Unleashing Type-2 Dendritic Cells to Drive Protective Antitumor CD4+ T Cell Immunity

Abstract

Differentiation of proinflammatory CD4⁺ conventional T cells (T_conv) is critical for productive antitumor responses yet their elicitation remains poorly understood. We comprehensively characterized myeloid cells in tumor draining lymph nodes (tdLN) of mice and identified two subsets of conventional type-2 dendritic cells (cDC2) that traffic from tumor to tdLN and present tumor-derived antigens to CD4⁺ T_conv, but then fail to support antitumor CD4⁺ T_conv differentiation. Regulatory T cell (T_reg) depletion enhanced their capacity to elicit strong CD4⁺ T_conv responses and ensuing antitumor protection. Analogous cDC2 populations were identified in patients, and as in mice, their abundance relative to T_reg predicts protective ICOS⁺ PD-1^lo CD4⁺ T_conv phenotypes and survival. Further, in melanoma patients with low T_reg abundance, intratumoral cDC2 density alone correlates with abundant CD4⁺ T_conv and with responsiveness to anti-PD-1 therapy. Together, this highlights a pathway that restrains cDC2 and whose reversal enhances CD4⁺ T_conv abundance and controls tumor growth.

Keywords: CD4(+) T cells; T cell priming; checkpoint blockade; dendritic cells; immunotherapy; regulatory T cells; tumor immunology; tumor microenvironment.

Figure 1

Unbiased scRNA-seq of myeloid cells in the tdLN reveals extensive heterogeneity. (A) t-SNE display and graph-based clustering of CD90.2⁻ B220⁻ NK1.1⁻ CD11b⁺ and/or CD11c⁺ myeloid cells sorted from B16F10 tdLN and processed for scRNA-seq. Each dot represents a single cell. (B) Expression of ImmGen population-specific gene signatures distributed across t-SNE plot of (A). (C) Heatmap displaying top 10 DE genes for each cluster when comparing clusters 0 through 7 (ranked by fold change) (D) (left) A heatmap displaying the top 30 DE genes between clusters 0 and 4, with Cd9 highlighted by a red line. (right) A flow cytometry histogram displaying the differential surface expression of CD301b between CD9⁻ and CD9⁺ CD11b⁺ CD24⁻ DCs (E) Representative gating strategy used to identify myeloid populations in the tdLN (F) Representative flow cytometry histograms displaying levels of ZsGreen tumor antigen within myeloid populations in the tdLN (left). Frequency of ZsGreen⁺ cells within t dLN myeloid populations (right). Data pooled from two independent experiments. Figure 2

Figure 2

mCD301b^−/+ cDC2 are uniquely able to induce anti-tumor CD4⁺ T_conv proliferation but fail to initiate CD4⁺ T_conv differentiation. (A-D) Purified CD4⁺ OT-II T cells were co-cultured ex vivo with sorted APC populations from tdLN and analyzed at 3 days. (A) Absolute number of live OT-II T cells recovered from co-culture, normalized and statistically compared to mCD301b⁺ condition (t-test). (B) Histograms of OT-II T cell dye dilution (left). Frequency of recovered OT-II T cells that had undergone division with statistical comparison to mCD301b⁺ condition (t-test) (right). (C) Absolute number of live OT-II T cells recovered from co-culture containing exogenous OVA peptide (323–339), normalized and statistically compared to mCD301b⁺ condition (t-test). (D) Histograms of OT-II T cell dye dilution (left). Frequency of recovered OT-II T cells that had undergone division with statistical comparison to mCD301b⁺ condition (t-test) (right). (E) Frequency of tdLN DC populations in control or Irf4^−/− tumor-bearing mice. (F) Purified CD45.1⁺ OT-II T cells were adoptively transferred to control or Irf4^−/− B16^ChOVA tumor-bearing mice with tdLN harvested 3 days later to assess OT-II T cell dye dilution (left) and quantify the frequency of cells that had divided (middle) and their frequency of endogenous CD4⁺ T cells (right). (G-K) CD45.1⁺ CD4⁺ OT-II T cells were transferred to wild-type mice that were inoculated with B16^chOVA (tdLN^B16ChOVA), endoOVA, or X31^pOVA and draining LNs were harvested for analysis. (G) Cell surface Cd69 levels on divided CD45.1⁺ CD4⁺ OT-II T cells (left) and quantification of MFI with each cell division as determined by dye dilution (right) 3 days following transfer. Surface CD44 (H) and CD62L (I) levels on transferred CD45.1⁺ CD4⁺ OT-II T cells (left) and quantification of MFI (right) 3 days following transfer. (J) Frequency of transferred CD45.1⁺ CD4⁺ CD44⁺ OT-II T cells that are ICOS⁺PD-1^lo T_h1-like. (K) Frequency of transferred CD45.1⁺ CD4⁺ CD44⁺ OT-II T cells that produce IL-4, IL-17A and IFNγ following PMA/Ionomycin restimulation with detection by intracellular antibody staining 7 days after transfer. Data are represented as average ± SEM unless explicitly specified. *P <0.05, **P<0.01, ***P<0.001, ****P<0.0001.

Figure 3

Regulatory T cell depletion enhances cDC2 migration to the tdLN and unleashes an anti-tumor CD4⁺ T_conv response. (A) Dot plot correlation of intratumoral CD11b⁺ CD301b^−/+ cDC2 frequency within MHC-II⁺ cells against CD4⁺ T_conv within CD90.2⁺ (left) or T_reg (right) within CD90.2⁺. Dots colored according to ratio of B16-F10:B16^Gm-csf cells in the tumor. Two pooled experiments displayed. (B) Tumor growth from control and Foxp3^DTR mice. Upward facing black arrowheads indicate DT treatment. Results depict tumor growth curves of individual mice. (C) Tumor growth from control or Foxp3^DTR mice injected with isotype/anti-CD4/anti-CD8 depleting antibodies. Results depict tumor growth curves of individual mice. Two pooled experiments displayed. (D) Tumor growth from control or Foxp3^DTR mice injected with with vehicle or FTY720. Results depict tumor growth curves of individual mice. Two pooled experiment displayed. (E) CD45.1⁺ CD4⁺ OT-II T cells were adoptively transferred into DT-treated control or Foxp3^DTR B16^ChOVA-tumor-bearing mice and recovered 3 days later for analysis of dye dilution (left) and quantification of absolute number of OT-II present within the tdLN (right). Three pooled experiments displayed with normalization to control. (F) Control and Foxp3^DTR B16^ZsGreen tumor-bearing mice were treated with DT and absolute number of ZsGreen⁺ migratory DC in the tdLN were analyzed at day 5 post-DT. (G) Control and Foxp3^DTR B16^ZsGreen tumor-bearing mice were treated with DT and absolute number of ZsGreen⁺ CD11b⁺ cDC2 in the tdLN were analyzed at day 0, 1, 3 and 5 post-DT. Data displayed as percent of maximum absolute number. Samples statistically compared to day 0 DT condition. (H) Control and Foxp3^DTR B16^ZsGreen tumor-bearing mice were treated with DT and analyzed for the frequency of CD4⁺ T_conv expressing CD69 and CD44 at day 0, 1, 3 and 5 post-DT. Data displayed as frequency of maximum expression. Samples statistically compared to day 0 DT condition. Data are represented as average ± SEM. *P <0.05, **P<0.01, ***P<0.001, ****P<0.0001.

Figure 4

Regulatory T cell depletion enhances cDC2 function and CD4⁺ T_conv differentiation. (A-C) Purified CD4⁺ OT-II T cells were co-cultured with tdLN APC populations sorted from tdLN of control or Foxp3^DTR B78chOVA-bearing animals and harvested 3 days after plating for analysis. (A) Absolute number of live OT-II T cells recovered, normalized and statistically compared to mCD301b⁺ condition. (B) Frequency of recovered OT-II T cells that had undergone division, statistically compared to mCD301b⁺ condition (t-test). (C) Cell surface CD69 levels on divided OT-II. (D) Volcano plots displaying DE expressed genes comparing control and Foxp3DTR tdLN mCD301b⁻ (left) and mCD301b⁺ (right). Log N fold cutoff of 0.4 used. Genes of interest labelled. (E) Cell surface levels of CD80 and CD86 on mCD301b⁻ and mCD301b⁺ in control and Foxp3^DTR tdLN. (F) Frequency of CD44⁺ CD4⁺ T_conv that are ICOS⁺ PD-1^lo in control and Foxp3^DTR tdLN (left). Frequency of tdLN CD44⁺ CD4⁺ T_conv producing IL-4, IL-17A or IFNγ from control or Foxp3^DTR tumor-bearing mice following ex vivo restimulation (right). (G) Frequency of CD44⁺ CD4⁺ T_conv that are ICOS⁺ PD-1^lo in control and Foxp3^DTR TME (left). Frequency of CD44⁺ CD4⁺ T_conv producing IL-4, IL-17A or IFNγ in control or Foxp3^DTR TME following ex vivo restimulation (right). (H, I) Control and Foxp3^DTR tumor-bearing mice were treated with FTY720 or vehicle and tdLN (H) or tumor (I) were harvested to quantify frequency of CD45⁺ cells that are CD44⁺ CD4⁺ ICOS⁺ PD-1^lo T_conv (left) and are IFNγ-producing CD44⁺ CD4⁺ T_conv following ex vivo restimulation (right). Representative experiment displayed. Data are represented as average ± SEM. *P <0.05, **P<0.01, ***P<0.001, ****P<0.0001.

Figure 5

Anti-CTLA-4 induces expansion and functional enhancement of CD11b⁺ cDC2. (A) Frequency of T_reg within CD4⁺ T cells in tdLN (left) or tumor (right) from B16^ZsGreen tumor-bearing mice treated with mouse IgG2c isotype or anti-CTLA-4 with a mouse IgG2c Fc. (B) Absolute number of ZsGreen⁺ DC in tdLN (normalized to weight of associated tumor). (C) Frequency of CD44⁺ CD4⁺ T_conv with ICOS⁺ PD-1^lo surface phenotype in tdLN (left) or tumor (right). (D) DC frequency of CD45⁺ cells within the vaccine site of mice treated with BvAX^+/− αCTLA-4 or GVAX +/− αCTLA-4. (E) Frequency of T_reg amongst CD4⁺ T cells (left) and frequency of CD44⁺ CD4⁺ T_conv or CD44⁺ cD8⁺ T cells amongst CD90.2⁺ T cells within the vaccine site of mice treated with BVAX +/− αCTLA-4 or GVAX +/− αCTLA-4 (right). (F) Quantification of CD80 and CD86 DMFI on mCD301b⁻ (left) or mCD301b⁺ (right) within the vaxLN of mice treated with BVAX +/− αCTLA-4 or GVAX +/− αCTLA-4. (G) Tumor growth from mice treated with BVAX +/− αCTLA-4 or GVAX +/− αCTLA-4. Ratio represents number of mice with tumors that displayed profound response (< 250mm³). Dotted line signifies 250 mm³. Representative experiment displayed. (H) DC frequency of either CD45⁺ or live cells within the vaccine site (left) or vaxLN (right) of control or Irf4^Δ/Δ mice treated with GVAX-B16^ChOVA and anti-CTLA-4. (I) Purified CD45.1⁺ OT-II T cells were adoptively transferred to control or Irf4^Δ/Δ mice treated with GVAX-B16^ChOVA and anti-CTLA-4 and vavLN were harvested 3 days later to assess OT-II T cell dye dilution (left) and quantify the frequency of cells that had divided (middle) and their frequency of endogenous CD4⁺ T cells (right). Data are represented as ± average SEM. *P <0.05, **P<0.01, ***P<0.001, ****P<0.0001.

Figure 6

scRNA-seq of the human tdLN reveals heterogeneity within BDCA-1⁺ cDC2. (A) t-SNE display of CD45⁺ CD3⁻ CD19/20⁻ CD56⁻ myeloid cells sorted from a human melanoma tdLN and processed for scRNA-seq with pDC, neutrophil, NK cell, T cell and B cell contaminants removed from graph-based clustering analysis. (B) Heatmap displaying top 10 DE genes for each cluster when comparing clusters 0 through 6 (ranked by fold change). (C) Gene overlays of markers associated with various myeloid cell types on human tdLN t-SNE. (D) t-SNE display and graph-based clustering of BDCA-1⁺ cDC2 (cluster 0) from (A). (E) Heatmap displaying DE genes between clusters 0.1–0.3 with genes of interested labelled. (F) Violin plots displaying expression probability differences for denoted genes within clusters 0.1–0.3. (G) Gating strategy (left) in human TME to identify BDCA-3⁺ cDC1, CD14⁻ BDCA-1⁺ cDC2, CD14⁺ BDCA-1⁺ cDC2. Cell surface expression of CCR7 on BDCA-3⁺ cDC1, CD14⁻ BDCA-1⁺ cDC2, CD14⁺ BDCA-1⁺ cDC2 (right).

Figure 7

BDCA-1⁺ cDC2 proportion in the human TME impacts CD4⁺ T_conv proportion and quality. (A) Dot plot of BDCA-1⁺ cDC2 frequency of HLA-DR⁺ cells and T_reg frequency of CD3⁺ T cells as quantified by flow cytometry in 32 human HNSC tumor samples. Dotted lines represent demarcation of samples divided based on proportion of BDCA-1⁺ cDC2 (CD14^−/+) and T_reg. (B) The frequency of CD4⁺ T cells (of CD3⁺ T cells) within each type of TME identified in (A). (C) Surface expression of ICOS and PD-1 on CD4⁺ T_conv, as a normalized geometric MFI, within each type of human TME identified in (A). (D) Percent of patients with a given stage of cancer at the time of flow cytometric analysis. (E) Progression-free survival since disease diagnosis. Mantel-Cox test performed between groups. (F) 19 human melanoma tumor samples (14 anti-PD-1 responder, 5 anti-PD-1 non-responders – see S6E) were parsed based on abundance of BDCA-3⁺ cDC1 and plotted for proportions of both BdCA-3⁺ cDC1 (black) and BDCA-1⁺ cDC2 (orange). Responders were parsed based on those high for either BDCA-3⁺ cDC1 (above median split of 3.63) or BDCA-1⁺ cDC2 (above median split of 12.4). (G) Frequency of CD3⁺ T cells that are CD8⁺ T cells (left) and CD4⁺ T_conv (right) from the two groups identified in (F). (H) Proportions of T_reg amongst CD3⁺ T cells in samples from HNSC (A-E) and skin cutaneous melanoma (SKCM) (includes anti-PD-1 responders and non-responders) (F, G). Data are represented as ± average SEM. *P <0.05, **P<0.01, ***P<0.001, ****P<0.0001.