Chou, Justin

Abstract Background: Conventional prognostic factors for LBCL were not associated with outcomes in the pivotal ZUMA-1 study of axi-cel in relapsed LBCL (Neelapu et al. NEJM. 2017); however, other attributes like chimeric antigen receptor (CAR) T-cell fitness and composition (CCR7+CD45RA+ T cells), reduced preTx tumor burden, and immune tumor microenvironment (TME) with presence of activated CD8+PD-1+LAG-3+/-TIM-3- T cells were associated with efficacy (Locke et al. Blood Adv. 2020; Galon et al. ASCO 2020. #3022). Here, we evaluated preTx immune cell phenotypes in premanufacturing apheresis (premfg aph) material, comprising peripheral blood mononuclear cells, to determine associations with product attributes, immune TME features, and clinical efficacy in ZUMA-1. Methods: Evaluable samples from patients (pts) in Phase (Ph) 1 and Ph2 Cohorts (C) 1-3 were analyzed (NCT02348216; Ph1 and Ph2 C1+2, ≥2-y follow-up; C3, ≥6-mo follow-up). Memory T, myeloid, NK, NKT, and B cells in premfg aph material (n=101, excluding C3) were characterized by flow cytometry (FC). PreTx immune TME was analyzed by multiplex IHC (n=18) and gene expression analysis (n=30) as previously described (Rossi et al. AACR 2018. #LB-016; Galon et al. ASCO 2020. #3022). CAR T-cell fitness was analyzed by doubling time, viability during manufacturing, and product T-cell phenotypes by FC (n=145). Associations between these covariates, and with routine hematology tests, were performed by Spearman rank correlation or Wilcoxon tests. Effects on survival were assessed by Kaplan-Meier with optimized cutpoint selection. Results: The percentage (%) of naive (CCR7+CD45RA+) T helper (Th; CD4+CD127+CD25low) cells coexpressing CD27 and CD28 (median, 1%; range, 0.01%-15.8%; IQR, 0.3%-3.8%) in aph associated positively with axi-cel efficacy. The % of intermediate monocytes (IMs; CD14+CD16+; median, 1.8%; range, 0.003%-16.7%; IQR, 1%-3%) in aph associated negatively with efficacy. The % of circulating CD27+CD28+ naive Th cells associated positively with an enriched preTx immune TME T-cell signature, % CCR7+CD45RA+ product T cells, objective response rate, PFS, and OS. An increased % of IMs associated directly with negative predictive markers (preTx serum levels of LDH, IL-6, and CRP) and inversely with TME T-cell signature, PFS, and OS. The premfg ratio of CD27+CD28+ naive Th cells/IMs associated directly with CAR T-cell expansion and efficacy. Conclusions: This work points to a link between the pre-existing state of the immune system, reflected in premfg aph, and immune TME, as well as product attributes influencing axi-cel efficacy in LBCL. These data bear practical implications towards the development of predictive biomarkers for axi-cel efficacy. [JB and JC contributed equally.] Citation Format: Justin Budka, Justin Chou, Vicki Plaks, Francesca Milletti, Zixing Wang, Frederick L. Locke, Sattva S. Neelapu, David B. Miklos, Caron A. Jacobson, Lazaros J. Lekakis, Yi Lin, Armin Ghobadi, Zahid Bashir, Nathalie Scholler, Jérôme Galon, John M. Rossi, Adrian Bot. Pretreatment (PreTx) immune cell phenotypes in peripheral blood associated with the tumor immune contexture, product attributes, and durable clinical efficacy in patients with large B-cell lymphoma (LBCL) treated with axicabtagene ciloleucel (axi-cel) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr CT166.

3022 Background: Axi-cel is a US and EU-approved autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy for pts with relapsed/refractory large B cell lymphoma after ≥ 2 prior therapies. In ZUMA-1 (NCT02348216), the objective response rate was 83% (58% complete response rate; Locke et al. Lancet Oncol. 2019). T cell-related biology (Immunosign 21; Immunoscore) measured pretreatment in the tumor microenvironment (TME) was associated with response to axi-cel (Rossi et al. AACR 2018. #LB-016; Rossi et al. AACR 2019. #CT153). This expanded analysis characterized the pretreatment TME immune contexture and examined associations between immune cell subsets and response. Methods: In ZUMA-1, pts received axi-cel at a target dose of 2.0 × 106 CAR T cells/kg. Archival pretreatment tumor biopsy samples were analyzed by multiplex immunohistochemistry (Brightplex). Two panels were developed and applied to assess T cell (CD3, CD8, FoxP3, PD-1, LAG-3, TIM-3) and myeloid cell (CD11b, CD14, CD15, LOX1, S100A9, CD68) subsets (n = 14 total). The association between T cell and myeloid cell subset density, prespecified immune scores (Immunosign 21; Immunoscore), and objective response was evaluated. T test values were based on Brightplex analysis. Results: Pretreatment tumor biopsy samples from 18 pts were analyzed (14 objective responders and 4 nonresponders). The pretreatment TME comprised all major myeloid and T cell subsets, with diverse distribution across samples analyzed. The median TME density of monocytes (CD11b+ CD15− CD14+; 1215 cells/mm2) and macrophages (CD68+; 530 cells/mm2) was greater than that of the total CD8+ T cell subset (312 cells/mm2). The pretreatment Immunosign 21 and Immunoscore scores associated positively with the density of all major T cell subsets and some myeloid subsets. The density of activated CD8+ T cells (PD-1+ LAG-3+/− TIM-3−) was most significantly associated with clinical response versus other T cell subsets. The density of nonactivated CD8+ T cells (PD-1− LAG-3− TIM-3−) and exhausted CD8+ T cells (PD-1+ LAG-3+ TIM-3+) were not significantly associated with response. Additional characterization of the immune contexture and correlative analysis of cell subsets will be presented. Conclusions: These results suggest that a TME associated with increased density of activated PD-1+ LAG-3+/− TIM-3− CD8+ T cells, measurable pretreatment, facilitates clinical response in pts post–axi-cel.