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. 2015 Feb 1;194(3):950-9.
doi: 10.4049/jimmunol.1401686. Epub 2014 Dec 24.

Combination therapy with anti-CTLA-4 and anti-PD-1 leads to distinct immunologic changes in vivo

Rituparna Das  1 , Rakesh Verma  1 , Mario Sznol  1 , Chandra Sekhar Boddupalli  1 , Scott N Gettinger  1 , Harriet Kluger  1 , Margaret Callahan  2 , Jedd D Wolchok  2 , Ruth Halaban  3 , Madhav V Dhodapkar  1 , Kavita M Dhodapkar  4
Affiliations

Combination therapy with anti-CTLA-4 and anti-PD-1 leads to distinct immunologic changes in vivo

Rituparna Das et al. J Immunol. .

Abstract

Combination therapy concurrently targeting PD-1 and CTLA-4 immune checkpoints leads to remarkable antitumor effects. Although both PD-1 and CTLA-4 dampen the T cell activation, the in vivo effects of these drugs in humans remain to be clearly defined. To better understand biologic effects of therapy, we analyzed blood/tumor tissue from 45 patients undergoing single or combination immune checkpoint blockade. We show that blockade of CTLA-4, PD-1, or combination of the two leads to distinct genomic and functional signatures in vivo in purified human T cells and monocytes. Therapy-induced changes are more prominent in T cells than in monocytes and involve largely nonoverlapping changes in coding genes, including alternatively spliced transcripts and noncoding RNAs. Pathway analysis revealed that CTLA-4 blockade induces a proliferative signature predominantly in a subset of transitional memory T cells, whereas PD-1 blockade instead leads to changes in genes implicated in cytolysis and NK cell function. Combination blockade leads to nonoverlapping changes in gene expression, including proliferation-associated and chemokine genes. These therapies also have differential effects on plasma levels of CXCL10, soluble IL-2R, and IL-1α. Importantly, PD-1 receptor occupancy following anti-PD-1 therapy may be incomplete in the tumor T cells even in the setting of complete receptor occupancy in circulating T cells. These data demonstrate that, despite shared property of checkpoint blockade, Abs against PD-1, CTLA-4 alone, or in combination have distinct immunologic effects in vivo. Improved understanding of pharmacodynamic effects of these agents in patients will support rational development of immune-based combinations against cancer.

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Figures

Figure 1
Figure 1
RNA extracted from freshly isolated monocytes and T cells from peripheral blood of patients treated with either anti-PD1 (n=6), anti-CTLA4 (n=5), combination therapy with anti-PD1 and anti-CTLA4 concurrently (Combo, n=6), and sequential anti-PD1 in patients with prior anti-CTLA4 (Seq, n=3) was analyzed using the Affymetrix HTA2.0 exon array. (A)The expression data for coding genes was analyzed using genespring 12.5platform.Coding genes were identified using the locus type filter on coding followed by manual curation of the list obtained. Differentially regulated genes were obtained by using p<0.05 and FC+/− 1.3 fold in post therapy samples compared to pre therapy samples. Changes in expression of coding genes in peripheral blood T cells and monocytes of patients treated with anti-PD1, anti-CTLA4, Combination (Combo) or Sequential (Seq) therapy. Figure shows genes differently regulated (p<0.05, fold change ≥ ±1.3) in samples obtained 3 weeks post therapy compared to baseline prior to starting therapy. The genes that were upregulated are in red and those that were downregulated are in blue. (B). Venn diagrams showing differentially regulated T cell coding genes that were shared between patients treated with anti-PD1 (αPD1), anti-CTLA4 (αCTLA4), Combination (Combo) and Sequential therapy (Seq). The figure shows that majority of the genes were unique to each specific treatment group. (C). Q-PCR was performed to confirm expression of ICOS and Ki67 as determined by microarray (n=15). Figure shows correlation between levels obtained by Q-PCR versus expression levels as determined by gene array on the same patients. (D) Expression data was analyzed to detect alternatively spliced genes using exon flow workflow of Partek GS 6.6. Exons with probe sets between 10 and 100, a p value of <0.05 at exon level and <0.00001 at the exon cluster level were included in the analysis. Figure shows alternatively spliced genes in peripheral T cells and monocytes of patients treated with anti-PD1, anti-CTLA4, Combination and Sequential therapy. Alternatively spliced genes differentially regulated at the exon level only are in blue, and genes differentially regulated at both the exon and gene level are represented in red. (E) Venn diagram showing differentially regulated alternatively spliced genes in T cells shared between patients treated with anti-PD1, anti-CTLA4 and Combination therapy. (F) Expression data was analyzed for changes in non-coding genes using Partek GS 6.6. The bar graph shows non-coding genes that are differentially regulated (p<0.05 and fold change of +/− 1.3) in peripheral blood T cells and monocytes of patients receiving therapy with checkpoint blockade inhibitors. The pie charts show the type of non- coding genes (ielinc/LncRNA, miRNA, piRNAetc) that are differentially regulated in the T cells of the patients. Miscellaneous group includes anti-sense, transfer, ribosomal and Y-RNA.
Figure 2
Figure 2
Changes in T cell proliferation and cytolytic function following therapy with checkpoint blockade inhibitors. Freshly collected frozen samples were used to for these assays. All pre and post therapy samples from the same patient were thawed at the same time, stained together using the same antibody cocktail and analyzed at the same time. (A) Bar graph shows expression of Ki67 (mean and standard error of mean) in peripheral blood (CD3, CD4 and CD8 T cells) of patients (n=34) before (Pre-white bars) and after (Post-Black bars) therapy with either anti-CTLA4 and Combo therapy (n=15) or anti-PD1 and Sequential therapy (n=19). Flow cytometry plots on the right show a representative patient with increase in Ki67+ cells after combination therapy. (B) Expression of T cell memory marker (CD45RO) in bulk T cells as well as Ki67 positive T cells after therapy in the same patient as in figure 2A. (C) Single cell mass cytometry (CyTOF) analysis for expression of surface markers on CD3+CD4+ Ki67+ as well as CD3+CD8+ Ki67+ cells before (Pre Rx) and 3 weeks after (Post Rx) starting combination therapy with anti-CTLA4 and anti-PD1. The figure shows median MFI. Plot is representative of 3 similar patients (anti-CTLA4=2 and combination treated patients n=1). (D) Expression of Granzyme B (mean and standard error of mean) in CD3 and CD8 T cells in peripheral blood of patients (n=34) before(pre) and after(post) therapy with anti-PD1 and Combo therapy (n=23) and those treated with anti-CTLA4 and Sequential therapy(n=11). The flow cytometry plot shows a representative patient.
Figure 3
Figure 3
Changes in plasma chemokine and cytokines of patients treated with checkpoint blockade inhibitors. Plasma collected before and after therapy with either anti-PD1, anti-CTLA4, combination therapy (Combo) as well as sequential therapy (Seq) was analyzed for presence of cytokines and chemokines using 39-plex luminex assay. All samples were tested in duplicate. Figure shows data for levels of cytokines and chemokines (mean and standard error of mean) that were differentially secreted. (A) sIL2Rα levels (B) IL1α levels and (C) CXCL10/IP10 levels in plasma of patients pre and post therapy.
Figure 4
Figure 4
Early effects of combination blockade on cytokine secretion by tumor infiltrating lymphocytes Tumor biopsy and peripheral blood were obtained from a patient before and 3 weeks after starting combination therapy with ipilimumab and nivolumab. Tumor infiltrating lymphocytes were either cultured alone (Alone) or with anti-CD3/CD28 beads (Anti-CD3/28). Culture supernatant obtained at 48 hours was subjected to luminex assay. Peripheral blood mononuclear cells obtained at the same time were stimulated with PMA and ionomycin and intracellular flow cytometry was performed for the detection of IFNγ. (A) Secretion of IFNγ by tumor infiltrating lymphocytes before and after therapy. (B) Secretion of IL2 by the tumor infiltrating lymphocytes. (C) Percent of IFNγ positive CD4 and CD8 T cells in the peripheral blood obtained pre and post therapy from the same patient.
Figure 5
Figure 5
PD1 expression and occupancy in patients treated with checkpoint blockade inhibitors. PD1 surface expression was determined on tumor infiltrating lymphocytes and blood from patients (n=6 different patients). Cells were obtained from the tumor sample by manual dissociation. PBMCs obtained from the blood and the tumor tissue were stained and analyzed together. (A) Graph in the left panel shows expression of PD1 on CD4 and CD8 T cells in the tumor as well as peripheral blood T cells drawn at the same time. Panel on the right is a representative flow cytometry plot showing controls (Fluorensence minus one; FMO and Isotype) as well as PD1 staining on CD8 T cells. (B) Expression of PD1 on CD3, CD4 and CD8 T cells in peripheral blood of representative patients before and after treatment with anti-PD1 and anti-CTLA4. (C). Bar graph shows percent PD1 on CD4 and CD8 T cells that was unoccupied after therapy with anti-PD1 compared to that prior to therapy in 2 separate patients. Bar in white shows data from peripheral blood T cells and bar in black shows data from tumor infiltrating T cells. (D) Expression of PD1 on peripheral blood and tumor infiltrating T cells in a patient before and after combination therapy with anti-CTLA4 and anti-PD1 therapy. Data are representative of similar findings on two patients.
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