Neuroblastoma Formation Requires Unconventional CD4 T Cells and Arginase-1-Dependent Myeloid Cells

Abstract

Immune cells regulate tumor growth by mirroring their function as tissue repair organizers in normal tissues. To understand the different facets of immune-tumor collaboration through genetics, spatial transcriptomics, and immunologic manipulation with noninvasive, longitudinal imaging, we generated a penetrant double oncogene-driven autochthonous model of neuroblastoma. Spatial transcriptomic analysis showed that CD4⁺ and myeloid populations colocalized within the tumor parenchyma, while CD8⁺ T cells and B cells were peripherally dispersed. Depletion of CD4⁺ T cells or CCR2⁺ macrophages, but not B cells, CD8⁺ T cells, or natural killer (NK) cells, prevented tumor formation. Tumor CD4⁺ T cells displayed unconventional phenotypes and were clonotypically diverse and antigen independent. Within the myeloid fraction, tumor growth required myeloid cells expressing arginase-1. Overall, these results demonstrate how arginine-metabolizing myeloid cells conspire with pathogenic CD4⁺ T cells to create permissive conditions for tumor formation, suggesting that these protumorigenic pathways could be disabled by targeting myeloid arginine metabolism. SIGNIFICANCE: A new model of human neuroblastoma provides ways to track tumor formation and expansion in living animals, allowing identification of CD4⁺ T-cell and macrophage functions required for oncogenesis.

Graphical abstract

Figure 1.

Point mutations in the endogenous Alk locus and neuroblastoma formation. A, Diagram of the two ALK mutations introduced into the endogenous Alk locus. B, Experimental design of the longitudinal study for animals reported herein. C, Incidence and survival curves comparing tumor formation of Alk^F1178L; TH-MYCN or Alk^Y1282S; TH-MYCN mice. Representative image of an Alk^F1178L; TH-MYCN mouse with a large abdominal neuroblastoma. D, Clustered heat map of “signature” gene expression comparing murine neuroblastoma (NB) models and other human solid tumors. E, GD2 expression in CD45⁻ tumor cells. Purple and green histograms show GD2 expression from two individual tumors compared with isotype control (gray histogram). F, CD276 (B7-H3) expression in tumor cells. Purple and green histograms show CD276 expression from CD45⁻ cells from two individual tumors compared with isotype control (gray histogram). G, Frequency of PD-L1– and PD-L2–expressing cells in CD45⁺ or CD45⁻ intratumoral populations. In C, data were analyzed by the log-rank test. Criteria for scoring tumor incidence and inclusion and exclusion criteria are described in Materials and Methods. In D, the complete transcriptional signature is available in Supplementary Table S3 and available in full using accession numbers GSE12460, GSE13136, GSE16237, GSE37372, GSE29683, E-TABM-1202, GSE27516, GSE98763, and GSE27516. Red font, canonical neuroblastoma-associated mRNAs.

Figure 2.

Single-cell gene expression and spatial transcriptomic analysis of the neuroblastoma landscape characterize tumor-infiltrating immune populations and tumor cell subsets. A, t-SNE dimensionality reduction of mouse Alk^F1178L; TH-MYCN CD45⁻ and CD45⁺ tumor cells based on scGEX data, with cell clusters identified based on marker gene expression (Supplementary Fig. S1C). DC, dendritic cell; Tfh, T follicuar helper. B, Feature plot of tumor cells indicated by module scoring of Ncam1, Th, and Mycn expression. C, Box plots representing the proportion of cell types among the tumor-infiltrating CD45⁺ cells using the clusters identified in the scGEX analysis. Colors indicate replicate tumor identity within and across plots. D, Feature plots showing expression of gene markers of specific myeloid populations found in the tumor sample. E, Spatial transcriptomics feature plots from a representative section (A1), where expression of individual genes is overlaid on tumor section. Capture area points are enlarged for ease of visualization and are transparent for values below 0.1 on the accompanying color scale. Tumor cluster signatures represent classification scores derived from integration of scGEX data with spatial transcriptomics data. F, Violin plots of genes enriched in tumor cluster 3 compared with tumor cluster 7, including neural-like genes and cancer-associated genes. G–I, Spatial transcriptomics feature plots from a representative neuroblastoma section (A1) for B cells, CD8⁺ T cells, CD4⁺ T cells, and macrophages. Cd8a and Cd4 values are from section-specific log normalization. J, Box plots showing scGEX signature classification scores from spatial transcriptomics section A1 for capture spots with a macrophage classification score of 0 (no macs) versus spots with a positive macrophage classification score (with macs). Statistical comparisons were made with Wilcoxon rank sum tests.

Figure 3.

CD4⁺, but not CD8⁺ or B cells, are pathogenic in Alk^F1178L; TH-MYCN neuroblastoma. A, Incidence and survival curves comparing tumor formation between Alk^F1178L; Rag1^−/−; TH-MYCN mice and Alk^F1178L; TH-MYCN mice. B, Incidence and survival curves of Alk^F1178L; TH-MYCN mice treated with dual anti-CD19 and anti-B220 antibodies or control. C, Incidence and survival curves in Alk^F1178L; TH-MYCN mice treated with anti-CD8 depleting antibody or control. D, Flow cytometric analysis of MHC class I expression on intratumoral CD45⁺ and CD45⁻ populations. E, Incidence and survival curves in Alk^F1178L; TH-MYCN mice treated with anti-CD4 depleting antibody or control. F, Successful depletion of CD4⁺ T cells in the tumor (first panel). Presence of Foxp3⁺ CD8⁺ cells in Alk^F1178L; TH-MYCN mice treated with anti-CD4 depleting antibody. Data are representative of n = 2 mice. G, Dot plot of genes enriched across the CD4⁺ T-cell clusters in these tumor samples with genes binned in functional groups “Conventional CD4 genes,” “Cancer-related,” “Unconventional lineage markers,” and “Residency genes.” Color corresponds to expression of each gene relative to the average among the four focal populations, and the size of the dot represents the proportion of cells from the cluster expressing each gene. H, Donut plot of the frequency (freq) of Foxp3⁺ cells within each cluster. Clusters with 0% cells expressing Foxp3 are not shown. I, Flow cytometric analysis of tumor-resident CD4⁺ cells. CD4⁺ CD62L⁻ cells express higher amounts of the “unconventional” markers Foxp3, Helios, PD1, and ICOS than CD4⁺ CD62L⁺ cells. J, t-SNE of only CD4⁺ T cells subsetted from the full dataset, with subclusters identified on the basis of marker gene expression. Dotted line indicates CD4 cluster 7. K, CD4 t-SNE from J, with colors indicating the originating tumor. Dotted line indicates CD4 cluster 7. L, Dot plot of “Unconventional lineage markers.” In A–C and E, data were analyzed by the log-rank test.

Figure 4.

Tumor-resident CD4⁺ CD25⁺ cells are not antigen specific. A, CD4⁺ CD25⁺ cells were isolated from Alk^F1178L; TH-MYCN mice for TCR repertoire analysis. TCRdist trees (right) with dashed ellipses indicating groups of similar TCRs, or neighbors, as a cluster. Representative TCR logos (left) depict most highly used V and J genes, CDR3 amino acid sequences, and predicted VDJ rearrangement of each cluster (n = 4 mice, 262 TCR clones). B, Clone pie charts for four independent mice. Each wedge represents a unique TCR clone. The size of top clone is in red, and total number of sequences is in black. C, CD4 cells migrate to the tumor in an antigen-independent manner. Alk^F1178L; TH-MYCN mice were intravenously injected with 5 × 10⁶ CD4⁺ cells from OT-II mice prior to tumor formation. Tumors from mice receiving OT-II donor cells show increased numbers of Vβ5⁺ CD4 cells (right) compared with control mice (left).

Figure 5.

Myeloid Arg1 is pathogenic in neuroblastoma. A, Incidence and survival curves comparing tumor formation of Alk^F1178L; TH-MYCN; Ccr2^−/− mice. B, Feature plots showing cell-specific expression of Arg1. C, Dot plot of enzymes and known markers of monocyte, macrophage, and granulocyte populations. Color corresponds to expression of each gene relative to the average among the four focal populations, and the size of the dot represents the proportion of cells from the cluster expressing each gene. D, CD45⁻ tumor cells express negligible Arg1 as detected by flow cytometry. E, Arg1 expression is predominantly expressed in CD45⁺ cells that also express CD68 and CCR2. Data are representative of three independent tumors. F, Heat map and volcano plot of gene expression in amino acid–starved CD4⁺ T cells. Data are from three biological replicates. Complete microarray data available in GEO (accession number GSE126024). G, Amino acid–starved CD4⁺ T cells reversibly increase Foxp3 expression. T cells were stimulated in the presence of APC in complete RPMI containing 100% (1200 μmol/L) or 1% (12 μmol/L) l-arginine with or without TGFβ and Foxp3 expression measured after 72 hours. Data are representative of n = 5 biologically independent experiments. H, Amino acid–starved CD4⁺ cells have increased expression of the “unconventional” markers Foxp3, Helios, and ICOS (but not PD1) compared with nonstarved CD4⁺ cells. I, Incidence and survival curves comparing tumor formation between Alk^F1178L; TH-MYCN; Stat6^−/−mice and Alk^F1178L; TH-MYCN mice. J, Incidence and survival curves comparing tumor formation of Alk^F1178L; TH-MYCN mice lacking Arg1 in all hematopoietic cells. K, Pairwise HRs as determined by CoxPH regression modeling. Reported P values are adjusted for multiple comparisons. F, female; M, male; WT, wild-type. Error bars represent the SE of the coefficients. In A, I, and J, data were analyzed by the log-rank test.