Distinct cellular mechanisms mediate anti-CTLA-4 and anti-PD-1 checkpoint blockade
Spencer C. Wei1, Jacob Levine2, Dana Pe’er2 and James P. Allison1
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
Checkpoint blockade is able to achieve durable responses in a subset of patients, however we lack a satisfying comprehension of the underlying mechanisms of anti-CTLA-4 and anti-PD-1 induced tumor rejection. To address this issue we utilized mass cytometry to comprehensively profile the effect of checkpoint blockade on tumor immune infiltrates in murine tumor models. We demonstrate that high dimensional mass cytometry analysis enables unsupervised identification of biologically relevant tumor infiltrating immune populations with high sensitivity and specificity.
Using this approach we analyzed MC38 and B16BL6 murine tumors in mice treated with anti-CTLA-4, anti-PD-1, or control antibodies. In both tumor models we identify 15 distinct T cell populations with 0.5% or greater frequency. Notably, some but not all of these T cell populations were responsive to checkpoint blockade. A subset of tumor infiltrating CD8 T cell populations expanded while a subset of regulatory T cell populations contracted following both anti-CTLA-4 and anti-PD-1. Interestingly, we observed an expansion of a Th1-like CD4 effector T cell population only in response to anti-CTLA-4 treatment. Thus, we find that anti-PD-1 predominantly engages subsets of tumor infiltrating CD8 T cells whereas anti-CTLA-4 engages both the CD4 and CD8 effector compartments.
Our findings indicate that anti-CTLA-4 and anti-PD-1 utilize distinct cellular mechanisms to induce tumor rejection. These findings have implications for the rational design of combinatorial therapeutic approaches. Furthermore, these results demonstrate that mass cytometry analysis can be utilized to identify biologically relevant tumor infiltrating immune populations.
We acknowledge the MDACC core facility NCI Support Grant P30CA16672.