31 Dynamic change of PD-L1 expression on extracellular vesicles predicts response to immune-checkpoint inhibitors in non-small cell lung cancer patients

Background Immune-checkpoint inhibitors (ICIs) have revolutionized the treatment of advanced/metastatic non-small cell lung cancer patients (NSCLC), however, only a small subset of patients derives clinical benefit.1–3 To date, PD-L1 immunohistochemical evaluation is the gold-standard assay and the only approved biomarker, but associated with several limitations due to technical and biological factors such as spatial and temporal tumor heterogeneity.4 5 In this context, liquid biopsies emerge as novel powerful tools that could allow the non-invasive real-time characterization of the tumor PD-L1 status. In particular, extracellular vesicles (EVs), defined as cell-derived double-membrane structures involved in cell communication, hold strong potential as tissue surrogates. Recent studies have suggested that EV PD-L1 could stratify melanoma patients receiving ICIs, but none has showed the predictive value of this biomarker in NSCLC patients.6 7 We hypothesize that EV PD-L1 cargo can serve to stratify the response to ICIs in NSCLC patients. Methods This study enrolled advanced/metastatic NSCLC patients receiving ICI treatment. Plasma samples were obtained at baseline (T1) and at 8 weeks (T2) during the first response evaluation. Patients were classified as responders when showing partial, stable or complete response or as non-responders when manifesting progressive disease following RECIST v1.1.8 Plasma EVs were isolated by standard serial ultracentrifugation methods and characterized according to ISEV recommendations.9 10 Tissue PD-L1 expression was measured by immunohistochemistry while EV PD-L1 expression was measured by immunoblot. A predictive model was created by logistic-regression and a bootstrap corrected ROC curve to validate the results. Results Paired plasma samples from 21 patients were analyzed. PD-L1 tissue expression was not correlated with treatment response (p=0.394) nor matched the baseline EV PD-L1 levels (p=0.337) (figure 1.A). However, the dynamics of EV PD-L1 (T1-T2) correlated with the treatment response, observing an increase of PD-L1 expression in non-responders and a decrease or stable levels in responders (p=0.043) (figure 1.B). The predictive model reported an AUC=0.85, 90% CI=0.72–0.97, with 74.2% sensitivity and 73.5% specificity (figure 1.C). Moreover, the increase of EV PD-L1 was associated with shorter overall survival (HR=4.34, p=0.037) and shorter progression-free survival (HR=5.06, p=0.025) (figure 1 D & E). Conclusions Our preliminary-study showed, for the first time, the predictive and prognostic value of EV PD-L1 dynamic changes in immunotherapy-treated NSCLC patients. Although larger studies are needed to validate these results, this promising biomarker could have important clinical implications, guiding treatment decisions in near real-time and improving the outcome of patients that could benefit from ICIs. Acknowledgements We would like to extend our gratitude to the all the patients that participated in the study. Ethics Approval All patients consented to an Institutional Review Board–approved protocol (A.O. Papardo, Messina, Italy). Biological material was transfer to the University of Maryland, USA under signed MTA between both institutions (MTA/2020-13111). References Rittmeyer A, Barlesi F, Waterkamp D, et al. Atezolizumab versus docetaxel in patients with previously treated non-small-cell lung cancer (OAK): a phase 3, open-label, multicentre randomised controlled trial. Lancet 2017;389:255–265. Borghaei H, Paz-Ares L, Horn L, et al. Nivolumab versus Docetaxel in Advanced Nonsquamous Non-Small-Cell Lung Cancer. N Engl J Med 2015;373:1627–1639. Chen DS, Mellman I: Oncology Meets Immunology: The Cancer-Immunity Cycle. Immunity 2013, 39:1–10. Zou WP, Wolchok JD, Chen LP. PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: Mechanisms, response biomarkers, and combinations. Sci Transl Med. 2016; 8:328rv4. Patel SP, Kurzrock R. PD-L1 Expression as a predictive biomarker in cancer immunotherapy. Mol Cancer Ther 2015;14:847–56. Cordonnier M, Nardin C, Chanteloup G, et al. Tracking the evolution of circulating exosomal-PD-L1 to monitor melanoma patients. J Extracell Vesicles 2020;9:1710899. Del Re M, Marconcini R, Pasquini G, et al. PD-L1 mRNA expression in plasma-derived exosomes is associated with response to anti-PD-1 antibodies in melanoma and NSCLC. Br J Cancer 2018;118:820–824. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 2009;45:228–47. Reclusa P, Verstraelen P, Taverna S, et al. Improving extracellular vesicles visualization: From static to motion. Sci Rep 2020;10(1):6494. Thery C, Witwer KW, Aikawa E, et al. Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for extracellular vesicles and update of the MISEV2014 guidelines. J Extracell Vesicles 2018;7:1535750.