Description

Dissecting Mechanisms of anti-PD-1 Therapy with Massively Parallel Single-Cell RNA-Sequencing

Brian C Miller^1,2,3, Marc H Wadsworth 2nd^3,4, Kevin Bi^1,3, Travis K Hughes^2,3,4, Robert Manguso^1,2,3, Arlene H Sharpe^2,3, Alex K Shalek^2,3,4, W Nicholas Haining^{1,2,3 *}

¹Dana-Farber Cancer Institute, Boston, MA. ²Harvard Medical School, Boston, MA. ³Broad Institute of MIT and Harvard, Cambridge, MA. ⁴Massachusetts Institute of Technology, Cambridge, MA.

*corresponding author

Anti-PD-1 therapy is an important new treatment option for many malignancies, but overall response rates are less than 40%. Limited understanding of how anti-PD-1 treatment changes the tumor immune microenvironment is a barrier to identifying rational combination therapies and understanding mechanisms of immunotherapy resistance. To overcome this barrier, we set out to understand the mechanisms by which anti-PD-1 therapy augments the anti-tumor immune response using single-cell genomics. We have developed a novel massively parallel single-cell RNA-sequencing platform (“Seq-Well”) and have used it to define the global expression profile of all major immune lineages in the tumor microenvironment in a mouse model of immunotherapy. In a single experiment we were able to sequence the transcriptomes of over 600 cells, allowing us to clearly distinguish different immune lineages within the tumor microenvironment. We detect two transcriptionally distinct populations of CD8⁺ T cells, one that is highly proliferative (as marked by Ki-67), and one that has higher expression of cytotoxic markers (i.e. perforin). The Ki-67^hi population is enriched for a gene expression signature from terminally exhausted CD8⁺ T cells, suggesting that this is a more exhausted subset. Treatment with anti-PD-1 globally alters the tumor microenvironment, including enriching for CD8⁺ T cells in the Prf^hi subpopulation compared with the Ki-67^hi more terminally exhausted population. Studies to understand changes in the immune infiltrate of immunotherapy resistant tumors are currently ongoing. In conclusion, massively parallel single-cell RNA-seq allows us to dissect the mechanisms by which checkpoint blockade controls tumor growth.