Fc-enhanced anti-CTLA-4 depletes tumor-infiltrating regulatory T cells to augment immune effects of androgen ablation in high-risk prostate cancer

Abstract

Despite high rates of post-surgical recurrence in men with high-risk localized prostate cancer (PCa), there is currently no role for neoadjuvant therapy. Tumor infiltrating regulatory T cells (TI-Tregs) limit the antitumor effects of presurgical androgen deprivation therapy (ADT). Therefore, we designed a neoadjuvant clinical trial to test whether Treg depletion via a non-fucosylated anti-CTLA-4 antibody (BMS-986218) is feasible and augments response to ADT. In this single-center, two-arm, open-label study, 24 men with high-risk localized PCa were randomized to ADT with or without BMS-986218 prior to radical prostatectomy. Treatment was well tolerated and feasible. Mechanistic studies indicated BMS-986218 depleted TI-Tregs by engaging CD16a/FCGR3A on tumor macrophages, modulated dendritic cells (DCs), and augmented T cell priming. Depth of Treg depletion and increased DC frequencies were quantitatively associated with improved clinical outcome. Overall, this study supports the feasibility and biological activity of neoadjuvant immunotherapy with ADT + Fc-enhanced anti-CTLA-4 in high-risk localized PCa.

Keywords: CTLA-4; CyTOF; Ipilimumab; Neoadjuvant; Prostate Cancer; Regulatory T Cell; single cell RNA sequencing.

Figure 1:. NeoRED-P trial design and consort diagram.

(A) Schematic of NeoRED-P clinical trial design. (B) NeoRED-P trial consort diagram.

Figure 2:. Secondary biological and clinical endpoint measures of the NeoRED-P trial.

(A) Representative images from whole-slide immunofluorescence data for CD4 and FoxP3 with DAPI nuclear staining. Inset grey box shows a representative CD4⁺FoxP3⁺ cell at 2.5x magnification relative to the original image. Scale bar = 40μm. (B) Violin plot representing Treg frequency as measured by percent of DAPI⁺CD4⁺FoxP3⁺ Tregs of all DAPI⁺ cells in tumor regions iterated by treatment group in the immunofluorescence dataset. Untreated n=12; ADT n=7; ADT + anti-CTLA4-NF n=10. (C) Kaplan-Meier curve of PSA recurrence-free survival in patients treated with neoadjuvant ADT. (D) Kaplan-Meier curve of PSA recurrence-free survival in patients treated with neoadjuvant ADT + anti-CTLA4-NF. (E). Percent change in serum PSA from pre-treatment to time of surgery in ADT arm patients. Dotted line denotes 50% decline in PSA (PSA50). (F) Percent change in serum PSA from pre-treatment to time of surgery in ADT + anti-CTLA4-NF arm patients.

Figure 3:. Single cell multi-omic interrogation of mechanisms underlying TI-Treg depletion and clinical response to anti-CTLA4-NF.

(A) Schematic of immune correlates performed. (B) Summary of data collection and QC passing at a per-patient level for CyTOF, scRNAseq, and immunofluorescence datasets. Patients are additionally annotated according to presence or absence of PSA recurrence within 2 years post-surgery. (C) UMAP plot representing subclustering of myeloid cells in the scRNAseq dataset utilizing the PISCES pipeline. (D) Visualization of representative myeloid lineage-defining gene expression overlayed on the parent NeoRED tumor myeloid scRNAseq UMAP plot to validate cluster annotations. (E) Bubble plot validating expression of additional myeloid cluster defining genes. (F) Visualization of VIPER-inferred protein activity of select Fcγ receptors across myeloid clusters in UMAP space. (G) Violin plot of FCGR3A/CD16a inferred protein activity on a per cell level stratified by myeloid cluster. (H) Correlation between Treg frequency and average inferred protein activity of FCGR3A/CD16a across all myeloid cells on a per patient basis, stratified by treatment group. ADT n=8; ADT + anti-CTLA4-NF n=11. (I) Correlation between Treg frequency and average inferred protein activity of FCGR3A/CD16a across TREM2⁺ TAM cluster cells on a per patient basis, stratified by treatment group. Pearson correlations were utilized to evaluate statistical significance of correlations. (J) Bubble plot representing relative expression of phenotypic markers in Tregs from ADT + anti-CTLA4-NF group versus Tregs in the ADT only group, as calculated by log₂ transformed ratio of average geometric MFI of each marker on Tregs from ADT + anti-CTLA4-NF versus ADT groups. Bubble size represents relative gMFI, while color intensity represents percent expression of indicated markers across all Tregs in the dataset. Red color indicates higher relative gMFI in Tregs from patients treated with ADT + anti-CTLA4-NF, while blue color indicates higher relative gMFI in patients treated with ADT only. (K) Violin plot representing frequency of Tregs at time of surgery in the scRNAseq dataset stratified by 2-year PSA recurrence status. No recurrence n=7; recurrence n=4. Two-tailed Welch’s t-test was performed to evaluate statistical significance. (L) Kaplan-Meier curve representing time-to-PSA recurrence in ADT + anti-CTLA4-NF treated patients stratified by Treg frequency in the scRNAseq data. Log-rank test was performed to evaluate statistical significance. Unless otherwise stated, two-tailed Welch’s t test was used to assess statistical significance.

Figure 4:. Effect of ADT + Fc-enhanced anti-CTLA-4 on DCs.

(A) Violin plot of myeloid cluster frequencies as percent of myeloid cells stratified by patient 2-year PSA recurrence status. No recurrence n=7; recurrence n=4. Two-tailed student’s t-test was utilized to test statistical significance. (B) Kaplan-Meier curve representing time-to-PSA recurrence in patients stratified by dendritic cell frequency. Log-rank test was performed to evaluate statistical significance. (C) Schematic of pre-clinical validation experiment in the MycCaP model. (D) Percent change in tumor volume relative to baseline volume prior to ADT stratified by treatment group. Average values are represented by solid lines and standard deviations are represented by shaded areas. (E) Kaplan-Meier curve representing survival of mice shown in (D). Log-rank (Mantel-Cox) test was used to evaluate statistical significance. (F) Left: Supervised UMAP of live CD45⁺ cells from MycCaP tumors harvested following therapy as denoted in (D-E). Semi-supervised clustering was performed using FlowSOM and clusters were manually annotated according to expression of lineage-defining markers. Right: Heatmap of lineage-defining markers across all clusters. Data represents geometric MFI for each marker normalized to the minimum and maximum values across all clusters. (G) Frequency of TI-Tregs and (H) frequency of cDCs as percent of all live CD45⁺ cells, stratified by treatment group. (I) Left: PaCMAP representing FlowSOM-derived cDC clusters. Clusters were manually annotated according to expression of canonical marker proteins. Right: Pseudocolor representation of cDC phenotypes in PaCMAP space stratified by treatment group. (J) Violin plot representing frequency of PD-L2⁺ DCs as percent of all DCs stratified by treatment group. (K) Violin plot representing frequency of CD40⁺ DCs as percent of all DCs stratified by treatment group. Welch’s t-test was used to assess statistical significance. Murine data shown is n=8 mice per group and representative of two independent experiments each for survival and immune profiling studies.

Figure 5:. Phenotypic modulation of T cells and enhanced priming by anti-CTLA4-NF.

(A) PaCMAP plot of NeoRED-P patient tumor-infiltrating CD8 T cells by CyTOF. Clusters were derived from FlowSOM. (B) Pseudocolor density plots of CD8 T cells in PaCMAP space stratified by treatment group. (C) Expression of CD39 and 4–1BB by geometric MFI on CD8 T cells as represented by color mapping on PaCMAP plot. (D) Violin plot representing frequency of manually gated CD39⁺4–1BB⁺ CD8 T cells as a percentage of all CD8 T cells stratified by treatment group. Untreated n=7; ADT n=8; ADT + anti-CTLA4-NF n=8. Single patient with MSI^hi status called out in plot. (E) PaCMAP plot of NeoRED-P patient tumor-infiltrating CD4⁺ FoxP3⁻ Tconv cells by CyTOF. Clusters were derived from FlowSOM. (F) Pseudocolor density plots of CD4 Tconv cells in PaCMAP space stratified by treatment group. (G) Expression of CD39 and 4–1BB by geometric MFI on CD4 Tconv as represented by color mapping on PaCMAP plot. (H) Violin plot representing frequency of manually gated CD39⁺4–1BB⁺ CD4 Tconv cells as a percentage of all CD8 T cells stratified by treatment group. Untreated n=7; ADT n=8; ADT + anti-CTLA4-NF n=8. Single patient with MSI^hi status called out in plot. (I) PaCMAP plot of MycCaP-infiltrating CD8 T cells by 45-parameter flow cytometry in response to ADT, ADT + anti-CTLA4 (ND), or ADT + anti-CTLA4 (D). Clusters were derived from FlowSOM. (J) Pseudocolor density plots of CD8 T cells in PaCMAP space stratified by treatment group. (K) Expression of CD39 and 4–1BB by geometric MFI on CD8 T cells as represented by color mapping on PaCMAP plot. (L) Violin plot representing frequency of manually gated CD39⁺4–1BB⁺ CD8 T cells as a percentage of all CD8 T cells stratified by treatment group. (M) Biaxial plots representing expression of CD44 and Ki67 on CD8 T cells in tumor draining lymph nodes of mice shown in (I-L). (N) Biaxial plots representing expression of CD44 and Ki67 on CD4⁺FoxP3⁻ Tconv cells in tumor draining lymph nodes of mice shown in (L-O). (O) Violin plots representing frequencies of CD44⁺Ki67⁺ CD8 and CD4 Tconv cells as a percentage of parent populations stratified by treatment group. Two-tailed Welch’s t-test was used to assess statistical significance. All murine data shown is n=7 per group and representative of two independent experiments each for survival and immune profiling studies. (P) Schematic overview of working model based on findings from this study.