Single-cell spatial landscape of immunotherapy response reveals mechanisms of CXCL13 enhanced antitumor immunity

Abstract

Background: Immunotherapy has revolutionized clinical outcomes for patients suffering from lung cancer, yet relatively few patients sustain long-term durable responses. Recent studies have demonstrated that the tumor immune microenvironment fosters tumorous heterogeneity and mediates both disease progression and response to immune checkpoint inhibitors (ICI). As such, there is an unmet need to elucidate the spatially defined single-cell landscape of the lung cancer microenvironment to understand the mechanisms of disease progression and identify biomarkers of response to ICI.

Methods: Here, in this study, we applied imaging mass cytometry to characterize the tumor and immunological landscape of immunotherapy response in non-small cell lung cancer by describing activated cell states, cellular interactions and neighborhoods associated with improved efficacy. We functionally validated our findings using preclinical mouse models of cancer treated with anti-programmed cell death protein-1 (PD-1) immune checkpoint blockade.

Results: We resolved 114,524 single cells in 27 patients treated with ICI, enabling spatial resolution of immune lineages and activation states with distinct clinical outcomes. We demonstrated that CXCL13 expression is associated with ICI efficacy in patients, and that recombinant CXCL13 potentiates anti-PD-1 response in vivo in association with increased antigen experienced T cell subsets and reduced CCR2+ monocytes.

Discussion: Our results provide a high-resolution molecular resource and illustrate the importance of major immune lineages as well as their functional substates in understanding the role of the tumor immune microenvironment in response to ICIs.

Keywords: Cytokines; Immunotherapy; Lung Neoplasms.

Figure 1

Single cell spatial landscape of response to ICI in NSCLC. (A) Schematic of IMC acquisition of multiplexed images from 27 patients with NSCLC, involving laser ablation of metal-conjugated antibodies, CyTOF acquisition, single-cell phenotyping and characterization of the prevalence and interactions of immune cells. (B) Cell assignment hierarchy. (C) Representative images of antibody staining and corresponding single-cell segmented images for responders and non-responders. (D) Average expression of markers in indicated cell populations. (E) Kaplan-Meier overall survival analysis for 11 patients with NSCLC treated with ICI (responders n=6, non-responders n=5). (F) Frequency of cancer and immune cell populations in responders and non-responders to immune checkpoint inhibitors as a proportion of total cells. Non-Cl Mo - responders versus non-responders: *p=0.017316. (G) Ratio of average marker intensity in cancer and immune cell populations. Green represents higher intensity in responders, gray in non-responders and white was not calculated. Median±IQR. Statistical analysis (E: log-rank test, F: Mann-Whitney test). Cl Mo, classical monocyte; CyTOF, cytometry by time of flight; DC, dendritic cell; ICI, immune checkpoint inhibitor; IMC, imaging mass cytometry; Int Mo, intermediate monocyte; M1-like MAC, M1-like macrophage; M2-like MAC, M2-like macrophage; NK cell, natural killer cell; Non-Cl Mo, non-classical monocyte; NSCLC, non-small cell lung cancer; Tc, cytotoxic T cell; Th, helper T cell; TMA, tissue microarray; Treg, regulatory T cell.

Figure 2

Cell–cell communication and spatial neighborhoods associated with response to ICI in NSCLC. (A) Prevalence of CXCL13+ T cells, CXCL13+ Th and CXCL13+ Tc across non-responders and responders as a proportion of T cells. CXCL13+ T cells – non-responders versus responders: *p=0.021645. CXCL13+ Th non-responders versus responders: *p=0.021645. (B) Pie chart indicating the relative proportion of cell types expressing CXCL13 (n=11). (C) Heatmap indicating significant pairwise cell-type interaction (red) or avoidance (blue) summarized across the two-sided permutation tests on individual images (n=11 images; 1000 permutations each). (D) Heatmap of seven cellular neighborhoods discovered in 11 patients with NSCLC. (E) Number of cells per cellular neighborhood in non-responders and responders to ICI (CN2 – non-responders vs responders *p=0.0303). Median±IQR. Statistical analysis (A, E: Mann-Whitney test). Cl Mo, classical monocyte; ICI, immune checkpoint inhibitor; Int Mo, intermediate monocyte; M1-like MAC, M1-like macrophage; M2-like MAC, M2-like macrophage; NK cell, natural killer cell; NSCLC, non-small cell lung cancer; Tc, cytotoxic T cell; Th, helper T cell; Treg, regulatory T cell.

Figure 3

Recombinant CXCL13 (rCXCL13) potentiates anti-PD-1 efficacy. (A) Schematic of experimental setup. C57BL/6 male mice were inoculated with 500,000 HKP1, 300,000 MC38 or 500,000 LLC1 cells into the flank. Representative CD8 IHC and H&E of (B) HKP1, (D) MC38, and (F) LLC1 treatment-naive tumors. Tumor growth curves of C57BL/6 wildtype mice inoculated with (C) HKP1, (E) MC38, or (G) LLC1 tumors with indicated treatments. Tumor sizes are shown as mean±SEM. HKP1 - rCXCL13+anti-PD1 versus PBS+anti-PD-1: ****p<0.0001, PBS+anti-PD1 versus PBS+IgG: **p=0.0067. MC38 - rCXCL13+anti-PD1 versus PBS+anti-PD-1: ***p=0.0001. Statistical analysis (C, E, G: two-way analysis of variance with Tukey multiple comparisons test). Scale bar on the H&E and IHC represents 100 µm. CRC, colorectal cancer; ICI, immune checkpoint inhibitor; IHC, immunohistochemistry; NK cell, natural killer cell; NSCLC, non-small cell lung cancer; PBS, phosphate-buffered saline; PD-1, programmed cell death protein-1; rCXCL13, recombinant CXCL13; Tc, cytotoxic T cell; Treg, regulatory T cell.

Figure 4

The rCXCL13 and anti-PD-1 lead to recruitment of antigen-experienced T cells. Uniform Manifold Approximation and Projection (UMAP) of total CD45+ cells from combining all treatment groups in (A) HKP1, (B) MC38 or (C) LLC1 models. (D) Average frequency of CCR2⁻ monocytes in IgG+ PBS control tumors. Average frequency of CCR2⁻ monocytes in (E) HKP1, (F) MC38, (G) LLC1. UMAP plot of all T cells highlighting antigen-experienced CD4+ and CD8+ T-cell abundance in (H) HKP1, (J) MC38 or (L) LLC1 models with indicated treatments. Average frequency of dendritic cells in (I) HKP1 or CD8+ T cells in (K) MC38 and (J) LLC1 models. Mean±SEM. Statistical analysis (D–M: one-way analysis of variance with Tukey multiple comparisons test). PBS, phosphate-buffered saline; PD-1, programmed cell death protein-1; rCXCL13, recombinant CXCL13; Tregs, regulatory T cells.