Cellular Mechanisms of Combination Checkpoint Blockade

Identification: Wei, Spencer
Publication Date: March 30, 2018
Expiration Date: April 23, 2019


Description

Cellular Mechanisms of Combination Checkpoint Blockade
 
Spencer C. Wei1, Roshan Sharma2, Nana-Ama A.S. Anang1, Jacob H. Levine2, Alexandre Reuben3, Alexandria P. Cogdill1, 3, Miles C. Andrews3, Jennifer A. Wargo3, Dana Pe'er2, and James P. Allison1, 4
1Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 2Computational and Systems Biology Program, Sloan Kettering Institute, New York, NY, USA; 3Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 4Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
 
Immune checkpoint blockade is able to achieve durable responses in a subset of patients. However, we still lack a satisfying comprehension of the underlying mechanisms. In particular, it remains unclear whether combination therapies utilize similar cellular and molecular mechanisms as constituent monotherapies. Distinguishing between these possibilities is important for understanding of how to rationally design combination approaches and what information is needed to guide this process. We hypothesize that combination anti-CTLA-4 plus anti-PD-1 therapy engages distinct cellular mechanisms to induce tumor rejection compared to monotherapies. To address this hypothesis, we utilized mass cytometry to comprehensively profile effects on T cell populations following combination anti-CTLA-4 plus anti-PD-1 checkpoint blockade therapy in preclinical murine tumor models and clinical samples. Mass cytometry enables characterization of more than 40 protein parameters at single cell resolution and robust unsupervised cellular classification.
 
Using this approach, we identify 14 MC38 tumor infiltrating T cell populations. Similar to previous findings utilizing comparable technical approaches, we observe that anti-CTLA-4 and anti-PD-1 monotherapies have distinct effects on tumor infiltrating T cell populations. Anti-PD-1 predominantly leads to expansion of phenotypically exhausted tumor infiltrating CD8 T cells whereas anti-CTLA-4 leads to expansion of CD8 subsets as well as a Th1-like CD4 effector population. Combination therapy enhanced the effects of monotherapies, however also notably led to distinct effects on multiple T cell populations. In particular, combination therapy differentially modulated phenotypically exhausted CD8 T cell populations compared to monotherapies. We also performed mass cytometry based profiling of peripheral blood from melanoma patients treated with checkpoint blockade therapies. These analyses identified 15 T cell populations present in peripheral blood and further support the differential engagement of specific cell populations by combination anti-CTLA-4 plus anti-PD-1 therapy. These findings indicate that combination therapy, at least in the context of anti-CTLA-4 and anti-PD-1, leads to distinct cellular effects compared to monotherapies, and suggest that combination therapy differentially modulates T cell function.

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