Abstract

Abstract Background: Expression of PD-L1 on tumor and immune markers in tumor tissue is associated with improved response to PD-1 and PD-L1 checkpoint inhibitors. However, each alone has limited predictive utility. Multimodal characterization of both the tumor and host immune system is an unmet medical need for the improved prediction of response to immunotherapy. Metastatic lesions are likely to be undersampled and require a liquid biopsy, given tumor heterogeneity and evolution and temporal changes in the host immune system. We sought to examine expression of PD-L1 on circulating tumor cells (CTCs) as well as characterize rare immune cell populations with a noninvasive liquid biopsy. Examining dynamic biomarker changes in longitudinal samples could enable the development of novel diagnostic tools for response prediction and pharmacodynamics studies related to immunotherapy. Methods: Blood samples from lung cancer patients were collected and shipped to Epic Sciences. Contrived samples were also developed, using cancer cell lines spiked into healthy donor (HD) blood. Red blood cells were lysed and nucleated cells were plated onto glass slides. Slides were stained with DAPI and immune cocktails, then imaged. Targets included pan-CK, CD45, PD-L1, CD4, CD8, Ki-67, and TIM-3. Approximately 3 million nucleated cells per slide were examined through advanced digital pathology pipelines to detect and quantify changes in T-cell populations and to assess circulating tumor burden. Results: Epic Sciences' rare cell detection platform has an analytically validated limit of detection of 2 cells/mL of blood. Immuno-panels were developed to profile leukocyte subpopulations and CTCs from a single blood sample and feasibility was demonstrated in cell lines, HD and lung disease patient blood. Quantitation experiments showed that immunomagnetically purified CD8+ and CD4+ cells spiked in 3:1, 1:1, and 1:3 ratios were detected as 3.1:1, 1:1.1, and 1:3.1. Purified CD4 cells were also spiked into healthy donor WBCs at target ratios of 1-10%. Percentages of detected spike-in CD4 cells were linearly correlated with the target ratios with correlation coefficient (r) = 0.96. 22.8% (18/79) lung cancer patients had PD-L1+ CTCs detected, and the majority (91%) of patients had PD-L1+ leukocyte populations. Conclusions: The low limit of detection of the Epic Sciences CTC platform coupled with the ability to archive patient blood samples allowed for retrospective, precise quantification of leukocyte subpopulations and PD-L1 expression on CTCs. Development of a liquid biopsy-based platform that can simultaneously measure immune biomarkers in CTCs as well as on leukocytes will allow for real-time assessment and monitoring of response to immune checkpoint inhibitors. Citation Format: Rachel Krupa, David Lu, Adam Jendrisak, Angel Rodriguez, Nadia Ebrahim, Robin Richardson, Sean Nisperos, Ryon Graf, Jiyun Byun, Yipeng Wang, Mark Landers, Ryan Dittamore. Simultaneous characterization and quantification of immune cell subpopulations and PD-L1 expressing CTCs in peripheral blood of cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5536.

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