Abstract LB-218: High-dimensional modeling of single-cell-based CD8+ T cell exhaustion predicts response to immune checkpoint blockade
Authors: Jin Guangxu , Xue Gang , Wang Rui-Sheng , Wu Ling-Yun , Miller Lance , Lu Yong , Zhang Wei 
Published: August 2019

INTRODUCTION Accurate prediction of response to existing immune checkpoint blockade (ICB) and development of more efficacious ICB strategies are needed for cancer immunotherapy. The single-cell-level characterization of tumor-infiltrating CD8+ T lymphocytes (TILs) has presented new opportunities. However, the phenotypic variability of TILs, including tumor-specificity and CD8+ TIL exhaustion that regulate response to ICB, is poorly understood. Computationally modeling a large number of CD8+ TILs with high-dimensional T cell functional markers can link high-dimensional single-cell data with fundemental T cell functionalities.

METHODS Here we develop a computational method (called HD-scMed) to predict response to ICB at the single-cell level. Our high-dimensional single-cell method, HD-scMed, models the phenotypic variability of CD8+ TILs directly within the original high-dimensional expression space, defined by k-dimensional exhaustion markers and other T cell functional markers. Within the high-dimensional expression space, HD-scMed identifies Pareto-optimal Frontier (PF) TILs representing a subset of exhausted TILs, by a mathematical model, Pareto Optimization. A quantitative criterion, D-value, defined as the Euclidean distance from PF TILs to the baseline TILs excluded by the PF, is used to indicate the extent to which the PF TILs are exhausted.

RESULTS D-value accurately predicts clinical response to the ICB, i.e., αPD-1, αCTLA-4, and αPD-1+αCTLA-4, with performance of AUC=100% by single-cell flow cytometry (CyTOF) data with 101,401 CD8+ TILs from human tumors after ICBs, and AUC=95% and 86% by single-cell RNA-seq (scRNA-seq) data including 9,405 CD8+ TILs from human tumors before and after ICBs, respectively. Mechanistically, “D-high” TILs are associated with high tumor-specificity, enhanced exhaustion, and inactivated effector and cytotoxic signatures in non-responders; whereas “D-low” TILs are enriched in responders demonstrating tumor-specific T cells with T cell activation and cytolytic effector T cell signatures. We also observed “D negative” bystander T cells irrelevant to response. Notably, LAG3 shows significantly higher contribution to TIL D values in non-responders than responders. To reverse the functionality of the LAG3-high TILs after receiving αPD-1+αCTLA-4, we tested the effects of αLAG3 with αPD-1+αCTLA-4 in murine tumor models. Remarkably, the combination, αLAG3+αPD-1+αCTLA-4, showed extraordinary antitumor efficacy in eradicating advanced tumors, which was associated with burst GZMBhi TIL populations; whereas αPD-1+αCTLA-4 or αPD-1+αCTLA-4 plus other ICBs as control showed only moderate inhibition of tumor growth.

CONCLUSION Our study has important implications for cancer immunotherapy regarding both accurate prediction of ICB response and development of better strategies to reverse existing ICB resistance.

Citation Format: Guangxu Jin, Gang Xue, Rui-Sheng Wang, Ling-Yun Wu, Lance Miller, Yong Lu, Wei Zhang. High-dimensional modeling of single-cell-based CD8+ T cell exhaustion predicts response to immune checkpoint blockade [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-218.