Single-Cell Analyses Reveal a Functionally Heterogeneous Exhausted CD8+ T-cell Subpopulation That Is Correlated with...

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.