Differential effects of PD-L1 versus PD-1 blockade on myeloid inflammation in human cancer
Noffar Bar, Federica Costa, Rituparna Das, Alyssa Duffy, Mehmet Samur, Samuel McCachren, Scott N. Gettinger, Natalia Neparidze, Terri L. Parker, Jithendra Kini Bailur, Katherine Pendleton, Richa Bajpai, Lin Zhang, Mina L. Xu, Tara Anderson, Nicola Giuliani, Ajay Nooka, Hearn J. Cho, Aparna Raval, Mala Shanmugam, Kavita M. Dhodapkar, Madhav V. Dhodapkar
Noffar Bar, Federica Costa, Rituparna Das, Alyssa Duffy, Mehmet Samur, Samuel McCachren, Scott N. Gettinger, Natalia Neparidze, Terri L. Parker, Jithendra Kini Bailur, Katherine Pendleton, Richa Bajpai, Lin Zhang, Mina L. Xu, Tara Anderson, Nicola Giuliani, Ajay Nooka, Hearn J. Cho, Aparna Raval, Mala Shanmugam, Kavita M. Dhodapkar, Madhav V. Dhodapkar
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Clinical Research and Public Health Hematology Immunology

Differential effects of PD-L1 versus PD-1 blockade on myeloid inflammation in human cancer

Abstract

BACKGROUND PD-1 and PD-L1 have been studied interchangeably in the clinic as checkpoints to reinvigorate T cells in diverse tumor types. Data for biologic effects of checkpoint blockade in human premalignancy are limited.METHODS We analyzed the immunologic effects of PD-L1 blockade in a clinical trial of atezolizumab in patients with asymptomatic multiple myeloma (AMM), a precursor to clinical malignancy. Genomic signatures of PD-L1 blockade in purified monocytes and T cells in vivo were also compared with those following PD-1 blockade in lung cancer patients. Effects of PD-L1 blockade on monocyte-derived DCs were analyzed to better understand its effects on myeloid antigen-presenting cells.RESULTS In contrast to anti–PD-1 therapy, anti–PD-L1 therapy led to a distinct inflammatory signature in CD14+ monocytes and increase in myeloid-derived cytokines (e.g., IL-18) in vivo. Treatment of AMM patients with atezolizumab led to rapid activation and expansion of circulating myeloid cells, which persisted in the BM. Blockade of PD-L1 on purified monocyte-derived DCs led to rapid inflammasome activation and synergized with CD40L-driven DC maturation, leading to greater antigen-specific T cell expansion.CONCLUSION These data show that PD-L1 blockade leads to distinct systemic immunologic effects compared with PD-1 blockade in vivo in humans, particularly manifest as rapid myeloid activation. These findings also suggest an additional role for PD-L1 as a checkpoint for regulating inflammatory phenotype of myeloid cells and antigen presentation in DCs, which may be harnessed to improve PD-L1–based combination therapies.TRIAL REGISTRATION NCT02784483.FUNDING This work is supported, in part, by funds from NIH/NCI (NCI CA197603, CA238471, and CA208328).

Authors

Noffar Bar, Federica Costa, Rituparna Das, Alyssa Duffy, Mehmet Samur, Samuel McCachren, Scott N. Gettinger, Natalia Neparidze, Terri L. Parker, Jithendra Kini Bailur, Katherine Pendleton, Richa Bajpai, Lin Zhang, Mina L. Xu, Tara Anderson, Nicola Giuliani, Ajay Nooka, Hearn J. Cho, Aparna Raval, Mala Shanmugam, Kavita M. Dhodapkar, Madhav V. Dhodapkar

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Figure 2

PD-L1 blockade leads to distinct transcriptomic changes in circulating monocytes and T cells.

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PD-L1 blockade leads to distinct transcriptomic changes in circulating m...
RNA was extracted from magnetic bead isolated CD14+ monocytes and CD3+ T cells from patients with lung cancer before and after therapy with either anti–PD-L1 (atezolizumab; n = 5) or anti–PD-1 (nivolumab; n = 6 previously published; ref. 10) and analyzed using affymetrix human transcriptome array 2.0. (A) Distribution of differentially regulated genes upregulated and downregulated in monocytes and T cells following therapy with anti–PD-L1 or anti–PD-1. (B) Differentially regulated genes in monocytes following therapy with anti–PD-L1 (selected from top 50 differentially regulated genes). (C) Single cell RNA sequencing was performed before and after therapy with either anti–PD-L1 (n = 3) or anti–PD-1 (n = 4). Figure shows the number of shared differentially expressed (Wilcoxon rank-sum with Bonferroni’s correction, P < 0.05) genes after versus before treatment between all anti–PD-L1 treated monocytes and all anti–PD-1–treated monocytes. (D) Uniform manifold approximation and projection (UMAP) plots of monocytes from single cell RNA sequencing of anti–PD-L1 monocytes before and after treatment (left panel: blue, after treatment; red, before treatment) and monocyte groups identified by unsupervised clustering (right panel). Cluster 1 represents CD16+ monocytes; clusters 2, 3, and 4 represent CD16– monocytes.