The effect of low-dose IL-2 and Treg adoptive cell therapy in patients with type 1 diabetes

Shen Dong, Kamir J Hiam-Galvez, Cody T Mowery, Kevan C Herold, Stephen E Gitelman, Jonathan H Esensten, Weihong Liu, Angela P Lares, Ashley S Leinbach, Michael Lee, Vinh Nguyen, Stanley J Tamaki, Whitney Tamaki, Courtney M Tamaki, Morvarid Mehdizadeh, Amy L Putnam, Matthew H Spitzer, Chun Jimmie Ye, Qizhi Tang, Jeffrey A Bluestone, Shen Dong, Kamir J Hiam-Galvez, Cody T Mowery, Kevan C Herold, Stephen E Gitelman, Jonathan H Esensten, Weihong Liu, Angela P Lares, Ashley S Leinbach, Michael Lee, Vinh Nguyen, Stanley J Tamaki, Whitney Tamaki, Courtney M Tamaki, Morvarid Mehdizadeh, Amy L Putnam, Matthew H Spitzer, Chun Jimmie Ye, Qizhi Tang, Jeffrey A Bluestone

Abstract

BACKGROUNDA previous phase I study showed that the infusion of autologous Tregs expanded ex vivo into patients with recent-onset type 1 diabetes (T1D) had an excellent safety profile. However, the majority of the infused Tregs were undetectable in the peripheral blood 3 months postinfusion (Treg-T1D trial). Therefore, we conducted a phase I study (TILT trial) combining polyclonal Tregs and low-dose IL-2, shown to enhance Treg survival and expansion, and assessed the impact over time on Treg populations and other immune cells.METHODSPatients with T1D were treated with a single infusion of autologous polyclonal Tregs followed by one or two 5-day courses of recombinant human low-dose IL-2 (ld-IL-2). Flow cytometry, cytometry by time of flight, and 10x Genomics single-cell RNA-Seq were used to follow the distinct immune cell populations' phenotypes over time.RESULTSMultiparametric analysis revealed that the combination therapy led to an increase in the number of infused and endogenous Tregs but also resulted in a substantial increase from baseline in a subset of activated NK, mucosal associated invariant T, and clonal CD8+ T cell populations.CONCLUSIONThese data support the hypothesis that ld-IL-2 expands exogenously administered Tregs but also can expand cytotoxic cells. These results have important implications for the use of a combination of ld-IL-2 and Tregs for the treatment of autoimmune diseases with preexisting active immunity.TRIAL REGISTRATIONClinicalTrials.gov NCT01210664 (Treg-T1D trial), NCT02772679 (TILT trial).FUNDINGSean N. Parker Autoimmune Research Laboratory Fund, National Center for Research Resources.

Keywords: Autoimmunity; Clinical Trials; Diabetes; Immunotherapy; T cells.

Conflict of interest statement

Conflict of interest: JAB is a member of the scientific advisory boards of Arcus Biosciences, Solid Biosciences, and VIR Biotechnology and a member of the board of directors of both Gilead Sciences and Provention Bio. JAB is cofounder, president, and CEO of Sonoma Biotherapeutics, a company developing Treg-based cell therapies for the treatment of autoimmune diseases. JAB has a patent 62/667,981 licensed to Juno, a patent 62/744,058 pending, a patent 7,722,862 issued to Sonoma Biotherapeutics, a patent 9,012,134 issued to Sonoma Biotherapeutics, a patent 62/629,103 pending, and a patent 20060292142 issued to Provention Bio. KCH has consulted for Roche Pharmaceuticals. SEG has consulted for Biolojic, Caladrius Biosciences, Roche Pharmaceuticals, Avotres, Immunomolecular Therapeutics, and Tolerion. MHS receives research funding from Genentech (Roche), Bristol Myers Squibb, and Valitor and has been a paid consultant for Five Prime Therapeutics, and Ono Pharmaceutical, and January Inc. QT is a cofounder of Sonoma Biotherapeutics.

Figures

Figure 1. Metabolic assessments.
Figure 1. Metabolic assessments.
(A) (Left column) C-peptide AUC is reported for fasting 4-hour mixed meal tolerance test (MMTT) without carbohydrate restriction for 3 days preceding testing. The target glucose level at the start of the test was between 70 and 200 mg/dL. Regular insulin or short-acting insulin analogs were allowed up to 6 and 2 hours before the test, respectively, to achieve the desired glucose level. The baseline blood samples (−10 minutes and 0 minutes) were drawn, and then patients drank Boost high protein nutritional energy drink (Nestle Nutrition) at 6 kcal/kg (1 kcal/mL) to a maximum of 360 mL. Blood was drawn at 15, 30, 60, 90, 120, 150, 180, 210, and 240 minutes following Boost dose. C-peptide AUC was calculated using the trapezoid rule. (Middle column) Hemoglobin A1c (HbA1c). (Right column) Insulin use. Insulin use for the 3 days immediately preceding the scheduled visit was self-reported. The average total insulin (long acting + short acting) use per day normalized to weight is reported. Table shows Treg and IL-2 dosage of each patient. MIU, million international units. (B) Percentage of relative C-peptide loss up to 104 and 78 weeks in patients from cohorts 1 and 2, respectively, of the TILT trial (2 left graphs) and from the placebo cohort of the AIDA and NT-14 trial (right graph). (C) Comparison of percentage of relative C-peptide loss at the indicated time point between the patients from TILT and placebo groups.
Figure 2. Longitudinal tracking of in vitro–expanded…
Figure 2. Longitudinal tracking of in vitro–expanded Tregs postinfusion.
(A) Graphs show the percentage of DNA enrichment with deuterium (2H) in PBMC sorted Treg cells from TILT trial patients. Enlarged view of the 2H labeling kinetics up to 63 days is represented in the upper right of each graph. Black dashed lines indicate the fifth day of each IL-2 infusion course. Table shows Treg and IL-2 dosage of each patient. (B) Graphs show the percentage of deuterated DNA enrichment normalized to the maximum value in total PBMCs over time in each patient from the TILT trial. Light blue lines and gray areas show superimposition to normalized percentage of deuterated DNA enrichment of the T1D trial. Table shows Treg dosage. (C) Percentage of 2H level in postinfusion sorted non-Tregs versus Tregs in TILT trial patients. Paired 2-tailed t tests were performed in order to assess statistical significance. *P < 0.05.
Figure 3. Low-dose IL-2 induces activation phenotype…
Figure 3. Low-dose IL-2 induces activation phenotype in the Treg subset at a protein level.
(A) Graphs represent the percentage of Tregs (left column) by flow cytometry at the indicated time points. TILT trial patient data are shown in upper graphs, and the Treg-T1D trial patients are represented in the lower graphs. Red asterisks indicate patients who received only 1 dose of IL-2. Tables indicate dosage of IL-2 and Tregs for each patient. Paired 2-tailed t tests were performed in order to assess statistical significance. (B and C) Percentage of FOXP3+ and median expression of FOXP3+ as well as median expression of CD27, CTLA-4, and HLA-DR was assessed by CyTOF. Data were normalized; cell populations were gated manually in CellEngine. Populations were then exported for analysis in R, and marker expression values were then arsinh-transformed with a cofactor of 5 and represented in dot plots. The results are plotted into 2 separated batches (batches 1 and 2) due to batch effect affecting the comparison of the samples within the same analysis pipeline (batches layout of the samples, Supplemental Table 3). Asterisks indicate significance relative to the control group determined by 1-way ANOVA. ***P < 0.001; ****P < 0.0001.
Figure 4. Low-dose IL-2 induces activation phenotype…
Figure 4. Low-dose IL-2 induces activation phenotype in the Treg subset at the mRNA level.
10x Genomics single-cell RNA-Seq data were analyzed by Scanpy package. (A) UMAPs show expression of FOXP3 in cluster 11 from UMAP in Supplemental Figure 2 in the TILT patient samples and Treg-T1D patient samples. (B) Volcano plots represent differential gene expression analysis of the Treg cell compartment (Supplemental Figure 2, cluster 11) from TILT and Treg-T1D patients at day 0 (left volcano plot) and day 7 (right volcano plot). Downregulated (red dots) and upregulated genes (green dots) are indicated in log2(fold change) (log2FC) with a P < 0.005. Gene expressions with P values greater than 0.005 were filtered out. Vertical dashed lines represent thresholds of log2FC of –0.6 and 0.6 corresponding to a fold change of 1.5 times. Table indicates the log2FC values of the indicated genes. Blue cells indicate nonsignificant genes filtered out due to a P > 0.005. (C) Dot plot shows longitudinal changes over time of percentage of FOXP3+ cells in cluster 11 for the 2 trials. Asterisks indicate significance relative to the control group determined by 1-way ANOVA. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001. (D) Graphs represent mean mRNA expression of the indicated genes normalized to day 0 for the patients of each clinical trial group (TILT in upper graphs and Treg-T1D in lower graphs). Red asterisks indicate patients that received only 1 dose of IL-2. (E) UMAP and leiden clustering of the Treg cluster 11. Heatmap shows Treg markers’ and activation markers’ mean expression in the indicated clusters. Stacked bar chart shows the percentage of cells in each cluster in Treg-T1D versus TILT patients.
Figure 5. Low-dose IL-2 induces cytotoxic phenotype…
Figure 5. Low-dose IL-2 induces cytotoxic phenotype in the NK cell subset and mucosal invariant associated T cell subset.
10x Genomics single-cell RNA-Seq data were analyzed by Scanpy package. (A) Volcano plots represent differential gene expression analysis of the NK cell compartment (Supplemental Figure 2, cluster 4) from TILT and Treg-T1D patients at day 0 (left volcano plot) and day 7 (right volcano plot). Downregulated (red dots) and upregulated genes (green dots) are indicated in log2FC with a P < 0.005. Gene expressions with P values greater than 0.005 were filtered out. Vertical dashed lines represent thresholds of log2FC of –0.6 and 0.6 corresponding to a fold change of 1.5 times. Table indicates the log2FC values of the indicated genes. Blue cells indicate nonsignificant genes filtered out due to a P > 0.005. (B) Percentage of GZMB+ cells in the NK cluster (Supplemental Figure 2, cluster 4) were calculated and shown on upper graphs for TILT trial patients and lower graphs for Treg-T1D trial patients. Tables indicate dosage of IL-2 and Tregs for each patient. (C) Dot plot represents percentage over time of GZMB+ cells in NK clusters in TILT and Treg-T1D trial patients. Asterisks indicate significance relative to the control group determined by 1-way ANOVA. *P < 0.05. (D) Graphs show correlation of day 0 to day 28 changes in the percentage of GZMB+ NK and day 0 to day 7 changes in the percentage of FOXP3+ Treg cells in TILT patients (upper graph) and Treg-T1D patients (lower graph). (E) Volcano plots represent differential gene expression analysis of the MAIT cell compartment (Supplemental Figure 2, cluster 6) from TILT and Treg-T1D patients at day 0 (left volcano plot) and day 7 (right volcano plot). Table indicates the log2FC values of the indicated genes. Blue cells indicate nonsignificant genes filtered out due to a P > 0.005.
Figure 6. Low-dose IL-2 treatment promotes a…
Figure 6. Low-dose IL-2 treatment promotes a cytotoxic phenotype in the CD8+ T cell subset.
(A) Flow cytometry analysis shows the percentage of total CD3+CD8+ T cells (left column) and CD8+CD25+ T cells (right column) at the collected time points. Upper graphs represent patients from the TILT trials, and lower graphs represent patients from the Treg-T1D trial. The table indicates the dosage of IL-2 and Tregs for each patient. (B) Single-cell RNA-Seq data were analyzed by Scanpy package. Volcano plots represent differential gene expression analysis of the PRF1+GZMB+CD8 T cell compartment (Supplemental Figure 2, cluster 5) from TILT and Treg-T1D patients at day 0 (left volcano plot) and day 7 (right volcano plot). Downregulated (red dots) and upregulated genes (green dots) are indicated in log2FC with a P < 0.005. Gene expressions with a P values greater than 0.005 were filtered out. Vertical dashed lines represent thresholds of log2FC of –0.6 and 0.6 corresponding to a fold change of 1.5 times. Table indicates the log2FC values of the indicated genes. Blue cells indicate non-significant genes filtered out due to a P > 0.005. (C) Table indicates the log2FC values of the indicated genes. Blue cells indicate nonsignificant genes filtered out due to a P > 0.005. (D) Dot plot shows PRF1 mRNA mean expression over time in PRF1+GZMB+CD8+ T cell cluster in TILT and Treg-T1D trial patients. Asterisks indicate significance relative to the control group determined by 1-way ANOVA. *P < 0.05.
Figure 7. Low-dose IL-2 increases clonal expansion…
Figure 7. Low-dose IL-2 increases clonal expansion of the PRF1+GZMB+CD8+ T cell compartment.
(A) Clonal diversity from the Treg, PRF1+GZMB+CD8 T cell, and total CD3+ populations was evaluated by the calculation of the Gini index. Dot plots show values of Gini index for each patient from the TILT and the Treg-T1D trial. Unpaired 2-tailed t tests were performed in order to assess statistical significance. (B) Left UMAP plot represents clusters of immune cells identified in Supplemental Figure 2. Density plots on the right represent mapping of TCR clones expanded more than 30 times in each clinical trial group. (C) Heatmaps represent cytotoxicity and activation markers gene expression (log normalized) of all the cells expressing expanded TCRs. Left y axis links the patient to the depicted expanded TCRs.

References

    1. Bluestone JA, et al. Genetics, pathogenesis and clinical interventions in type 1 diabetes. Nature. 2010;464(7293):1293–1300. doi: 10.1038/nature08933.
    1. Menke A, et al. The prevalence of type 1 diabetes in the United States. Epidemiology. 2013;24(5):773–774. doi: 10.1097/EDE.0b013e31829ef01a.
    1. Miller KM, et al. Current state of type 1 diabetes treatment in the U.S.: updated data from the T1D Exchange clinic registry. Diabetes Care. 2015;38(6):971–978. doi: 10.2337/dc15-0078.
    1. Brusko TM, et al. Functional defects and the influence of age on the frequency of CD4+ CD25+ T-cells in type 1 diabetes. Diabetes. 2005;54(5):1407–1414. doi: 10.2337/diabetes.54.5.1407.
    1. Lindley S, et al. Defective suppressor function in CD4(+)CD25(+) T-cells from patients with type 1 diabetes. Diabetes. 2005;54(1):92–99. doi: 10.2337/diabetes.54.1.92.
    1. Long SA, et al. Defects in IL-2R signaling contribute to diminished maintenance of FOXP3 expression in CD4(+)CD25(+) regulatory T-cells of type 1 diabetic subjects. Diabetes. 2010;59(2):407–415. doi: 10.2337/db09-0694.
    1. Marwaha AK, et al. Cutting edge: increased IL-17-secreting T cells in children with new-onset type 1 diabetes. J Immunol. 2010;185(7):3814–3818. doi: 10.4049/jimmunol.1001860.
    1. McClymont SA, et al. Plasticity of human regulatory T cells in healthy subjects and patients with type 1 diabetes. J Immunol. 2011;186(7):3918–3926. doi: 10.4049/jimmunol.1003099.
    1. Schneider A, et al. The effector T cells of diabetic subjects are resistant to regulation via CD4+ FOXP3+ regulatory T cells. J Immunol. 2008;181(10):7350–7355. doi: 10.4049/jimmunol.181.10.7350.
    1. Buckner JH. Mechanisms of impaired regulation by CD4(+)CD25(+)FOXP3(+) regulatory T cells in human autoimmune diseases. Nat Rev Immunol. 2010;10(12):849–859. doi: 10.1038/nri2889.
    1. Tang Q, Bluestone JA. Regulatory T-cell therapy in transplantation: moving to the clinic. Cold Spring Harb Perspect Med. 2013;3(11):a015552. doi: 10.1101/cshperspect.a015552.
    1. Bluestone JA, et al. Type 1 diabetes immunotherapy using polyclonal regulatory T cells. Sci Transl Med. 2015;7(315):315ra189. doi: 10.1126/scitranslmed.aad4134.
    1. Webb GJ, Hirschfield GM. Using GWAS to identify genetic predisposition in hepatic autoimmunity. J Autoimmun. 2016;66:25–39. doi: 10.1016/j.jaut.2015.08.016.
    1. Yu A, Malek TR. Selective availability of IL-2 is a major determinant controlling the production of CD4+CD25+Foxp3+ T regulatory cells. J Immunol. 2006;177(8):5115–5121. doi: 10.4049/jimmunol.177.8.5115.
    1. Boyman O, Sprent J. The role of interleukin-2 during homeostasis and activation of the immune system. Nat Rev Immunol. 2012;12(3):180–190. doi: 10.1038/nri3156.
    1. Weist BM, et al. Thymic regulatory T cell niche size is dictated by limiting IL-2 from antigen-bearing dendritic cells and feedback competition. Nat Immunol. 2015;16(6):635–641. doi: 10.1038/ni.3171.
    1. Liao W, et al. Interleukin-2 at the crossroads of effector responses, tolerance, and immunotherapy. Immunity. 2013;38(1):13–25. doi: 10.1016/j.immuni.2013.01.004.
    1. Roth TL, et al. Reprogramming human T cell function and specificity with non-viral genome targeting. Nature. 2018;559(7714):405–409. doi: 10.1038/s41586-018-0326-5.
    1. Grinberg-Bleyer Y, et al. IL-2 reverses established type 1 diabetes in NOD mice by a local effect on pancreatic regulatory T cells. J Exp Med. 2010;207(9):1871–1878. doi: 10.1084/jem.20100209.
    1. Tang Q, et al. Central role of defective interleukin-2 production in the triggering of islet autoimmune destruction. Immunity. 2008;28(5):687–697. doi: 10.1016/j.immuni.2008.03.016.
    1. Koreth J, et al. Interleukin-2 and regulatory T cells in graft-versus-host disease. N Engl J Med. 2011;365(22):2055–2066. doi: 10.1056/NEJMoa1108188.
    1. Matsuoka KI. Low-dose interleukin-2 as a modulator of Treg homeostasis after HSCT: current understanding and future perspectives. Int J Hematol. 2018;107(2):130–137. doi: 10.1007/s12185-017-2386-y.
    1. Zhao C, et al. Low dose of IL-2 combined with rapamycin restores and maintains the long-term balance of Th17/Treg cells in refractory SLE patients. BMC Immunol. 2019;20(1):32. doi: 10.1186/s12865-019-0305-0.
    1. He J, et al. Efficacy and safety of low-dose IL-2 in the treatment of systemic lupus erythematosus: a randomised, double-blind, placebo-controlled trial. Ann Rheum Dis. 2020;79(1):141–149. doi: 10.1136/annrheumdis-2019-215396.
    1. Spolski R, et al. Biology and regulation of IL-2: from molecular mechanisms to human therapy. Nat Rev Immunol. 2018;18(10):648–659. doi: 10.1038/s41577-018-0046-y.
    1. Cabrera SM, et al. Interleukin-1 antagonism moderates the inflammatory state associated with Type 1 diabetes during clinical trials conducted at disease onset. Eur J Immunol. 2016;46(4):1030–1046. doi: 10.1002/eji.201546005.
    1. Moran A, et al. Interleukin-1 antagonism in type 1 diabetes of recent onset: two multicentre, randomised, double-blind, placebo-controlled trials. Lancet. 2013;381(9881):1905–1915. doi: 10.1016/S0140-6736(13)60023-9.
    1. Hartemann A, et al. Low-dose interleukin 2 in patients with type 1 diabetes: a phase 1/2 randomised, double-blind, placebo-controlled trial. Lancet Diabetes Endocrinol. 2013;1(4):295–305. doi: 10.1016/S2213-8587(13)70113-X.
    1. Hirakawa M, et al. Low-dose IL-2 selectively activates subsets of CD4+ Tregs and NK cells. JCI Insight. 2016;1(18):89278.
    1. Matsuoka K, et al. Low-dose interleukin-2 therapy restores regulatory T cell homeostasis in patients with chronic graft-versus-host disease. Sci Transl Med. 2013;5(179):179ra43.
    1. Kang HM, et al. Multiplexed droplet single-cell RNA-sequencing using natural genetic variation. Nat Biotechnol. 2018;36(1):89–94. doi: 10.1038/nbt.4042.
    1. Rosenblum MD, et al. Regulatory T cell memory. Nat Rev Immunol. 2016;16(2):90–101. doi: 10.1038/nri.2015.1.
    1. Yu A, et al. A low interleukin-2 receptor signaling threshold supports the development and homeostasis of T regulatory cells. Immunity. 2009;30(2):204–217. doi: 10.1016/j.immuni.2008.11.014.
    1. Saadoun D, et al. Regulatory T-cell responses to low-dose interleukin-2 in HCV-induced vasculitis. N Engl J Med. 2011;365(22):2067–2077. doi: 10.1056/NEJMoa1105143.
    1. Rosenzwajg M, et al. Low-dose interleukin-2 fosters a dose-dependent regulatory T cell tuned milieu in T1D patients. J Autoimmun. 2015;58:48–58. doi: 10.1016/j.jaut.2015.01.001.
    1. Carnero Contentti E, et al. Mucosal-associated invariant T cell features and TCR repertoire characteristics during the course of multiple sclerosis. Front Immunol. 2019;10:2690.
    1. Reantragoon R, et al. Antigen-loaded MR1 tetramers define T cell receptor heterogeneity in mucosal-associated invariant T cells. J Exp Med. 2013;210(11):2305–2320. doi: 10.1084/jem.20130958.
    1. Gulden E, et al. MAIT cells: a link between gut integrity and type 1 diabetes. Cell Metab. 2017;26(6):813–815. doi: 10.1016/j.cmet.2017.11.007.
    1. Rouxel O, et al. Cytotoxic and regulatory roles of mucosal-associated invariant T cells in type 1 diabetes. Nat Immunol. 2017;18(12):1321–1331. doi: 10.1038/ni.3854.
    1. Toubal A, et al. Mucosal-associated invariant T cells and disease. Nat Rev Immunol. 2019;19(10):643–657. doi: 10.1038/s41577-019-0191-y.
    1. Dias J, et al. Human MAIT-cell responses to Escherichia coli: activation, cytokine production, proliferation, and cytotoxicity. J Leukoc Biol. 2016;100(1):233–240. doi: 10.1189/jlb.4TA0815-391RR.
    1. Fontenot JD, et al. A function for interleukin 2 in Foxp3-expressing regulatory T cells. Nat Immunol. 2005;6(11):1142–1151. doi: 10.1038/ni1263.
    1. Knoechel B, et al. Sequential development of interleukin 2-dependent effector and regulatory T cells in response to endogenous systemic antigen. J Exp Med. 2005;202(10):1375–1386. doi: 10.1084/jem.20050855.
    1. Barron L, et al. Cutting edge: mechanisms of IL-2-dependent maintenance of functional regulatory T cells. J Immunol. 2010;185(11):6426–6430. doi: 10.4049/jimmunol.0903940.
    1. Abbas AK, et al. Revisiting IL-2: biology and therapeutic prospects. Sci Immunol. 2018;3(25):eaat1482. doi: 10.1126/sciimmunol.aat1482.
    1. Marek-Trzonkowska N, et al. Factors affecting long-term efficacy of T regulatory cell-based therapy in type 1 diabetes. J Transl Med. 2016;14(1):332. doi: 10.1186/s12967-016-1090-7.
    1. Koreth J, et al. Efficacy, durability, and response predictors of low-dose interleukin-2 therapy for chronic graft-versus-host disease. Blood. 2016;128(1):130–137. doi: 10.1182/blood-2016-02-702852.
    1. Castela E, et al. Effects of low-dose recombinant interleukin 2 to promote T-regulatory cells in alopecia areata. JAMA Dermatol. 2014;150(7):748–751. doi: 10.1001/jamadermatol.2014.504.
    1. Long SA, et al. Rapamycin/IL-2 combination therapy in patients with type 1 diabetes augments Tregs yet transiently impairs β-cell function. Diabetes. 2012;61(9):2340–2348. doi: 10.2337/db12-0049.
    1. Yu A, et al. Selective IL-2 responsiveness of regulatory T cells through multiple intrinsic mechanisms supports the use of low-dose IL-2 therapy in type 1 diabetes. Diabetes. 2015;64(6):2172–2183. doi: 10.2337/db14-1322.
    1. Todd JA, et al. Regulatory T cell responses in participants with type 1 diabetes after a single dose of interleukin-2: a non-randomised, open label, adaptive dose-finding trial. PLoS Med. 2016;13(10):e1002139. doi: 10.1371/journal.pmed.1002139.
    1. Rosenzwajg M, et al. Low-dose IL-2 in children with recently diagnosed type 1 diabetes: a phase I/II randomised, double-blind, placebo-controlled, dose-finding study. Diabetologia. 2020;63(9):1808–1821. doi: 10.1007/s00125-020-05200-w.
    1. Simeonov DR, et al. Discovery of stimulation-responsive immune enhancers with CRISPR activation. Nature. 2017;549(7670):111–115. doi: 10.1038/nature23875.
    1. Trotta E, et al. A human anti-IL-2 antibody that potentiates regulatory T cells by a structure-based mechanism. Nat Med. 2018;24(7):1005–1014. doi: 10.1038/s41591-018-0070-2.
    1. Khoryati L, et al. An IL-2 mutein engineered to promote expansion of regulatory T cells arrests ongoing autoimmunity in mice. Sci Immunol. 2020;5(50):eaba5264. doi: 10.1126/sciimmunol.aba5264.
    1. Charych DH, et al. NKTR-214, an engineered cytokine with biased IL2 receptor binding, increased tumor exposure, and marked efficacy in mouse tumor models. Clin Cancer Res. 2016;22(3):680–690. doi: 10.1158/1078-0432.CCR-15-1631.
    1. Sockolosky JT, et al. Selective targeting of engineered T cells using orthogonal IL-2 cytokine-receptor complexes. Science. 2018;359(6379):1037–1042. doi: 10.1126/science.aar3246.
    1. Spitzer MH, et al. Systemic immunity is required for effective cancer immunotherapy. Cell. 2017;168(3):487–502. doi: 10.1016/j.cell.2016.12.022.
    1. Finck R, et al. Normalization of mass cytometry data with bead standards. Cytometry A. 2013;83(5):483–494.
    1. Zunder ER, et al. Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm. Nat Protoc. 2015;10(2):316–333. doi: 10.1038/nprot.2015.020.
    1. Wolf FA, et al. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 2018;19(1):15. doi: 10.1186/s13059-017-1382-0.

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