Pan-cancer single cell transcriptomic clustering reveals heterogeneous CD8+ exhausted T cell populations with different immune checkpoint inhibitor responses.

Abstract

In most cancers, T lymphocytes comprise an essential cellular component of the non-neoplastic microenvironment, where they have the capacity to both suppress and support tumor growth. One specialized T lymphocyte population is the CD8⁺ exhausted T cell, which has been intensely studied as an actionable therapeutic target. Unfortunately, there is currently no uniformly accepted classification scheme for these specialized T cells. To provide a potential model for classifying CD8⁺ exhausted T cells, we leveraged single cell transcriptomic analysis of a diverse collection of both human (n = 8) and mouse (n = 4) cancers to identify unique subpopulations shared across tumor types and species. By integrating data from both human and mouse cancer studies, as well as previously described CD8⁺ exhausted T cell subsets, we provide an integrated framework to characterize the heterogeneity of exhausted CD8⁺ T cells. As such, one of these subpopulations (cluster C1) increases following immune checkpoint inhibitor treatment in the setting of cancer in mice and patients. Taken together, this proposed classification scheme may be useful for the design and interpretation of current and future immune-based therapy studies.