE WAAL MALEFYT, R., COFFMAN, R. L. & O'GARRA, A. 2001. Interleukin-10 and the interleukin-10 receptor. Annu Rev Immunol, 19, 683-765. [0199] MORAGA, I., RICHTER, D., WILMES, S., WINKELMANN, H., JUDE, K., THOMAS, C., SUHOSKI, M. M., ENGLEMAN, E. G., PIEHLER, J. & GARCIA, K. C. 2015a. Instructive roles for cytokine-receptor binding parameters in determining signaling and functional potency. Science Signaling, 8. [0200] MORAGA, I., RICHTER, D., WILMES, S., WINKELMANN, H., JUDE, K., THOMAS, C., SUHOSKI, M. M., ENGLEMAN, E. G., PIEHLER, J. & GARCIA, K. C. 2015b. Instructive roles for cytokine-receptor binding parameters in determining signaling and functional potency. Sci Signal, 8, ra114. [0201] MORAGA, I., WERNIG, G., WILMES, S., GRYSHKOVA, V., RICHTER, C. P., HONG, W. J., SINHA, R., GUO, F., FABIONAR, H., WEHRMAN, T. S., KRUTZIK, P., DEMHARTER, S., PLO, I., WEISSMAN, I. L., MINARY, P., MAJETI, R., CONSTANTINESCU, S. N., PIEHLER, J. & GARCIA, K. C. 2015c. Tuning cytokine receptor signaling by re-orienting dimer geometry with surrogate ligands. Cell, 160, 1196-208. [0202] MOUTEL S, BEUGNET A, SCHNEIDER A, LOMBARD B, LOEW D, AMIGORENA S, PEREZ F, SEGURA E. Surface LSP-1 Is a Phenotypic Marker Distinguishing Human Classical versus Monocyte-Derived Dendritic Cells. iScience. 2020 Apr. 24; 23(4):100987 [0203] MUMM, J. B., EMMERICH, J., ZHANG, X., CHAN, I., WU, L., MAUZE, S., BLAISDELL, S., BASHAM, B., DAI, J., GREIN, J., SHEPPARD, C., HONG, K., CUTLER, C., TURNER, S., LAFACE, D., KLEINSCHEK, M., JUDO, M., AYANOGLU, G., LANGOWSKI, J., GU, D., PAPORELLO, B., MURPHY, E., SRIRAM, V., NARAVULA, S., DESAI, B., MEDICHERLA, S., SEGHEZZI, W., MCCLANAHAN, T., CANNON-CARLSON, S., BEEBE, A. M. & OFT, M. 2011. IL-10 elicits IFNgamma-dependent tumor immune surveillance. Cancer Cell, 20, 781-96. [0204] MUMM, J. B. & OFT, M. 2013. Pegylated IL-10 induces cancer immunity: the surprising role of IL-10 as a potent inducer of IFN-γ-mediated CD8(+) T cell cytotoxicity. Bioessays, 35, 623-31. [0205] NAING, A., INFANTE, J. R., PAPADOPOULOS, K. P., CHAN, I. H., SHEN, C., RATTI, N. P., ROJO, B., AUTIO, K. A., WONG, D. J., PATEL, M. R., OTT, P. A., FALCHOOK, G. S., PANT, S., HUNG, A., PEKAREK, K. L., WU, V., ADAMOW, M., MCCAULEY, S., MUMM, J. B., WONG, P., VAN VLASSELAER, P., LEVEQUE, J., TANNIR, N. M. & OFT, M. 2018. PEGylated IL-10 (Pegilodecakin) Induces Systemic Immune Activation, CD8. Cancer Cell, 34, 775-791.e3.
[0206] NAING, A., WONG, D. J., INFANTE, J. R., KORN, W. M., ALJUMAILY, R., PAPADOPOULOS, K. P., AUTIO, K. A., PANT, S., BAUER, T. M., DRAKAKI, A., DAVER, N. G., HUNG, A., RATTI, N., MCCAULEY, S., VAN VLASSELAER, P., VERMA, R., FERRY, D., OFT, M., DIAB, A., GARON, E. B. & TANNIR, N. M. 2019. Pegilodecakin combined with pembrolizumab or nivolumab for patients with advanced solid tumours (IVY): a multicentre, multicohort, open-label, phase 1b trial. Lancet Oncol, 20, 1544-1555. [0207] OFT, M. 2014. IL-10: master switch from tumor-promoting inflammation to antitumor immunity. Cancer Immunol Res, 2, 194-9. [0208] OFT, M. 2019. Immune regulation and cytotoxic T cell activation of IL-10 agonists—Preclinical and clinical experience. Semin Immunol, 44, 101325. [0209] RAY, J. P., MARSHALL, H. D., LAIDLAW, B. J., STARON, M. M., KAECH, S. M. & CRAFT, J. 2014. Transcription factor STAT3 and type I interferons are corepressive insulators for differentiation of follicular helper and T helper 1 cells. Immunity, 40, 367-77. [0210] RHODES J W, TONG O, HARMAN A N, TURVILLE S G. Human Dendritic Cell Subsets, Ontogeny, and Impact on HIV Infection. Front Immunol. 2019 May 16; 10:1088. [0211] ROLLINGS, C. M., SINCLAIR, L. V., BRADY, H. J. M., CANTRELL, D. A. & ROSS, S. H. 2018. Interleukin-2 shapes the cytotoxic T cell proteome and immune environment-sensing programs. Sci Signal, 11. [0212] SAXENA, A., KHOSRAVIANI, S., NOEL, S., MOHAN, D., DONNER, T. & HAMAD, A. R. 2015. Interleukin-10 paradox: A potent immunoregulatory cytokine that has been difficult to harness for immunotherapy. Cytokine, 74, 27-34. [0213] SAXENA M, BHARDWAJ N. Turbocharging vaccines: emerging adjuvants for dendritic cell based therapeutic cancer vaccines. Curr Opin Immunol. 2017 August; 47:35-43. [0214] SHIGEMORI, S. & SHIMOSATO, T. 2017. Applications of Genetically Modified Immunobiotics with High Immunoregulatory Capacity for Treatment of Inflammatory Bowel Diseases. Front Immunol, 8, 22. [0215] SIEW J J, CHEN H M, CHEN H Y, CHEN H L, CHEN C M, SOONG B W, WU Y R, CHANG C P, CHAN Y C, LIN C H, LIU F T, CHERN Y. Galectin-3 is required for the microglia-mediated brain inflammation in a model of Huntington's disease. Nat Commun. 2019 Aug. 2; 10(1):3473. [0216] SPANGLER, J. B., MORAGA, I., JUDE, K. M., SAWIDES, C. S., AND GARCIA, K. C. (2019). A strategy for the selection of monovalent antibodies that span protein dimer interfaces. J Biol Chem 294, 13876-13886. [0217] STEIDLER, L., HANS, W., SCHOTTE, L., NEIRYNCK, S., OBERMEIER, F., FALK, W., FIERS, W. & REMAUT, E. 2000. Treatment of murine colitis by Lactococcus lactis secreting interleukin-10. Science, 289, 1352-5. [0218] TAN, J. C., INDELICATO, S. R., NARULA, S. K., ZAVODNY, P. J., AND CHOU, C. C. (1993). Characterization of interleukin-10 receptors on human and mouse cells. J Biol Chem 268, 21053-21059. [0219] WALTER, M. R. 2014. The molecular basis of IL-10 function: from receptor structure to the onset of signaling. Curr Top Microbiol Immunol, 380, 191-212. [0220] WEHINGER, J., GOUILLEUX, F., GRONER, B., FINKE, J., MERTELSMANN, R. & WEBER-NORDT, R. M. 1996. IL-10 induces DNA binding activity of three STAT proteins (Stat1, Stat3, and Stat5) and their distinct combinatorial assembly in the promoters of selected genes. FEBS Lett, 394, 365-70. [0221] WILLEMS, F., MARCHANT, A., DELVILLE, J. P., GERARD, C., DELVAUX, A., VELU, T., D E BOER, M. & GOLDMAN, M. 1994. Interleukin-10 inhibits B7 and intercellular adhesion molecule-1 expression on human monocytes. Eur J Immunol, 24, 1007-9. [0222] WILMES, S., BEUTEL, O., LI, Z., FRANCOIS-NEWTON, V., RICHTER, C. P., JANNING, D., KROLL, C., HANHART, P., HOTTE, K., YOU, C., UZE, G., PELLEGRINI, S. & PIEHLER, J. 2015. Receptor dimerization dynamics as a regulatory valve for plasticity of type I interferon signaling. J Cell Biol, 209, 579-93. [0223] WILMES, S., HAFER, M., VUORIO, J., TUCKER, J. A., WINKELMANN, H., LOCHTE, S., STANLY, T. A., PULGAR PRIETO, K. D., POOJARI, C., SHARMA, V., RICHTER, C. P., KURRE, R., HUBBARD, S. R., GARCIA, K. C., MORAGA, I., VATTULAINEN, I., HITCHCOCK, I. S. & PIEHLER, J. 2020. Mechanism of homodimeric cytokine receptor activation and dysregulation by oncogenic mutations. Science, 367, 643-652. [0224] YANG, X. P., GHORESCHI, K., STEWARD-THARP, S. M., RODRIGUEZ-CANALES, J., ZHU, J., GRAINGER, J. R., HIRAHARA, K., SUN, H. W., WEI, L., VAHEDI, G., KANNO, Y., O'SHEA, J. J. & LAURENCE, A. 2011. Opposing regulation of the locus encoding IL-17 through direct, reciprocal actions of STAT3 and STAT5. Nat Immunol, 12, 247-54. [0225] YAZDANI S, BANSAL R, PRAKASH J. Drug targeting to myofibroblasts: Implications for fibrosis and cancer. Adv Drug Deliv Rev. 2017 Nov. 1; 121:101-116. [0226] YUE, F. Y., DUMMER, R., GEERTSEN, R., HOFBAUER, G., LAINE, E., MANOLIO, S. & BURG, G. 1997. Interleukin-10 is a growth factor for human melanoma cells and down-regulates HLA class-I, HLA class-II and ICAM-1 molecules. Int J Cancer, 71, 630-7. [0227] ZHAO, S., WU, D., WU, P., WANG, Z. & HUANG, J. 2015. Serum IL-10 Predicts Worse Outcome in Cancer Patients: A Meta-Analysis. PLoS One, 10, e0139598. [0228] ZHU, L., SHI, T., ZHONG, C., WANG, Y., CHANG, M. & LIU, X. 2017. IL-10 and IL-10 Receptor Mutations in Very Early Onset Inflammatory Bowel Disease. Gastroenterology Res, 10, 65-69.