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ZBTB46 coordinates angiogenesis and immunity to control tumor outcome

Nature Immunology volume 25, pages 1546–1554 (2024)Cite this article

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Abstract

Tumor angiogenesis and immunity show an inverse correlation in cancer progression and outcome1. Here, we report that ZBTB46, a repressive transcription factor and a widely accepted marker for classical dendritic cells (DCs)2,3, controls both tumor angiogenesis and immunity. Zbtb46 was downregulated in both DCs and endothelial cells by tumor-derived factors to facilitate robust tumor growth. Zbtb46 downregulation led to a hallmark pro-tumor microenvironment (TME), including dysfunctional vasculature and immunosuppressive conditions. Analysis of human cancer data revealed a similar association of low ZBTB46 expression with an immunosuppressive TME and a worse prognosis. In contrast, enforced Zbtb46 expression led to TME changes to restrict tumor growth. Mechanistically, Zbtb46-deficient endothelial cells were highly angiogenic, and Zbtb46-deficient bone marrow progenitors upregulated Cebpb and diverted the DC program to immunosuppressive myeloid lineage output, potentially explaining the myeloid lineage skewing phenomenon in cancer4. Conversely, enforced Zbtb46 expression normalized tumor vessels and, by suppressing Cebpb, skewed bone marrow precursors toward immunostimulatory myeloid lineage output, leading to an immune-hot TME. Remarkably, Zbtb46 mRNA treatment synergized with anti-PD1 immunotherapy to improve tumor management in preclinical models. These findings identify ZBTB46 as a critical factor for angiogenesis and for myeloid lineage skewing in cancer and suggest that maintaining its expression could have therapeutic benefits.

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Fig. 1: ZBTB46 is a negative regulator of tumor progression.
Fig. 2: ZBTB46 normalizes tumor vasculature.
Fig. 3: ZBTB46 promotes antitumor immunity.
Fig. 4: ZBTB46 remodels the TME into an antitumor immunostimulatory milieu.
Fig. 5: Therapeutic maintenance of ZBTB46 improves cancer immunotherapy outcome.

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Data availability

Sequencing data are available at the Gene Expression Omnibus under accessions GSE226087 (bulk RNA-seq) and GSE264124 (scRNA-seq). Human bulk RNA tumor datasets are available from the TCGA database. Source data are provided with this paper.

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Acknowledgements

We thank K. M. Murphy at Washington University in St. Louis for the Zbtb46gfp/gfp (Zbtb46 KO) mice and M. Egeblad at Cold Spring Harbor Laboratory for MMTV-PyMT mice. We thank our colleagues at Washington University, M. J. Miller for the Tg(Cdh5-cre/ERT2)1Rha mice, which were originally obtained from R. H. Adams at the Max Planck Institute, Germany, R.D. Schreiber for 1956 and 1969 sarcoma cells, K. Lavine for MCECs and K. Weilbaecher for PyMT-BO1-GFP-Luc cells. We also thank A. S. Krupnick at the University of Virginia for providing LLC-GFP cells. We thank Washington University Center for Cellular Imaging (WUCCI) and Pathology FACS core for providing access to the light microscopes and FACS facility, respectively. We also thank GTAC@MGI for performing the RNA-seq. This work was supported by NIH grants R01HL149954, R01HL55337 and R01CA271714 (to K.C.).

Author information

Authors and Affiliations

  1. Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA

    Ashraf Ul Kabir, Carisa Zeng, Madhav Subramanian, Jun Wu, Minseo Kim, Karen Krchma, Xiaoli Wang, Daved H. Fremont, Maxim N. Artyomov & Kyunghee Choi

  2. Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA

    Carmen M. Halabi

  3. Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA

    Hua Pan

  4. Health Heart Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA

    Samuel A. Wickline

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Contributions

A.U.K. and K.C. conceived the idea, designed the experiments and wrote the manuscript. A.U.K. performed all experiments and analyzed data. C.Z. and M.N.A. analyzed the TME single-cell RNA-seq dataset. M.S. analyzed bulk RNA-seq data and TCGA dataset. M.K. helped with the ChIP–qPCR experiments. J.W. and K.K. helped with BM chimeric mice generation and analysis. C.M.H. helped with the cardiovascular measures of the ZKO mice. H.P. and S.A.W. provided p5RHH peptides for the nanoparticles. X.W. and D.H.F. helped with the Zbtb46 lentiviral constructs. K.C. provided overall supervision and coordinated all the experimental activities. All authors approved the final manuscript.

Corresponding author

Correspondence to Kyunghee Choi.

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Competing interests

S.A.W. and H.P. have equity with Altamira Therapeutics. The other authors declare no competing interests.

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Nature Immunology thanks Lorenzo Mortara and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Ioana Staicu, in collaboration with the Nature Immunology team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Zbtb46 is a tumor suppressor and its expression is downregulated in tumor.

a, Zbtb46 expression in different cell population in mouse Trachea and Heart analyzed by single cell RNA sequencing. Data acquired from the Tabula Muris portal: https://tabula-muris.ds.czbiohub.org/. b-c, Analysis of (b) vital cardiovascular parameters and (c) pressure-diameter measurements in the Zbtb46 KO (n = 4) and wild-type (n = 11) mice. d, Zbtb46 expression in ECs and DCs isolated from the mammary gland (MEC and MDC) of the healthy and from the PyMT-BO1 tumor-bearing (TEC and TDC) wild-type mice (n = 4 for D19-TEC and -TDC, 5 for SDC, and 6 for the remaining groups). e-f, Zbtb46 expression in ECs from Lung (LEC) and mammary gland (MEC) of the healthy wild-type mice and from the tumors (TEC) of the (e) LLC carcinoma (n = 3) and (f) MMTV-PyMT (n = 4 for MEC and 3 for TEC) bearing mice. g-h, Analysis of ZBTB46 + (GFP+) (g) ECs and (h) DCs from the lungs and spleen of the healthy and tumors of the 1956 sarcoma-bearing Zbtb46gfp/+ mice (n = 4). i, Measurements of B, CD8T, Treg, and XCR1+ cDC1-like myeloid cells in the tumor-draining lymph nodes of 1956 sarcoma-bearing mice (n = 3). j, Overall survival of patients with indicated cancer separated by ZBTB46 expression as high (>50th percentile) and low (<50th percentile). Survival data were derived from publicly available clinical records of TCGA patients. k, Activated DCs, M1 macrophages, B cells, and CD8 + T effector memory cells in high vs. low ZBTB46 expressing tumors in patients from the TCGA database analyzed with the CIBERSORT algorithm. Data are mean±SD. P-values were determined using two-tailed Student’s t-test for b, e-h, and i, One-way ANOVA with Tukey’s multiple comparison test for c or with Dunnett’s test for d, Log ranked test for j, and unpaired t-tests with Holm-Šídák multiple comparison test for k. ns=not significant.

Source data

Extended Data Fig. 2 Both endothelial and hematopoietic Zbtb46 expression contribute to the suppression of tumor progression and ZBTB46 maintains endothelial cells quiescent in the tumor context.

a, Stromal and hematopoietic Zbtb46 KO BM chimera generation scheme and FACS analysis of CD45.1 (for stromal KO) or CD45.2 (for hematopoietic KO) repopulation in PB (n = 4). b, 1956 sarcoma and PyMT-BO1 progression in wild-type (n = 7 for 1956 and 3 for PyMT-BO1), VEC-cre Zbtb46 KO (n = 4 for 1956 and 3 for PyMT-BO1), VAV-cre Zbtb46 KO (n = 7 for 1956 and 5 for PyMT-BO1), and Zbtb46 KO (n = 6 for 1956 and 3 for PyMT-BO1) mice. c, PyMT-BO1 growth in wild-type, VEC-cre Zbtb46 KO, CD11c-cre Zbtb46 KO, and Zbtb46 KO mice (n = 3). d, Zbtb46 expression in Lung-ECs from wild-type and Tamoxifen−inducible VEC-cre Zbtb46 CKO (iVEC-cre ZKO) mice (n = 3). e,1956 sarcoma growth in wild-type (n = 6), iVEC-cre ZKO (n = 6), and Zbtb46 KO (n = 5) mice. f-g, Representative images with quantification of tumoral CD31+ vessels in (f) wild-type (n = 10), VEC-cre Zbtb46 KO (n = 6), VAV-cre Zbtb46 KO (n = 7), CD11c-Cre Zbtb46 CKO (n = 4), Zbtb46 KO (n = 11), and (g) iVEC-cre ZKO mice (n = 10). h, Proliferation of the cultured parental, Zbtb46 knockdown (ZKD), and Zbtb46 overexpressing (ZOE) MCEC cells (pooled from 2 biological replicates, n = 3/replicates). i, Zbtb46 expression in tumor-ECs, tumor-DCs, and GFP+ tumors from 1956 sarcoma (n = 9) and PyMT-BO1 (n = 9 for tumor-EC and tumor-DC and 4 for tumor cells) -bearing wild-type mice with empty vector (EV) or Zbtb46 (ZOE) lentiviral overexpression construct intra-tumor treatment. j, 1956 sarcoma and PyMT-BO1 progression with empty vector (1956-EV and BO1-EV) or Zbtb46 (1956-ZOE and BO1-ZOE) lentiviral overexpression or Zbtb46 shRNA construct expression (1956-ZKD and BO1-ZKD) in wild-type mice (n = 6). k-l, Representative images and quantification for (k) vascular perfusion (n = 7) and (l) pericyte coverage (n = 5) as measured by the FITC-lectin binding to vessels and NG2+ vascular area, respectively, in the 1956 sarcoma tissue of intra-tumor EV or ZOE lentivirus treated wild-type and Zbtb46 KO mice. m, Representative images with quantification of tumoral CD31+ vessels in wild-type mice bearing 1956 sarcoma co-transplanted with parental ECs (TC + WTEC) or Zbtb46-overexpressed ECs (TC + ZOEEC) (n = 6). Data are mean±SD. P-values were determined using One-way ANOVA with Dunnett’s test for a-c, e, f, h, and k and two-tailed Student’s t-test for d, g, i, j, l, and m. ns=not significant. Scale bars=100μm (f, g, and k-m).

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Extended Data Fig. 3 Zbtb46 KO hematopoietic system is similar to wild-type in homeostasis but more immunosuppressive in the tumor and ZBTB46 sustains DC lineage generation while suppressing myeloid lineages in the tumor context.

a, 1969 regressive sarcoma growth in wild-type (n = 5), VEC-cre Zbtb46 KO (n = 5), CD11c-cre Zbtb46 KO (n = 6), and Zbtb46 KO (n = 4) mice. b, Hemavet and FACS analysis of PB, BM, and spleen in the wild-type and Zbtb46 KO mice in healthy condition (n = 3). c, MDSCs (CD11b + Gr1+) in the PB of the tumor-bearing mice in wild-type and Zbtb46 KO mice (n = 3). d, MDSC generation from wild-type and Zbtb46 KO mice BM (n = 3). Created with BioRender.com. e, Gr1+ and MHCII+ cell generation from BM-sorted CMPs and GMPs of wild-type or Zbtb46 KO mice (n = 4). f, Gr1+ and MHCII+ cell generation from wild-type BM-sorted KSL, CMPs, and GMPs with empty vector-mCherry (WT) or Zbtb46-mCherry (ZOE) overexpression (n = 3). g, Genomic snapshots depicting the ZBTB46 binding regions at the indicated genomic loci. h, Cebpb expression in BM cells of wild-type or Zbtb46 KO mice with empty vector (EV) or Zbtb46 (ZOE) lentiviral overexpression (n = 3). i, Zbtb46 and Cebpb expression in BM cells of wild-type or Zbtb46 KO mice with empty vector (EV), or Zbtb46 (ZOE), or Cebpb shRNA constructs (CKD), or Cebpb (COE) lentiviral overexpression (n = 3). j, Consensus motif for ZBTB46 and CEBPB ChIP sequences. k, Genomic snapshots depicting the CEBPB binding regions at the indicated genomic loci. l, Schematics of reporter lentivector core expression cassette for CEBP signaling pathway. Created with BioRender.com. m, Chemiluminescence measurement of SEAP activity in the reporter-only (control), or reporter with Cebpb overexpressed (COE), or reporter with Cebpb and Zbtb46 overexpressed (COE + ZOE) assay system (n = 4). n, Analysis of a few DC and macrophage signature genes in BM cells of 1956 sarcoma-bearing wild-type and Zbtb46 KO mice with empty vector (EV) or Zbtb46 (ZOE) lentiviral overexpression (n = 3). Data are mean±SD. P-values were determined using two-tailed Student’s t-test for b-f and One-way ANOVA with Dunnett’s test for h, i, m, and n. ns=not significant.

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Extended Data Fig. 4 Lenti-Zbtb46 treatment remodels tumor infiltrating lymphocytes.

a, tSNE plot from merged scRNAseq data of exclusively intratumoral lymphocytes. b, tSNE plots of lymphocytes showing select marker-gene expression. c, Violin plots displaying expression levels of select genes in CD8T cell clusters. d, Percentages of cells in CD4 and T_act clusters across different treatment. e, Violin plots displaying expression levels of select genes in CD4T cell cluster between control and treatment group. f, Heatmap of GSEA identifying pathway enrichment by T cell clusters. g, Violin plots displaying expression levels of select genes in NK cell clusters. h, Percentages of cells in NK_s3-5 clusters across different treatment. i, Heatmap of GSEA identifying pathway enrichment by NK cell clusters.

Extended Data Fig. 5 Lenti-Zbtb46 treatment remodels intratumoral macrophage/monocytes.

a, Violin plots displaying Cx3cr1 and Nos2 expression levels in the macrophage/monocyte population. b, Heatmap of GSEA identifying pathway enrichment in the macrophage/monocyte population by treatment. c, tSNE plot from merged scRNAseq data of exclusively intratumoral macrophages/monocytes. d, Violin plots displaying expression levels of select genes in macrophage/monocyte clusters. e Percentages of cells in Mac_s2-s6 clusters across treatment. f, Heatmap of GSEA identifying pathway enrichment by macrophages/monocytes clusters. g, Violin plots displaying expression levels of select genes in Mac_s2 and Mac_s4 clusters between control and treatment group.

Extended Data Fig. 6 Lenti-Zbtb46 treatment remodels intratumoral dendritic cell population.

a, tSNE plot from merged scRNAseq data of exclusively intratumoral dendritic cells (DC). b, Heatmap of GSEA identifying pathway enrichment by DC clusters. Heatmap displaying normalized expression of select genes in each DC cluster. c, Percentages of cells in DC_s1-s4 clusters across different treatment. d, tSNE plots highlighting H2-Ab1, Itgax, and Xcr1 expressing cells in the macrophage/monocyte population. Heatmap of GSEA identifying pathway enrichment by DC clusters. e, Violin plots displaying expression levels of select genes in DC_s1-s3 clusters between control and treatment group.

Extended Data Fig. 7 Lenti-Zbtb46 treatment remodels intratumoral neutrophil cell population.

a, tSNE plot from merged scRNAseq data of exclusively intratumoral neutrophils. b, Percentages of cells in Neu_s1-s3 clusters across different treatment. c, Heatmap displaying normalized expression of select genes in each neutrophil cluster. d, Heatmap of GSEA identifying pathway enrichment by neutrophil clusters. e, Ratio of the frequencies of neutrophil clusters N_s2 over (N_s1+N_s3). f, Heatmap of GSEA identifying pathway enrichment in the total intratumoral neutrophil population by Zbtb46 treatment. g, Percentage of mast cells in the tumor microenvironment across different treatment. h, Heatmap of GSEA identifying pathway enrichment in the mast cell population by treatment.

Extended Data Fig. 8 Lenti-Zbtb46 treatment reshapes the landscape of intratumoral stromal cell population.

a, tSNE plot from merged scRNAseq data of exclusively intratumoral stromal cells. b, Heatmap displaying normalized expression of select genes in each stromal cluster. c, Heatmap of GSEA identifying pathway enrichment in the endothelial cell population (Strm_c1 cluster) by treatment. d, Heatmap of GSEA identifying pathway enrichment by remaining stromal clusters. e, Percentages of cells in different stromal clusters across treatment. f, Violin plots displaying expression levels of select genes in Strm_s2-s5 (fibroblasts) cell clusters between control and treatment groups.

Extended Data Fig. 9 Systemic Zbtb46 mRNA nanoparticle treatment restricts tumor growth and enhances outcomes of anti-PD1 immunotherapy.

a-f, Tumor growth kinetic (a, d; n = 7 for control and 8 for ZmR in a; n = 8/group in d), Zbtb46 expression (b, e; n = 3 for control and 4 for ZmR), and immune microenvironment (c, f; n = 3 for control and 4 for ZmR) of 1956 sarcoma (a-c) and PyMT-BO1 breast cancer (d-f) in wild-type mice with control (EGFP mRNA nanoparticle) and Zbtb46 mRNA nanoparticle (ZmR) treatment. g, Growth of 1956 sarcoma cells co-transplanted with parental endothelial cells (WTEC) or Zbtb46 overexpressed endothelial cells (ZOEEC) with IgG or anti-PD1 treatment (n = 6 for WTEC+IgG, 7 for WTEC+Anti-PD1, 6 for ZOEEC+IgG, and 8 for ZOEEC+Anti-PD1). CR= Complete Remission. h-j, Representative images and quantification for (h) tumoral CD31+ vessels (n = 15 for control, 10 for Anti-PD1, 11 for ZmR, and 12 for Anti-PD1+ZmR), (i) pericyte coverage as measured by the NG2+ vascular area (n = 5 for control and 4 for ZmR), and (j) Gr1+ cells (n = 3), respectively, in 1956 sarcoma of wild-type mice with Zbtb46 mRNA nanoparticle (ZmR) or control (EGFP mRNA nanoparticle + IgG) treatment. Data are mean±SD. P-values were determined using two-tailed Student’s t-test for a-f, i, and j and One-way ANOVA with Dunnett’s test for g and h. ns=not significant.

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Extended Data Fig. 10 Tumor-derived factors suppress Zbtb46 expression.

a-b, Zbtb46 expression in (a) MCEC cells (n = 5 (left); n = 3 for PBS and H2O2 and 4 for the rest) and (b) BM-derived DC (BMDC) (n = 10 for PBS and PGE2 and 12 for VEGF and RA) with indicated treatments for 24 hours. c, Gr1+ and MHCII+ cell generation from wild-type BM cells with Control (PBS), or RA, or PGE2 as indicated (n = 3). Created with BioRender.com. d, Schematics depicting treatment plan for tumor-bearing mice. Created with BioRender.com. e-i, Tumor growth kinetic (e, h; n = 6 for PBS, 7 for BMS493, and 8 for NS398 and NAC-APO in e; n = 6 for PBS and BMS493 and 8 for NS398 and NAC-APO in h), Zbtb46 expression (f, i; n = 3 for tumor-EC and tumor-DC and 5 for total-BM in f; n = 3 in i), and FACS analysis of BM (g, n = 5) of 1956 sarcoma (e-g) and PyMT-BO1 breast cancer (h-i) in wild-type mice with BMS493 (inverse pan−retinoic acid receptor agonist), NS398 (selective cyclooxygenase-2 inhibitor), and NAC + APO (ROS scavengers) treatment. Data are mean±SD. P-values were determined using two-tailed Student’s t-test for a(left), e, f, h, and i and One-way ANOVA with Dunnett’s test for a(right)-c, f(right), and g. ns=not significant.

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Kabir, A.U., Zeng, C., Subramanian, M. et al. ZBTB46 coordinates angiogenesis and immunity to control tumor outcome. Nat Immunol 25, 1546–1554 (2024). https://doi.org/10.1038/s41590-024-01936-4

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