Abstract 566: High dimensional single cell analysis predicts response to anti-PD-1 immunotherapy

Checkpoint inhibition of programmed cell death protein 1 (PD-1) has revolutionized cancer therapy. As more and more patients with metastatic melanoma but also other cancers show a dramatic increase in progression-free survival, still a large proportion of patients do not show durable response. As options for monotherapies, as well as combination immunotherapies, increase in the clinics, predictive biomarkers of clinical response are urgently needed. We employed high-dimensional single cell mass cytometry and a machine-learning bioinformatics pipeline for the in-depth characterization of all immune cells in the peripheral blood of stage IV melanoma patients before and at 12 weeks of anti-PD-1 immunotherapy. We observed a clear treatment response of patients under immunotherapy. However, a strong predictor of progression free and overall survival in response to anti-PD-1 immunotherapy before therapy was the frequency of CD14 + CD16 - HLA-DR hi monocytes. We could confirm this by conventional flow cytometry in an independent, blinded validation cohort and propose this as a novel predictive biomarker for therapy decisions in the clinic. We further present a high dimensional analysis workflow to analyze predictive and prognostic immune biomarkers during future clinical trials. Citation Format: Carsten Krieg, Malgorzata Nowicka, Silvia Guglietta, Sabrina Schindler, Felix J. Hartmann, Lukas M. Weber, Reinhard Dummer, Mark D. Robinson, Mitchell P. Levesque, Burkhard Becher. High dimensional single cell analysis predicts response to anti-PD-1 immunotherapy [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 566.