Research ArticleTUMOR IMMUNOLOGY

VEGF-A drives TOX-dependent T cell exhaustion in anti–PD-1–resistant microsatellite stable colorectal cancers

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Science Immunology  08 Nov 2019:
Vol. 4, Issue 41, eaay0555
DOI: 10.1126/sciimmunol.aay0555
  • Fig. 1 Numbers and exhaustion status of tumor-infiltrating CD8+ T cells in MSS and MSI CRC.

    (A to D) The numbers of tumor-infiltrating CD3+ (A and B) and CD8+ (C and D) T cells were analyzed by immunohistochemical staining at the invasive margin (A and C) and tumor center (B and D) in MSS (n = 125) and MSI (n = 26) CRC. Cell density was quantified by averaging the number of stained cells in randomly selected high-power fields (number of positively stained cells per square millimeter). Representative images are presented on the left side. Scale bars, 100 μm. (E) Single cells were isolated from MSS (n = 110) and MSI (n = 14) CRC, and the percentages of PD-1high, TIM-3+, LAG-3+, and TIGIT+ cells among tumor-infiltrating CD8+ T cells were analyzed by flow cytometry. Representative flow cytometry plots are presented at the top. SSC, side-scattered light. (F) The percentage of NY-ESO-1157-165–specific cells among tumor-infiltrating CD8+ T cells from HLA-A2(+) patients with MSS (n = 45) and MSI (n = 5) CRC was analyzed by flow cytometry. (G) The percentages of PD-1high, TIM-3+, LAG-3+, and TIGIT+ cells among NY-ESO-1157-165–specific, tumor-infiltrating CD8+ T cells from HLA-A2(+) patients with MSS (n = 45) and MSI (n = 5) CRC were analyzed by flow cytometry. (H) Single cells from MSS (n = 10) and MSI (n = 3) CRC were stained with cell trace violet (CTV) and stimulated with anti-CD3 antibodies, and the proliferation of CD8+ T cells was analyzed by flow cytometry. Representative histograms are presented on the left side. (I) Single cells from MSS (n = 17) and MSI (n = 9) CRC were stimulated with anti-CD3 antibodies and intracellular cytokine staining performed for IFN-γ and TNF. Representative plots are presented on the left side. Bars represent mean ± SEM; NS, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

  • Fig. 2 Immune subtypes and VEGF-A expression in MSS and MSI CRC.

    (A) The proportions of four different immune subtypes (wound healing, IFN-γ dominant, inflammatory, and lymphocyte-depleted) were analyzed in MSS and MSI CRC from TCGA CRC cohort. (B) The percentages of wound healing subtypes in TCGA pan-cancer cohort according to cancer type. Abbreviations for the cancer types were based on the suggestions of the National Cancer Institute Genomic Data Commons (http://gdc.cancer.gov) except for MSS CRC and MSI CRC. (C) The expression of VEGFA mRNA was analyzed in MSS and MSI CRC from TCGA colorectal cancer cohort. The log2 (RPKM + 1) value of VEGFA mRNA is presented. RPKM, reads per kilobase per million. (D) The expression of VEGF-A was analyzed by immunohistochemical staining of tumor tissues from MSS (n = 72) and MSI (n = 17) CRC. Representative images are presented on the left side. Scale bars, 100 μm. (E) Single cells from CRC tissues (n = 17) were cultured with brefeldin A and monensin for 12 hours and then intracellular staining was performed for VEGF-A. The proportions of tumor cells (CD45EpCAM+ cells) and tumor-infiltrating T cells (CD45+CD3+ T cells) among VEGF-A–producing cells were analyzed by flow cytometry. (F and G) Plasma concentrations of VEGF-A in patients with MSS (n = 80) and MSI (n = 8) CRC measured by enzyme-linked immunosorbent assay (F) and correlated with stages (G). Bars represent mean ± SEM; *P < 0.05; ***P < 0.001; ****P < 0.0001.

  • Fig. 3 Effects of VEGF-A on human CD8+ T cells.

    (A and B) CD8+ T cells were obtained from normal donors and stimulated with anti-CD3 antibodies for 60 hours (A) or 84 hours (B). The expression of VEGFR1 and VEGFR2 mRNA was analyzed by RT-PCR (A). β-Actin was used as an internal control. The expression of VEGFR1 and VEGFR2 in CD8+ T cells was analyzed by flow cytometry (B). Human umbilical vein endothelial cells (HUVECs) were used as a positive control. (C) The expression of VEGFR2 in CD8+ T cells from peripheral blood and tumors from MSS CRC (n = 12) was analyzed by flow cytometry. Representative histograms are presented on the left side. (D) The expression of VEGFR2 in tumor antigen–specific (NY-ESO-1157-165–specific) and bystander (CMV pp65495-503–specific) tumor-infiltrating CD8+ T cells (n = 10) was analyzed by flow cytometry. Representative histograms are presented on the left side. (E to G) PBMCs from normal donors were stimulated with anti-CD3 antibodies and VEGF-A for 84 hours. The percentages of PD-1+, TIM-3+, LAG-3+, and TIGIT+ cells among CD8+ T cells were analyzed by flow cytometry (E; n = 8). Proliferation of CD8+ T cells was analyzed by cell trace violet dilution (F; n = 5). Intracellular cytokine staining was performed for IFN-γ and TNF after 6 hours of stimulation with anti-CD3 antibodies (G; n = 6). Representative histograms or plots are presented on the left side. (H) The correlation between plasma VEGF-A concentration and the percentages of PD-1high, TIM-3+, LAG-3+, and TIGIT+ cells among tumor-infiltrating CD8+ T cells was analyzed in patients with MSS CRC (n = 49). Bars represent mean ± SEM; **P < 0.01; ***P < 0.001; ****P < 0.0001.

  • Fig. 4 Transcriptional profiles of VEGF-A–treated CD8+ T cells.

    (A to D) CD8+ T cells from normal donors (n = 4) were stimulated with anti-CD3 antibodies for 60 hours in the absence or presence of VEGF-A. Total RNA was isolated and RNA-seq analysis was performed. Hierarchical clustering of the transcriptome with or without VEGF-A treatment (A). Heatmap of genes expressed differentially by CD8+ T cells with or without VEGF-A treatment (B). Gene expression is presented as row-wise z scores of normalized read counts. GSEA of gene sets up-regulated (top) or down-regulated (bottom) in exhausted CD8+ T cells from the chronic LCMV infection model was performed using the transcriptome of VEGF-A–treated versus untreated CD8+ T cells (C). NES, normalized enrichment score. Volcano plot depicting differential expression of 1045 transcription factors in VEGF-A–treated CD8+ T cells compared with untreated CD8+ T cells (D). (E and F) PBMCs from normal donors were stimulated with anti-CD3 antibodies for 84 hours in the absence or presence of VEGF-A. The expression of NFATc1 (E) and TOX (F) was analyzed by flow cytometry (n = 4). Representative histograms are presented on the left side. (G) Cyclosporin A (CsA) was added to the culture when PBMCs were stimulated in the presence of VEGF-A and the expression of TOX was analyzed by flow cytometry (n = 6). Representative histograms are presented on the left side. MFI, mean fluorescence intensity. Bars represent mean ± SEM; ****P < 0.0001.

  • Fig. 5 TOX-dependent exhaustion of VEGF-A–treated CD8+ T cells.

    (A to C) PBMCs from normal donors (n = 6) were treated with anti-CD3 antibodies and VEGF-A for 84 hours. Twenty-four hours after starting the treatment, PBMCs were transfected with TOX siRNA or control siRNA. The expression of TOX, PD-1, TIM-3, LAG-3, and TIGIT among CD8+ T cells was analyzed by flow cytometry (A). Representative histograms are presented at the top. Proliferation of CD8+ T cells was analyzed by cell trace violet dilution (B). Intracellular cytokine staining was performed for IFN-γ and TNF after 6 hours of stimulation with anti-CD3 antibodies (C). Representative histograms or plots are presented on the left side. (D and E) CD8+ T cells from normal donors (n = 4) were stimulated with anti-CD3 antibodies and VEGF-A for 60 hours. Twenty-four hours after stimulation, CD8+ T cells were transfected with TOX siRNA or control siRNA. Total RNA was isolated and RNA-seq analysis was performed. GSEA of gene sets up-regulated (top) or down-regulated (bottom) in exhausted CD8+ T cells from the chronic LCMV infection model was performed using the transcriptome of VEGF-A–treated, control siRNA–transfected versus VEGF-A–treated, TOX siRNA–transfected CD8+ T cells (D). Hierarchical clustering of VEGF-A–untreated CD8+ T cells, VEGF-A–treated CD8+ T cells, control siRNA–transfected CD8+ T cells, and TOX siRNA–transfected CD8+ T cells (E). Bars represent mean ± SEM; ****P < 0.0001.

  • Fig. 6 TOX-dependent exhaustion of tumor-infiltrating CD8+ T cells from MSS CRC.

    (A) The correlation between the expression of TOX and immune checkpoint inhibitory receptors in tumor-infiltrating CD8+ T cells from patients with CRC (n = 124) was analyzed by flow cytometry. Data are presented as fold change in the mean fluorescence intensity of TOX in PD-1neg, TIM-3, LAG-3, or TIGIT tumor-infiltrating CD8+ T cells. (B) t-SNE analysis of the expression of TOX, PD-1, TIM-3, LAG-3, and TIGIT in tumor-infiltrating CD8+ T cells. (C) The expression of TOX in tumor antigen–specific (NY-ESO-1157-165 specific) and bystander (CMV pp65495–503 specific) tumor-infiltrating CD8+ T cells (n = 10) was analyzed by flow cytometry. (D) Tumor-infiltrating CD8+ T cells from MSS (n = 16, blue) and MSI (n = 8, red) CRC were isolated, total RNA was isolated, and RNA-seq analysis was performed. CRC cases are shown according to TOX expression level, and the CRC case with the highest TOX expression was placed on the left side. The gene expression of select genes is presented as row-wise z scores of normalized read counts. (E) The expression of TOX in tumor-infiltrating CD8+ T cells from MSS (n = 110) and MSI (n = 14) CRC was analyzed by flow cytometry. (F and G) TILs from MSS CRC were transfected with TOX siRNA or control siRNA. The expression of TOX, PD-1, TIM-3, LAG-3, and TIGIT in tumor-infiltrating CD8+ T cells was analyzed by flow cytometry (F; n = 6). Representative histograms are presented at the top. Intracellular cytokine staining was performed for IFN-γ and TNF after 6 hours of stimulation with anti-CD3 antibodies (G; n = 3). Representative plots are presented on the left side. Bars represent mean ± SEM; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

  • Fig. 7 Effects of combination blockade of PD-1 and VEGFR2.

    (A and B) NY-ESO-1157-165–specific PD-1+VEGFR2+ CD8+ T cells were cocultured with HLA-A2+PD-L1+ Caco-2 MSS CRC cells pulsed with NY-ESO-1157-165 peptide for 6 hours. T cell–mediated cytotoxicity was evaluated by TO-PRO-3 staining of PKH26-labeled Caco-2 cells (A; n = 4). Intracellular cytokine staining was performed for IFN-γ and TNF (B). Representative plots are presented. (C and D) Single cells from MSS CRC were stimulated with anti-CD3 antibodies in the absence or presence of anti–PD-1 and/or anti-VEGFR2 for 84 hours (C; n = 22) or 36 hours (D; n = 20). Proliferation of CD8+ T cells was analyzed by cell trace violet dilution (C). Intracellular cytokine staining was performed for IFN-γ and TNF after addition of brefeldin A and monensin 24 hours after stimulation (D). Data are presented as fold change relative to isotype controls. Representative histograms or plots are presented on the left side. Bars represent mean ± SEM; ***P < 0.001; ****P < 0.0001.

  • Fig. 8 Effects of VEGFR2 on CD8+ T cell functions in mouse in vivo tumor models.

    (A and B) Wild-type (WT) or T cell–specific VEGFR2 cKO mice (n = 12 for each group) were inoculated with MC38-OVA MSS CRC cells, and the tumor growth kinetics was analyzed (A). Estimated tumor volume is presented. Overall survival was analyzed with a Kaplan-Meier survival curve (B). (C to G) WT or T cell–specific VEGFR2 cKO mice were inoculated with MC38-OVA MSS CRC cells, and TILs were harvested 14 days after tumor cell inoculation (n = 5 for each group). The percentage of OVA257-265-specific cells (C), expression of TOX (D), and expression of PD-1, TIM-3, LAG-3, and TIGIT (E) among tumor-infiltrating OVA257-265-specific CD8+ T cells were analyzed. Representative plots or histograms are presented on the left side or at the top. TILs were stimulated with OVA257-265 peptide for 84 hours (F) or 36 hours (G). Proliferation of OVA257-265-specific CD8+ T cells was analyzed by cell trace violet dilution (F). Intracellular cytokine staining was performed for IFN-γ and TNF after addition of brefeldin A and monensin 24 hours after stimulation (G). Representative histograms or plots are presented on the left side. (H to J) WT mice were inoculated with MC38-OVA MSS CRC cells. Treatment with anti–PD-1 and/or anti-VEGFR2 started 14 days after tumor cell inoculation (n = 12 for each group) and the tumor growth kinetics of each treatment group was analyzed (H). Estimated tumor volume is presented. The overall survival of each treatment group is presented in Kaplan-Meier survival curves (I). Tumor tissues were harvested 21 days after tumor cell inoculation, and the expression of TOX in tumor-infiltrating OVA257-265-specific CD8+ T cells was analyzed (n = 6 for each group). ∆MFI is defined as a difference of MFI of TOX and isotype control (MFI of TOX − MFI of isotype control). MFI, mean fluorescence intensity (J). Bars represent mean ± SEM; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Supplementary Materials

  • immunology.sciencemag.org/cgi/content/full/4/41/eaay0555/DC1

    Fig. S1. Relative numbers of tumor-infiltrating T cells to tumor cells in MSS and MSI CRC.

    Fig. S2. Expression of immune checkpoint inhibitory receptors in CD8+ T cells from the peripheral blood, adjacent normal mucosa, and tumors of patients with CRC.

    Fig. S3. Expression of immune checkpoint inhibitory receptors in CD8+ T cells from the peripheral blood and adjacent normal mucosa of patients with MSS and MSI CRC.

    Fig. S4. Expression of CTAG1B in normal adjacent mucosa and tumor tissues.

    Fig. S5. Production of IFN-γ and TNF in CD8+ TILs upon anti-CD3 and anti-CD28 stimulation.

    Fig. S6. Expression of upstream regulators of wound healing signature genes in CRC.

    Fig. S7. Correlation of VEGF-A levels between plasma and tissue homogenates.

    Fig. S8. Representative histograms for the expression of immune checkpoint receptors on CD8+ T cells stimulated with anti-CD3 antibodies and VEGF-A.

    Fig. S9. Expression of immune checkpoint receptors on CD8+ T cells treated with VEGF-A in the absence of anti-CD3 stimulation.

    Fig. S10. Correlation between VEGF-A expression and T cell infiltration in MSS CRC.

    Fig. S11. Effects of NFATc1 inhibition on CD8+ T cells.

    Fig. S12. H3K27ac ChIP-seq analysis for control siRNA– or TOX siRNA–transfected CD8+ T cells after anti-CD3 and VEGF-A treatment.

    Fig. S13. GSEA analysis of tumor-infiltrating CD8+ T cell transcriptomes.

    Fig. S14. Expression of TOX in CD8+ T cells from the peripheral blood and adjacent normal mucosa of MSS and MSI CRC patients.

    Fig. S15. Characteristics of NY-ESO-1157-165–specific CD8+ T cell lines.

    Fig. S16. Effects of the blockade of PD-1 and VEGF-A on the function of tumor-infiltrating CD8+ T cells.

    Fig. S17. Effects of the blockade of PD-1, VEGFR2, and VEGF-A on the phenotype of tumor-infiltrating CD8+ T cells.

    Fig. S18. Expression of wound healing signature genes and VEGF-A in MC38-OVA tumor tissues.

    Fig. S19. Effects of T cell depletion in vivo.

    Fig. S20. Expression of VEGFR2 in tumor-infiltrating CD8+ T cells from wild-type and T cell–specific VEGFR2 conditional knockout mice.

    Fig. S21. Effects of in vivo blockade of PD-1 and VEGFR2 on the phenotype of OVA257-265-specific, tumor-infiltrating CD8+ T cells.

    Table S1. Raw data (Excel).

    Table S2. List of transcription factors up-regulated by VEGF-A treatment in CD8+ T cells during antigen recognition [Log2(fold change) > 2 and adjusted P < 0.05; Excel].

    Table S3. List of patients (Excel).

    Table S4. Key resources (Excel).

  • Supplementary Materials

    The PDF file includes:

    • Fig. S1. Relative numbers of tumor-infiltrating T cells to tumor cells in MSS and MSI CRC.
    • Fig. S2. Expression of immune checkpoint inhibitory receptors in CD8+ T cells from the peripheral blood, adjacent normal mucosa, and tumors of patients with CRC.
    • Fig. S3. Expression of immune checkpoint inhibitory receptors in CD8+ T cells from the peripheral blood and adjacent normal mucosa of patients with MSS and MSI CRC.
    • Fig. S4. Expression of CTAG1B in normal adjacent mucosa and tumor tissues.
    • Fig. S5. Production of IFN-γ and TNF in CD8+ TILs upon anti-CD3 and anti-CD28 stimulation.
    • Fig. S6. Expression of upstream regulators of wound healing signature genes in CRC.
    • Fig. S7. Correlation of VEGF-A levels between plasma and tissue homogenates.
    • Fig. S8. Representative histograms for the expression of immune checkpoint receptors on CD8+ T cells stimulated with anti-CD3 antibodies and VEGF-A.
    • Fig. S9. Expression of immune checkpoint receptors on CD8+ T cells treated with VEGF-A in the absence of anti-CD3 stimulation.
    • Fig. S10. Correlation between VEGF-A expression and T cell infiltration in MSS CRC.
    • Fig. S11. Effects of NFATc1 inhibition on CD8+ T cells.
    • Fig. S12. H3K27ac ChIP-seq analysis for control siRNA– or TOX siRNA–transfected CD8+ T cells after anti-CD3 and VEGF-A treatment.
    • Fig. S13. GSEA analysis of tumor-infiltrating CD8+ T cell transcriptomes.
    • Fig. S14. Expression of TOX in CD8+ T cells from the peripheral blood and adjacent normal mucosa of MSS and MSI CRC patients.
    • Fig. S15. Characteristics of NY-ESO-1157-165–specific CD8+ T cell lines.
    • Fig. S16. Effects of the blockade of PD-1 and VEGF-A on the function of tumor-infiltrating CD8+ T cells.
    • Fig. S17. Effects of the blockade of PD-1, VEGFR2, and VEGF-A on the phenotype of tumor-infiltrating CD8+ T cells.
    • Fig. S18. Expression of wound healing signature genes and VEGF-A in MC38-OVA tumor tissues.
    • Fig. S19. Effects of T cell depletion in vivo.
    • Fig. S20. Expression of VEGFR2 in tumor-infiltrating CD8+ T cells from wild-type and T cell–specific VEGFR2 conditional knockout mice.
    • Fig. S21. Effects of in vivo blockade of PD-1 and VEGFR2 on the phenotype of OVA257-265-specific, tumor-infiltrating CD8+ T cells.

    Download PDF

    Other Supplementary Material for this manuscript includes the following:

    • Table S1. Raw data (Excel).
    • Table S2. List of transcription factors up-regulated by VEGF-A treatment in CD8+ T cells during antigen recognition Log2(fold change) > 2 and adjusted P < 0.05; Excel.
    • Table S3. List of patients (Excel).
    • Table S4. Key resources (Excel).

    Files in this Data Supplement:

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