Systemic Immunity Is Required for Effective Cancer Immunotherapy

Abstract

Immune responses involve coordination across cell types and tissues. However, studies in cancer immunotherapy have focused heavily on local immune responses in the tumor microenvironment. To investigate immune activity more broadly, we performed an organism-wide study in genetically engineered cancer models using mass cytometry. We analyzed immune responses in several tissues after immunotherapy by developing intuitive models for visualizing single-cell data with statistical inference. Immune activation was evident in the tumor and systemically shortly after effective therapy was administered. However, during tumor rejection, only peripheral immune cells sustained their proliferation. This systemic response was coordinated across tissues and required for tumor eradication in several immunotherapy models. An emergent population of peripheral CD4 T cells conferred protection against new tumors and was significantly expanded in patients responding to immunotherapy. These studies demonstrate the critical impact of systemic immune responses that drive tumor rejection.

Keywords: cancer immunotherapy; immune responses; immunotherapy; mass cytometry; secondary lymphoid organs; single-cell analysis; systems immunology; tumor immunology; tumor microenvironment.

Copyright © 2017 Elsevier Inc. All rights reserved.

Figures

Figure 1. Tumor-binding antibodies and dendritic cell adjuvants induce rejection of spontaneous breast tumors

(A) MMTV-PyMT mice with tumors of 25mm2 treated with allogeneic IgG pooled from C57BL/6 and CD-1 mice, anti-CD40 and IFNγ or untreated. (B) H&E and (C) immunofluorescence of tumors from treated mice 8 days after therapy. (D) Mass cytometry experiment. (E) Binding of IgG antibodies from naïve CD-1 or C57BL/6 mice to MMTV-PyMT tumor cells. (F) Tumor sizes, day 8 after therapy, for mass cytometry. See also Fig. S1, Table S1.

Figure 2. The tumor microenvironment is remodeled and immune cells transiently proliferate during effective responses

(A) Statistical Scaffold map of the tumor on day 3. Black nodes are Landmark nodes, representing canonical cell populations identified manually. Other nodes reflect unsupervised clustering of live leukocytes (see Methods). Clusters in red denote populations significantly higher in frequency with effective therapy; blue clusters are significantly lower in frequency. pDC are in the dashed box to maximize space. Colored boxes are populations analyzed in B–E. (B) Expression profile of B cell, (C) cDC, (D) NK cell, or (E) Treg cell clusters expanding with effective therapy (red) versus those decreasing (blue). (F) Scaffold map of Ki67 expression in immune cells in the tumor on day 3. Subsets more proliferative after effective therapy in red. (G) Percent of Ki67+ Treg. (H) Percent of Ki67+ cDC. (I) Scaffold map of the tumor on day 8. (J) Expression profile of macrophage clusters expanding with effective therapy (red) versus those decreasing (blue). (K) Expression profile of ILC cluster increasing with effective therapy. (L) ILC1 frequencies. (M) Expression profile of CD4 T cell or (N) CD8 T cell cluster increasing with effective therapy. (O) Scaffold map of Ki67 expression in immune cells in the tumor on day 8. See also Fig. S2–S4, Tables S2–S3.

Figure 3. Cells in the tumor-draining lymph node display sustained activation

(A) Scaffold map of the draining lymph node on day 3. (B) Expression profile of B cell clusters expanding with effective therapy (red) versus those not changing (black). (C) Expression profile of Th1, (D) Treg or (E) CD8 T cell clusters increasing with effective therapy. (F) Scaffold map of Ki67 expression in cells in the draining lymph node on day 3. (G) Expression of CD44 and Ly6C in T cell clusters. (H) Scaffold map of the draining lymph node on day 8. (I) Expression profile of B cell, (J) CD4 T cell or (K) CD8 T cell clusters expanding with effective therapy (red) versus those decreasing (blue). (L) Frequency of Treg clusters. (M) Scaffold map of Ki67 expression in the draining lymph node on day 8. See also Fig. S4–S5, Tables S2–S3.

Figure 4. Immune responses are sustained in peripheral blood

(A) Scaffold map of blood on day 3. (B) Expression profile of B cell, pDC, (D) CD4 T cell, (E) Th1 cell,. (F) CD8 T cell, (G) Ly6C+ monocyte, or (H) Ly6C- monocyte clusters expanding with effective therapy (red histogram) versus those decreasing (blue histogram). (I) Scaffold map of Ki67 expression in immune cell clusters in blood on day 3. (J) Scaffold map of blood on day 8. (K) Frequency of platelets on day 8. (L) Scaffold map of Ki67 expression in cells in blood on day 8. See also Fig. S4, S6, Tables S2–S3.

Figure 5. Interfering with systemic immune responses prevents effective immunotherapy

(A) MMTV-PyMT tumor-bearing mice treated with alloIgG, anti-CD40, IFNγ and daily FTY720 or ethanol control starting one day before therapy. (B) Mice with orthotopic 4T1 tumors treated as in A. (C) Immunofluorescence of 4T1 tumors 14 days after therapy. (D–E) 4T1 lung metastases 20 days after therapy. (F) T cells from spleen and lymph nodes of mice with 4T1 tumors, treated with alloIgG, anti-CD40, IFNγ and FTY720 were transferred with IL-2 into naïve Balb/c mice. Controls only received IL-2. Recipients were challenged s.c. with 4T1 cells the next day. (G) MC38 tumor-bearing mice untreated or treated with anti-PD-1 and ethanol control or FTY720. All p-values reflect two-tailed, heteroskedastic t-tests in R. Error bars represent S.D.

Figure 6. A CD4 T cell subset from the periphery is sufficient to mediate anti-tumor immunity

(A) Pairwise correlations and hierarchical clustering of immune cell frequencies across organs of mice treated with effective therapy. (B) Adjacency matrix from panel A ordered by connectivity. CD4 T cells in black; CD8 T cells in white. (C) CD44+ CD4 or CD8 T cells from the lymph node, spleen and blood of MMTV-PyMT mice treated with effective therapy were expanded and transferred into treatment-naïve MMTV-PyMT mice (n=3–4 per group). (D) Force-directed graph of T cells from each tissue, time and treatment. Colored by tissue of origin. Light colors indicate initiation phase; dark colors indicate rejection phase. Clusters from mice receiving no or ineffective therapy are black. Node size reflects the frequency of T cells in that cluster as a percent of T cells by tissue. (E) CD4 T cells enriched in the periphery after effective therapy. (F) Frequency of Tbet+CD44+CD62L-CD27low CD4 T cells in the draining lymph node of BP melanoma mice on day 8. (G) CD44+CD62L-CD27low CD4 T cells were isolated from the lymph node, spleen and blood of MMTV-PyMT mice treated with effective therapy. Treatment-naïve MMTV-PyMT mice were sublethally irradiated, and sorted T cells (n=4) or PBS control (n=3) was injected i.v. All p-values reflect two-tailed, heteroskedastic t-tests in R. Error bars represent S.D. (H) Scaffold map of flow cytometry data from blood of melanoma patients treated with anti-CTLA-4 antibodies and GM-CSF, 3 weeks after therapy began. Red nodes are cell subsets significantly expanded in responding patients compared to non-responders. (I) Frequency of CD4+PD-1-CD127low T cells (identified manually) of total leukocytes, analyzed by two-tailed Wilcoxon rank-sum test. See also Fig. S7.

Figure 7. PD-L1 blockade combined with tumor-binding antibody therapy enables distal tumor rejection in multifocal disease

(A) Scaffold map denoting PD-L1 expression in immune cells in the tumor between effective and ineffective groups on day 3. (B) Percent of tumor cells expressing PD-L1 on day 3. (C) Scaffold maps representing changes in PD-L1 expression in the draining lymph node or (D) blood. (E) PD-L1 expression in un-injected tumors in MMTV-PyMT mice with multi-focal disease on day 3. (F) Frequency of PD-L1+ leukocytes in un-injected tumors of treated or untreated mice. (G) Tumor burden in MMTV-PyMT animals with late-stage multi-focal disease after tumor-binding antibody therapy alone or in combination with systemic anti-PD-L1. (H) Number of palpable tumors in mice from G. All p-values reflect two-tailed, heteroskedastic t-tests in R. Error bars represent S.D.