Single-Cell Analyses Reveal a Functionally Heterogeneous Exhausted CD8+ T-cell Subpopulation That Is Correlated with Response to Checkpoint Therapy in Melanoma

Abstract PD-1 pathway inhibitors have revolutionized cancer therapy. However, most patients do not durably benefit, highlighting the need for biomarkers to stratify patients as responders or nonresponders. Although CD8+ tumor-infiltrating lymphocytes (TIL) have been associated with immune checkpoint therapy response, there is no consensus on which CD8+ TIL subpopulations have the most prognostic value. Preclinical studies have focused on progenitor-like exhausted CD8+ T cells (TPEX) because TPEX proliferate more in response to PD-1 inhibitors than other exhausted T-cell (TEX) subpopulations. However, immune checkpoint inhibitor treatment drives TPEX differentiation into other TEX populations that can mediate antitumor immunity. These data complicate the ability to identify prognostically important T-cell populations in patients that predict immune checkpoint inhibitor treatment response. In this study, we found that patients with advanced melanoma with ≥20% of CD8+ TILs coexpressing PD-1 and CTLA4 (termed CPHi TIL) had better objective response rates and survival following PD-1 monotherapy than those below this threshold. Characterization of the CPHi TIL subset using bulk and single-cell RNA sequencing showed that although TPEX-like cells were present within the CPHi subset, they were in the minority of these cells. Rather, the CPHi population was numerically dominated by other subsets, including cycling, terminally exhausted–like, cytotoxic-like, and/or resident memory-like TEX populations, and a subset enriched for glycolytic genes. Collectively, these data show that CPHi TILs correlate with response in melanoma, but this TIL subset is a heterogeneous mix of different subpopulations that may differentially contribute to antitumor immunity following checkpoint blockade. Significance: The PD-1+ CTLA4+ CD8+ tumor-infiltrating lymphocyte population correlating with immunotherapy response is a heterogeneous mix of subpopulations, which has important implications for optimizing checkpoint-based immunotherapy.