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Erythropoietin receptor on cDC1s dictates immune tolerance

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Abstract

Type 1 conventional dendritic cells (cDC1s) are unique in their efferocytosis1 and cross-presenting abilities2, resulting in antigen-specific T cell immunity3 or tolerance4,5,6,7,8. However, the mechanisms that underlie cDC1 tolerogenic function remain largely unknown. Here we show that the erythropoietin receptor (EPOR) acts as a critical switch that determines the tolerogenic function of cDC1s and the threshold of antigen-specific T cell responses. In total lymphoid irradiation-induced allograft tolerance9,10, cDC1s upregulate EPOR expression, and conditional knockout of EPOR in cDC1s diminishes antigen-specific induction and expansion of FOXP3+ regulatory T (Treg) cells, resulting in allograft rejection. Mechanistically, EPOR promotes efferocytosis-induced tolerogenic maturation7,11 of splenic cDC1s towards late-stage CCR7+ cDC1s characterized by increased expression of the integrin β8 gene12 (Itgb8), and conditional knockout of Itgb8 in cDC1s impairs tolerance induced by total lymphoid irradiation plus anti-thymocyte serum. Migratory cDC1s in peripheral lymph nodes preferentially express EPOR, and their FOXP3+ Treg cell-inducing capacity is enhanced by erythropoietin. Reciprocally, loss of EPOR enables immunogenic maturation of peripheral lymph node migratory and splenic CCR7+ cDC1s by upregulating genes involved in MHC class II- and class I-mediated antigen presentation, cross-presentation and costimulation. EPOR deficiency in cDC1s reduces tumour growth by enhancing anti-tumour T cell immunity, particularly increasing the generation of precursor exhausted tumour antigen-specific CD8+ T cells13 in tumour-draining lymph nodes and supporting their maintenance within tumours, while concurrently reducing intratumoural Treg cells. Targeting EPOR on cDC1s to induce or inhibit T cell immune tolerance could have potential for treating a variety of diseases.

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Fig. 1: Efferocytotic tolerance-inducing cDC1s upregulate Epor following TLI.
Fig. 2: Absence of EPOR on cDC1s abrogates Treg cell-mediated allo-antigen-specific tolerance following TLI/ATS, resulting in allograft rejection.
Fig. 3: scRNA-seq analysis reveals that TLI/ATS promotes EPOR-dependent, efferocytosis-triggered tolerogenic maturation of splenic cDC1s.
Fig. 4: EPO-activated cDC1 EPOR supports antigen-specific FOXP3+ Treg cell induction in PLN and restrains the immunogenic maturation of CCR7+ cDC1s.
Fig. 5: EPOR expression on cDC1s hinders antigen-specific anti-tumour T cell immunity and the loss of EPOR in cDC1s leads to tumour reduction.

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Data availability

All transcriptional data generated in the current study were deposited at the NCBI Gene Expression Omnibus (GEO) and are publicly available through the following accession numbers: GSE253056 (bulk RNA-seq) and GSE284080 (scRNA-seq), respectively. Source data are provided with this paper.

Code availability

The scripts for replicating the RNA-seq analyses presented are accessible on GitHub (https://github.com/chansigit/Epor-cDC1-bulkRNAseq). Scripts for reproducing all scRNA-seq analyses presented are accessible on GitHub (https://github.com/chris-mcginnis-ucsf/epor_dc_tolerance) and associated processed data objects are available on Synapse (https://synapse.org/Synapse:syn64330568).

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Acknowledgements

We thank J. Idoyaga for providing Xcr1cre-mTFP1 mice; E. B. Rankin for providing Eporflox/flox mice; V. K. Kuchroo for providing MC38-OVA and B16F10-OVA tumour cell lines; P. Giang for preparing CD45.1+ Foxp3DTR/DTR spleens; NIH Tetramer Core Facility (NIH Contract 75N93020D00005 and RRID:SCR_026557) for providing I-Ab|mouse 2W1S|EAWGALANWAVDSA|PE-labelled tetramer; C. Zhu for processing the scRNA-seq FASTQ data and assistance with data analysis; C. Brown for assistance with resource acquisition; T. L. Roth for valuable discussion; L. L. Tolentino, K. Nguyen, C. Barclay and J. N. Delos Reyes for expert technical support in flow cytometry and fluorescence-activated cell sorting; the DIMC Core of the Stanford Diabetes Research Center; and Breakthrough T1D Center of Excellence for support. This work was supported by the following grants: U54 CA274511, CA251174, CA244114 (E.G.E.) and P01HL149626 (X.A.).

Author information

Author notes

  1. Deceased: Samuel Strober

Authors and Affiliations

  1. Department of Pathology, School of Medicine, Stanford University, Palo Alto, CA, USA

    Xiangyue Zhang, Christopher S. McGinnis, Guotao Yu, Kamir J. Hiam-Galvez, Wenhui Guo, Winnie Yao, Jingtao Qiu, Alexander Muselman, Ian L. Linde, Michael Angelo, Ansuman T. Satpathy & Edgar G. Engleman

  2. Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA

    Christopher S. McGinnis & Ansuman T. Satpathy

  3. Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA

    Sijie Chen

  4. Department of Medicine, Division of Blood and Marrow Transplantation and Cellular Therapy, School of Medicine, Stanford University, Palo Alto, CA, USA

    Pingping Zheng, Hao Yan & Toshihito Hirai

  5. Department of Pathology and Neuropathology, University Hospital and Comprehensive Cancer Center Tübingen, Tübingen, Germany

    Christian M. Schürch

  6. Cluster of Excellence iFIT (EXC 2180), Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, Germany

    Christian M. Schürch

  7. Department of Otolaryngology-Head and Neck Surgery, School of Medicine, Stanford University, Stanford, CA, USA

    Nathan E. Reticker-Flynn

  8. Department of Biomedical Engineering, Duke University, Durham, NC, USA

    John W. Hickey

  9. Department of Dermatology, University of California, San Francisco, San Francisco, CA, USA

    Victoria M. Tran & Tiffany C. Scharschmidt

  10. Division of Pulmonary, Critical Care, Allergy and Sleep, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA

    Wenli Qiu & Dean Sheppard

  11. CIRI, Centre International de Recherche en Infectiologie, Université de Lyon, Inserm U1111, Université Claude Bernard Lyon 1, CNRS UMR5308, ENS de Lyon, Lyon, France

    Delphine Brichart-Vernos & Helena Paidassi

  12. ImmunEdge, Redwood City, CA, USA

    Bo Yu

  13. Laboratory of Membrane Biology, New York Blood Center, New York, NY, USA

    Xiuli An

  14. Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands

    Yanling Xiao

  15. Department of Immunology, St Jude Children’s Research Hospital, Memphis, TN, USA

    Hongbo Chi

  16. Division of Infectious Diseases, Center for Inflammation and Tolerance, Cincinnati Children’s Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA

    Sing Sing Way

  17. Centre d’Immunologie de Marseille-Luminy, Aix-Marseille Université, INSERM, CNRS, Marseille, France

    Bernard Malissen

  18. Department of Medicine (Immunology and Rheumatology), School of Medicine, Stanford University, Palo Alto, CA, USA

    Samuel Strober

  19. Stanford Cancer Institute, School of Medicine, Stanford University, Palo Alto, CA, USA

    Edgar G. Engleman

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Contributions

X.Z. and E.G.E. conceived the study. X.Z. designed and performed the experiments, analysed data, interpreted the results and wrote the manuscript with E.G.E. C.S.M. and S.C. conducted the scRNA-seq analyses and wrote the scRNA-seq results and methods sections together with X.Z. and E.G.E. K.J.H.-G. and W.Y. prepared the scRNA-seq libraries. S.C., P.Z., N.E.R.-F. and X.Z. carried out the RNA-seq analyses. C.M.S. and J.W.H. performed the CODEX experiments. G.Y., W.G. and J.Q. assisted with flow cytometry staining and cell sorting, in vitro cell culture, T cell adoptive transfers, tumour growth studies and data recording. A.M. contributed to the flow cytometry analysis of cDC1 Epor-tdT expression in the brain and assisted with tissue preparation for in vivo studies. I.L.L. aided in the in vivo tumour studies. H.Y. and T.H. performed heart transplantation. V.M.T., W.Q. and D.B.-V. assisted with Aldh1a2 and Itgb8 animal models. B.Y. made DEC205-OVA. A.T.S. supervised the scRNA-seq analyses. K.J.H.-G., X.A., Y.X., H.P., T.C.S., M.A., D.S., H.C., A.T.S., S.S.W., B.M. and S.S. provided critical intellectual insights. E.G.E. supervised the study. All authors provided feedback on the manuscript draft.

Corresponding authors

Correspondence to Xiangyue Zhang or Edgar G. Engleman.

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Competing interests

X.Z. is a cofounder and shareholder of ImmunEdge Inc. E.G.E. is a founder, shareholder and board member of ImmunEdge Inc. B.Y. is a shareholder of ImmunEdge Inc. X.Z and E.G.E. are Stanford-affiliated inventors of PCT/US2023/063997, entitled ‘Epo Receptor Agonists and Antagonists’. C.S.M. holds patents related to MULTI-seq. C.M.S. is a cofounder and scientific advisor of Vicinity Bio GmbH and is on the scientific advisory board of and has received research funding from Enable Medicine Inc., all outside the current work. T.C.S. is a scientific advisory board member for Concerto Biosciences. M.A. is a consultant, board member, and shareholder in Ionpath Inc. D.S. is a founder of Pliant Therapeutics and Glial Biosciences and is on the Genentech Scientific Review Board and the Amgen Inflammation Scientific Review Board, and an advisor to Lila Biologics, Arda Therapeutics and TCGFB Inc. H.C. is a consultant for Kumquat Biosciences and TCura Bioscience. A.T.S. is a founder of Immunai, Cartography Biosciences and Prox Biosciences, an advisor to Zafrens and Wing Venture Capital, and receives research funding from Merck Research Laboratories. The other authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 XCR1+CD8α+ cDC1s in the spleen following TLI/ATS are bona fide cDC1s.

a, Total splenocyte frequency per spleen (UNT n=5; TLI/ATS n=10). b, Gating of CD11chighMHCIIhigh cDCs from the splenocytes. Summary graph of the frequency of cDCs in total splenocytes (UNT, n = 6; TLI/ATS, n = 7). c, Gating of CD8α+CD11b− cDC1s and CD8α−CD11b+ cDC2s; frequencies in cDCs (UNT, n = 6; TLI/ATS, n = 6). d, XCR1+ and e, Ki67+ cDC1 frequencies (UNT, n = 5; TLI/ATS, n = 5). f, qPCR of Batf3 and Irf8 in XCR1+CD8α+ cDC1s (n = 5/group). g, IRF8 and h, Zbtb46-GFP expression (UNT, n = 6; TLI/ATS, n = 5). i-k, MFI of MafB-mCherry expression and % of MafB-mCherry+ cells in XCR1+CD8α+ cDC1s (i), cDC2s (j) and red pulp macrophages (RPMΦs) (k). Day 0 (UNT), n = 4; TLI/ATS Day 5, n = 5; TLI/ATS Day 9, n = 5 (i,j,k). Data are shown from one experiment, representative of at least two independent experiments with similar results (a-k). Statistical analysis was performed using unpaired two-tailed Student’s t-test (a,b,c,d,e,h), or one-way ANOVA with Tukey’s multiple-comparison test (f,g,i,j,k). Data are mean ± s.e.m. (a-k).

Source data

Extended Data Fig. 2 TLI/ATS leads to widespread apoptosis and extramedullary erythropoiesis in the spleen and a marked rise in serum EPO.

a, TUNEL staining of spleen sections, UNT vs. TLI/ATS (scale bar = 200 µm). b, Spleen cell composition after ATS, TLI, or TLI/ATS; pie chart shows mean frequencies of indicated populations (n = 3). T cells (TCRβ+CD19−NK1.1−), B cells (CD19+TCRβ−NK1.1−), erythroid progenitors (CD11c−TER119+CD71+), cDCs (CD3ε−B220−SiglecH−PDCA-1−CD11chighMHCIIhigh), other myeloid cells are subdivided into CD11b+Ly6C−Ly6G+, CD11b+Ly6G −Ly6C+ and CD11bintF4/80+. c, Serum EPO levels over time after TLI/ATS (ELISA, n = 8). d, CD71+TER119+ erythroid progenitors in spleen (day 6) (upper) and in spleen/BM (lower) over time after TLI/ATS (n = 3). e, Co-detection by indexing (CODEX) imaging of WT C57BL/6 spleen (UNT vs. 1 day after TLI; scale bar = 500 µm). f, Scheme of EPO treatment in Epor-tdTomato-Cre mice (i.p. × 5 days). g,h, Flow cytometry showing splenic cDC1 frequency among cDCs (g) and Epor-tdT+ cDC1 frequency/MFI (h) (+PBS, n = 5; +EPO, n = 5). i-j, Frequencies of Epor-tdT+ and Epor-tdT− TER119+ erythroid cells (i) and Epor-tdT+CD11bintF4/80+Epor-tdT+ RPMΦs (j), (+PBS, n = 5; +EPO, n = 5). k, CCR7 vs. Epor-tdT expression in XCR1+CD8α+ cDC1s that were gated as live-dead aqua−CD3ε−CD19−B220− SiglecH−PDCA-1−CD11chighMHCIIhigh; histogram overlay for CCR7+ cDC1s (UNT, n = 5; TLI/ATS, n = 5). Data are shown from one experiment, representative of at least two independent experiments with similar results (a,b,c,d,g,h,i,j,k) or from one experiment (e). Statistical analysis was performed using unpaired two-tailed Student’s t-test (g,h,i,j,k). Data are mean ± s.e.m. (d,g-k). The diagram in f was created in BioRender. Zhang, X. (2025) https://BioRender.com/cx0n3vn.

Source data

Extended Data Fig. 3 EPO-EPOR downstream signaling is activated in cDC1s following TLI/ATS.

a-c, Gene Set Enrichment Analysis (GSEA) of transcriptional profiles using the Hallmark gene set of MSigDB. NES, normalized enrichment score; FDR, false discovery rate. Red: upregulated; Blue: downregulated. TLI/ATS vs. UNT. b, Upregulated gene sets. c, Downregulated gene sets. d-e, Intracellular phospho-flow cytometric analysis of EPO-EPOR downstream signaling in live-dead blue−Lin−SiglecH−PDCA-1−CD11chighMHCIIhigh. Spleens were harvested on the next day following the last dose of TLI or TLI/ATS. UNT (n = 4) vs. TLI (n = 4) vs. TLI/ATS (n = 4). d, XCR1+CD8α+ cDC1s and e, XCR1−CD8α− cDC2s. f,g, Histograms and MFI of the indicated EPO-EPOR downstream signaling molecules with fluorescence minus one (FMO) as controls by intracellular phospho-flow staining on the next day following the last dose of TLI/ATS treatment. Eporflox/flox (n = 4) vs. EporΔXcr1 (n = 5). cDC1s (f) and cDC2s (g). h, Ex vivo analysis of EPO-EPOR downstream signaling in splenic cDC1s. Splenic cDCs were MACS-purified with a pan-DC isolation kit and cultured at 5 × 106 cells/ml, then rested overnight. Cells were isolated from UNT or TLI/ATS-treated Eporflox/flox (n = 4; n = 4) and EporΔXcr1 (n = 4; n = 4) mice. cDCs from TLI/ATS-treated mice were stimulated ex vivo with EPO (10 IU/200 μl) or PBS (control) overnight. Phosphorylation of downstream signaling molecules was assessed by flow cytometry, after gating on XCR1+SIRPα− splenic cDC1s. Data are shown from one experiment, representative of at least two independent experiments with similar results (d-h). Statistical analysis was performed using unpaired two-tailed Student’s t-test (f,g), or one-way ANOVA Tukey’s multiple-comparison test (d, e and h left), or paired two-tailed Student’s t-test (h right). Data are mean ± s.e.m. (d-h).

Source data

Extended Data Fig. 4 FOXP3+ Tregs play an indispensable role in TLI/ATS-induced cDC1 EPOR-dependent immune tolerance.

a, Representative pseudocolor plots showing FOXP3+ Treg depletion efficiency in recipient mice on day 6 after DT treatment (DT injections on days 0, 2, and 4). b,c, Representative pseudocolor plots of C57BL/6, Batf3−/−, or EporΔXcr1 recipient conventional CD4+ T cell percentages and FOXP3+ Treg percentages in CD4+ T cells. d,e, Absolute cell number of indicated cell populations. b,d, Day 0 (UNT, n = 5; n = 5; n = 5 and TLI/ATS, n = 6; n = 5; n = 4) and c,e, Day 14 of UNT or TLI/ATS-treated groups post allo-BM infusion (UNT, n = 11; n = 6; n = 9 and TLI/ATS, n = 3; n = 11; n = 10). f, MHCII expression on cDC1s and cDC2s from MHCIIflox/flox and MHCIIΔXcr1 spleens. g,h,i, MHCIIflox/flox (n = 6) and MHCIIΔXcr1 (n = 6) recipients were given TLI/ATS and i.v. infused with BALB/c donor BM cells. 14 days post BM infusion, the percentages of donor type (H2Kd+) cells among leukocyte populations were determined in the peripheral blood of hosts. g,i, Recipient MHCI (H-2Kb)+TCRβ+CD4+ T cell frequency among total live cells and FOXP3+ frequency among CD4+ T cells were analyzed on day 14. j, CD45.2+FOXP3WTEporflox/flox (+ PBS/without DT, n = 8; +DT, n = 8) or EporΔXcr1 (+ PBS/ without DT, n = 8; +DT, n = 8) mice were injected with 30 million CD45.1+FOXP3DTR CD4+ T cells isolated by MACS. Two consecutive doses of DT or PBS were given on each of the following 2 days. Subsequently, the mice were treated with TLI/ATS, and 2W1S-BALB/c donor BM cells were infused i.v., and 14 days later, 2W1S-tetramer+CD44+H-2Kb+TCRβ+CD4+ T cells from the spleens were analyzed for FOXP3 expression by flow cytometry. FOXP3 expression in CD45.1+ or CD45.2+2W1S-tetramer+ CD4+ T cells is shown. One experiment (j) or one of two independent experiments with similar results are shown (a-i). Statistical analysis was performed using unpaired two-tailed Student’s t-test (g,i), two-way ANOVA with Tukey’s multiple-comparison test (d,e,j). Data are mean ± s.e.m. (d,e,g,i,j). The diagram in j was created in BioRender. Zhang, X. (2025) https://BioRender.com/cx0n3vn.

Source data

Extended Data Fig. 5 Differentially expressed genes (DEGs) in cDC1s in scRNA-seq analysis and ex vivo TGFβ-dependent Ag-specific FOXP3+ Treg induction by CCR7+ cDC1s.

a, UMAP of splenic cDC1 gene expression by sample identity. b, Dot plots of top condition-specific DEGs in Eporflox/flox and EporΔXcr1 mice (TLI/ATS vs. UNT). c, Absolute cDC1 numbers per spleen in UNT vs. TLI/ATS-treated Eporflox/flox (n = 5/condition) and EporΔXcr1 (n = 5/condition) mice. d, UMAPs of cDC1 subtypes in Epor-tdT+ and Epor-tdT– cells. e-g, Dot plots of top condition-specific DEGs in Epor-tdT+ and Epor-tdT– cDC1s (TLI/ATS) and in Eporflox/flox and EporΔXcr1 mice (TLI/ATS vs. UNT). Dot color = expression, size = % of indicated gene expressed cells (b,e-g). h, Bar charts showing cDC subtype (d) proportions in Epor-tdT+ and Epor-tdT– cDC1s following TLI/ATS. i, Role of TGFβ in FOXP3+ Treg induction by CCR7+ cDC1s: 12 h after apoptotic Act-mOVA injection, CCR7+ cDC1s (1×104) were cocultured with CD45.1+ CTV-labeled naïve OT-II cells ± anti-TGFβ; FOXP3 expression was analyzed by flow cytometry (n = 5/group). j,k, Representative flow cytometry analysis and l,m, Absolute cell number of indicated cell populations of Fig. 3j, Itgb8ΔXcr1 vs. littermate controls. j,l, Day 0 and k,m, Day 14 of UNT (n = 5; n = 5) or TLI/ATS-treated (n = 5; n = 5) groups post allo-BM infusion. n,o, Aldh1a2ΔCD11c: Batf3−/− (n = 6) vs. Aldh1a2flox/flox: Batf3−/− (n = 7) BM chimeric recipient mice (CD45.1+) were given TLI/ATS. 1 day after the last dose of TLI/ATS, 2W1S-BALB/c donor BM cells were infused i.v., and 14 days later, the percentages of donor type (H2Kd+) cells among leukocyte populations in the peripheral blood of hosts were determined (n) and 2W1S-tetramer+CD44+H-2Kb+TCRβ+CD4+ T cells from the spleens were analyzed for FOXP3 expression by flow cytometry and FOXP3+ Tregs were counted (o). Data are representative of at least three independent experiments with similar results (c,i) or one experiment (j-o). Statistical analysis was performed using unpaired two-tailed Student’s t-test (c,i,n,o), or two-way ANOVA followed by Tukey’s multiple-comparison test with P values adjusted (l,m), or propeller test, two-sided, no multiple-comparison correction (b), or wilcoxon rank sum test, two-sided, Bonferroni correction (h). Data are mean ± s.e.m. (c,i,l,m,n,o). The diagram in i was created in BioRender. Zhang, X. (2025) https://BioRender.com/rq2yp2e.

Source data

Extended Data Fig. 6 Absence of EPOR on cDC1s gives rise to immunogenic cDC1s that promote both CD8+ T cell cross-priming and CD4+ T cell priming to cell-associated Ags.

a, MFI of indicated molecules on gated cDC1s with fluorescence minus one (FMO) as controls. b, MFI of indicated molecules on gated cDC2s with fluorescence minus one (FMO) as controls. c, Percentages of cDC2s in splenic cDCs. d, Representative flow gating of CCR7+XCR1+SIRPα– cDC1s in splenic cDC1s (Upper), and percentages and absolute numbers of CCR7+ cDC1s (Lower). a-d, Eporflox/flox (n = 5) vs. EporΔXcr1 (n = 5) mice. e, MFI of indicated molecules on CCR7+ vs. CCR7– cDC1s. CD40 and PD-L1: Eporflox/flox (n = 5); EporΔXcr1 (n = 5). CD80 and CD86: Eporflox/flox (n = 6); EporΔXcr1 (n = 6). f, Cross-presentation assay: apoptotic Act-mOVA thymocytes injected into Eporflox/flox (n = 5) or EporΔXcr1 (n = 5) mice 1 day after transfer of CTV-labeled naïve CD45.1+ naïve OT-I cells; spleens analyzed on day 4 for OT-I expansion and proliferation. g, Same setup with OT-II cells; percentages and absolute numbers of OT-II cells and proliferating OT-II cells were assessed. Ag-specific CD4+ T cell response: Ag-specific CD4+ T cell immune response following i.v. injection of apoptotic Act-mOVA thymocytes 1 day after i.v. injection of CTV-labeled naïve CD45.1+ naïve OT-II cells. Spleens were analyzed at day 4 for OT-II expansion and proliferation. Eporflox/flox (n = 5) and EporΔXcr1 (n = 5) mice. Data are shown from one experiment, representative of at least three independent experiments with similar results (a-g). Statistical analysis was performed using unpaired two-tailed Student’s t-test (a,b,c,d,f,g) and two-way ANOVA followed by Tukey’s multiple-comparison test (e). Data are mean ± s.e.m. (a-g). The diagrams in f,g were created in BioRender. Zhang, X. (2025) https://BioRender.com/bth22u6.

Source data

Extended Data Fig. 7 Phenotypes of T cells in the spleens of Eporflox/flox vs. EporΔXcr1 mice and role of EPOR in cDC1-mediated cell-associated Ag-specific CD4+ T cell priming and proliferation and FOXP3+ Treg induction.

a-e, Percentages and absolute numbers of CD4+ T cells (a), FOXP3+CD25+ Tregs in CD4+ T cells (b), CD44highCD62Llow effector cells and CD44lowCD62Lhigh naïve cells in CD4+ T cells (c), CD8+ T cells (d), and CD44highCD62Llow effector cells and CD44lowCD62Lhigh naïve cells in CD8+ T cells (e) in the spleens of EporΔXcr1 and littermate Eporflox/flox control mice with representative flow cytometric plots. a-e, Eporflox/flox, n = 5; EporΔXcr1, n = 5. f,g, Flow cytometry-based measurement of cell-associated Ag-specific CD4+ T cell immune response in the spleen following i.v. injection of apoptotic Act-mOVA thymocytes into mice of the indicated genotypes 1 day after i.v. injection of CTV-labeled naïve CD45.1+ OT-II cells. f, WT C57BL/6 (n = 5) and Batf3−/− (n = 7). g, FOXP3+ Treg induction in Eporflox/flox and EporΔXcr1 mice. Recombinant EPO or PBS was administered daily, from Day −3 to Day 4. +PBS: Eporflox/flox (n = 5), EporΔXcr1 (n = 5); +EPO: Eporflox/flox (n = 5), EporΔXcr1 (n = 5) mice. Data are shown from one experiment, representative of at least three independent experiments with similar results (a-e), or two independent experiments with similar results (f,g). Statistical analysis was performed using unpaired two-tailed Student’s t-test (a-f), or two-way ANOVA followed by Tukey’s multiple-comparison test (g). Data are mean ± s.e.m. (a-g). The diagrams in f,g were created in BioRender. Zhang, X. (2025) https://BioRender.com/bth22u6.

Source data

Extended Data Fig. 8 Epor-tdT expression on XCR1+ cDC1s in selected organs and tolerogenic phenotype of Epor-tdT+ migratory cDC1s in PLN.

a,b,c CCR7- and Batf3-dependent Epor-tdT expression on migratory cDCs in pLNs. Migratory cDCs were gated as CD11cintMHCIIhigh from live-dead aqua−Lin−SiglecH−PDCA-1−EpCAM− cells, and resident cDCs were gated as CD11chighMHCIIint from live-dead aqua−Lin−SiglecH−PDCA-1− cells. pLNs including inguinal, axillary, brachial, and superficial cervical LNs were combined for analysis by flow cytometry (a,b). Ccr7−/−EportdT/+, Batf3−/−EportdT/+ and WT C57BL/6 mice (a). Histogram overlay of Epor-tdT expression on migratory or resident cDCs from individual mouse strains (b). Epor-tdT expression on migratory cDCs from individual pLNs of EportdT/+ mice (c). d, Epor-tdT expression on cDC1s obtained from the indicated organs in Zbtb46GFP/+EportdT/+ mice. cDCs were gated in CD45+ cells as CD11c+Zbtb46-GFP+, in which cDC1s were further gated as XCR1+CD103+. e, Flow cytometric analysis of tolerance associated cell-surface molecules on PLN Epor-tdT+ migratory cDC1s compared with Epor-tdT− cDCs and resident cDCs with FMO serving as controls (n = 8). Data are representative of at least two independent experiments with similar results (a-e). Statistical analysis was performed using one-way ANOVA Tukey’s multiple-comparison test (e). Data are mean ± s.e.m. (e). The diagrams in a,e were created in BioRender. Zhang, X. (2025) https://BioRender.com/5sr2iny.

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Extended Data Fig. 9 Induction of Ag-specific CD4+FOXP3+ Tregs by PLN migratory Epor-tdT+ cDC1s.

a, FACS-sorted PLN Epor-tdT+ (n = 4) or Epor-tdT− (n = 4) XCR1+ migratory cDC1s from Epor-tdT mice were cocultured for 5 days with CTV-labeled naïve OT-II cells + DEC205-OVA (ratio 1:5); FOXP3 expression in OT-II cells was analyzed by flow cytometry. b, Same setup as (a) but with apoptotic Act-mOVA thymocytes (ratio 1:5:2) ± EPO (20 IU per well per day for 5 days); FOXP3 expression in OT-II cells was measured. Epor-tdT+ (+ PBS or w/o, n = 4; +EPO, n = 4) or Epor-tdT− (+ PBS or w/o, n = 4; +EPO, n = 3) c, FACS-sorted PLN Epor-tdT+ or Epor-tdT− migratory cDC1s were cocultured for 12 h with apoptotic CD45.1+ thymocytes ± EPO; MFIs of surface markers were analyzed. Epor-tdT+: n = 2. Epor-tdT–: n = 2. d, Migratory cDC1s from Eporflox/flox or EporΔXcr1 mice were cocultured with naïve CTV-labeled OT-II cells and Act-mOVA thymocytes (1:5:2) ± EPO (20 IU per well per day for 5 days); FOXP3 induction was assessed. n = 6/group. e, Efferocytosis of PKH67-labeled apoptotic thymocytes by migratory cDC1s and cDC2s in dLNs 12 h post-injection. f, Act-mOVACD45.1/CD45.2 mice were reconstituted with either Eporflox/flox (n = 5) or EporΔXcr1 (n = 6) BM cells after lethal irradiation. 8 weeks post-reconstitution, naïve CTV-labeled OT-II cells were i.v. infused (day 0), and EPO was administered on days −2 to 2. FOXP3 induction in OT-II cells was assessed in inguinal LNs on day 9. Data are shown from one experiment, representative of two independent experiments with similar results (a-e) or one (f) independent experiment. Statistical analysis was performed using unpaired two-tailed Student’s t-test (a,b,f), two-way ANOVA with Tukey’s multiple-comparison test (d). Data are mean ± s.e.m. (a,b,c,d,f). The diagrams in a,b,c,e,f were created in BioRender. Zhang, X. (2025) https://BioRender.com/u560oi2.

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Extended Data Fig. 10 Phenotypes of T cells in the PLNs of Eporflox/flox vs. EporΔXcr1 mice.

a-e, Percentages and absolute numbers of CD4+ T cells (a), FOXP3+CD25+ Tregs in CD4+ T cells (b), CD44highCD62Llow effector cells and CD44lowCD62Lhigh naïve cells in CD4+ T cells (c), CD8+ T cells (d), and CD44highCD62Llow effector cells and CD44lowCD62Lhigh naïve cells in CD8+ T cells (e) in the PLNs of EporΔXcr1 and littermate Eporflox/flox control mice with representative flow cytometry plots. a-e, Eporflox/flox (n = 9) and EporΔXcr1 (n = 9). Data are shown from one experiment, representative of at least three independent experiments with similar results (a-e). Statistical analysis was performed using unpaired two-tailed Student’s t-test (a-e). Data are mean ± s.e.m. (a-e).

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Extended Data Fig. 11 EPOR expression on tumor-infiltrating leukocytes (TILs), tumor Ag-carrying migratory cDC1s in TDLNs and tumors, and the correlation of tumor growth with systemic EPO levels.

a, Zbtb46GFP/+EportdT/+ mice were implanted s.c. with MC38 or B16F10 tumor, or EO771 tumor in the mammary fat pad. On day 12, tumors were harvested for flow cytometric analysis of Epor-tdT on cDCs (live-dead aqua−CD45+Zbtb46-GFP+CD11c+); cDC1s were gated as XCR1+ and non-cDC1s as XCR1−. b-d, Mice implanted s.c. with MC38-OVAdim or B16F10-OVA; on day 10, tumors were analyzed for Epor-tdT expression in TILs. b, Representative gating strategy of individual live-dead blue− TIL populations. c,d, Histogram overlay showing Epor-tdT expression in individual cell populations. e, Zbtb46GFP/+EportdT/+ mice with MC38-OVAdim tumors (day 12) were analyzed for Epor-tdT on tumor-infiltrating cDCs; CCR7+ (population I) and CCR7− (populations II/III by Ly6A) subsets were gated, with XCR1/CD103 staining to define cDC1s and cDC2s. f, Quantification of Epor-tdT expression on individual tumor infiltrating cDC subsets. MC38-OVAdim (n = 4) and B16F10-OVA (n = 4) tumors were harvested on day 12 post-s.c. implantation for flow cytometry. Gating strategy as in Fig. 5a and Extended Data Fig. 11e. g, Flow cytometry analysis of Epor-tdT expression on TDLN migratory cDC1s. Overlay of migratory cDC1s with Lin− live cells to show Epor-tdT expression levels. h, Serum EPO levels were measured by ELISA on the indicated days after s.c. implantation of MC38-OVAdim (n = 6) or B16F10-OVA (n = 5) tumors in WT mice. i,j,k, B16F10-OVA-ZsGreen cells were s.c. implanted into EportdT/+ mice, and tdLN and tumor were analyzed on day 9 after inoculation. j, Flow cytometry analysis of Epor-tdT expression on tdLN ZsGreen+ migratory and resident XCR1+ cDC1s. Overlay of migratory ZsGreen+ cDC1s or resident ZsGreen+ cDC1s with Lin−live cells to show Epor-tdT expression levels. k, Flow cytometry analysis of Epor-tdT expression on tumor infiltrating ZsGreen+ cDC1s. Data are shown from one experiment, representative of at least two independent experiments with similar results (a-e,f,g,h,j,k). Statistical analysis was performed using one-way ANOVA with Dunnett’s multiple-comparison test (f). Data are mean ± s.e.m. (f,h). The diagrams in a,b,e,g,i were created in BioRender. Zhang, X. (2025) https://BioRender.com/gjjtedh.

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Extended Data Fig. 12 Loss of EPOR in cDC1s limits tumor growth and promotes immunogenic function of tumor Ag-carrying cDC1s in both TDLN and tumor.

a, Growth of MC38-OVAdim tumor cells implanted s.c. into Eporflox/flox (n = 8) and EporΔXcr1 mice (n = 9). b, Growth of B16F10-OVA tumor cells implanted s.c. into Eporflox/flox (n = 6) and EporΔXcr1 mice (n = 7). c, Experimental design for phenotyping tumor-Ag carrying ZsGreen+ cDC1s in tdLN and tumors in Eporflox/flox vs. EporΔXcr1 mice. B16F10-OVA-ZsGreen cells were implanted s.c. into EportdT/+ mice, and TDLNs and tumors were analyzed on day 9 after implantation. d, Flow cytometry analysis of Epor-tdT expression on ZsGreen+ migratory XCR1+SIRPα− cDC1s in tdLNs with summary graph of statistical quantification. Eporflox/flox (n = 7) and EporΔXcr1 (n = 8). e, Flow cytometry analysis of CD40, CD80 and CD86 expression on tumor infiltrating ZsGreen+ cDC1s with summary graph of statistical quantification. Eporflox/flox (n = 7) and EporΔXcr1 (n = 8) mice. (f-l) MC38-OVAdim tumors were s.c. implanted into Eporflox/flox (n = 8) and EporΔXcr1 (n = 7) and 10 days later TILs were analyzed. f. Percentages of CD45+ live immune cells and CD8+ or CD4+ T cells in CD45+ TILs. g, Frequency of OVA257-264-dextramer+CD8+ T cells among CD8+ T cells. h, Representative flow plots and quantification of CD8+ T cells expressing TIM-3 and PD-1. i, Representative flow plots and quantification of TCF1+TIM-3−CD8+ T cells. j, Representative histograms and quantification of perforin, granzyme-B, IFNγ and TNFα expression in tumor-infiltrating CD8+ T cells. k, Percentage of FOXP3+ Tregs in CD4+ T cells with representative flow plots (Left). Absolute number of Tregs (Right). l, Representative flow plots and percentages of T-bet+CXCR3+ Tregs in CD4+ FOXP3+ Tregs. (f-l). Data are shown from one experiment, representative of at least two independent experiments with similar results (a,b,d,e,f-l). Statistical analysis was performed using two-way ANOVA with Šídák’s multiple comparison test (a,b), or two-tailed unpaired Student’s t-test (d,e,f,g,i,j,k,l), or two-way ANOVA with Tukey’s multiple-comparison test (h). Data are mean ± s.e.m. (a,b,d,e-l). The diagram in c was created in BioRender. Zhang, X. (2025) https://BioRender.com/3jod9q7.

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Supplementary Tables 1 and 2, which contain the full gene list used to generate the signature and a list of detected differentially expressed genes (related to Fig. 4).

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Zhang, X., McGinnis, C.S., Yu, G. et al. Erythropoietin receptor on cDC1s dictates immune tolerance. Nature (2025). https://doi.org/10.1038/s41586-025-09824-z

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