Detailed gating strategy for quantification of subsets of monocytes and myeloid-derived suppressor cells (MDSCs), T cells and regulatory T cells (Tregs). Total cells were selected by gating on Time vs. SSC-A. Duplicates were removed via progressive gating on FSC-H vs. FSC-A and SSC-H vs. SSC-A. Dead cells were excluded by considering only EMA-negative cells. (A) A lineage cocktail (CD3, CD19, CD56) was used to avoid cross-contamination. Previously described MDSC populations were identified as Lin-CD14+HLA-DRlow and Lin-CD14-CD15+CD11b+ within the all-cell gate. Overall monocytes were defined as CD14+, while subsets were separated into classical monocytes (Lin-CD14+CD16-HLA-DR+), non-classical monocytes (Lin-CD14-CD16+HLA-DR+) and Lin- CD14-CD16dimHLA-DR+ monocytes within the all-cell gate. (B) A morphological gate was used to identify the population of lymphocytes. Next, CD3+ cells were selected and further separated into CD4+ and CD8+ cells. Ki67 expression was investigated on CD4+ and CD8+ cells. CD8+ T cells with suppressive potential were defined as CD103+. Previously described phenotypes of Tregs were defined as CD4+CD25+FoxP3+ and CD4+CD127lowCD25+FoxP3+. These were further subdivided into proliferating (Ki67+CD45RA-) and non-proliferating Tregs (Ki67-CD45RA+).
ARTICLE ABSTRACT
Purpose: To identify baseline peripheral blood biomarkers associated with clinical outcome following ipilimumab treatment in advanced melanoma patients.Experimental Design: Frequencies of myeloid-derived suppressor cells (MDSC) and regulatory T cells (Treg), serum lactate dehydrogenase (LDH), routine blood counts, and clinical characteristics were assessed in 209 patients. Endpoints were overall survival (OS) and best overall response. Statistical calculations were done by Kaplan–Meier and Cox regression analysis, including calibration and discrimination by C-statistics.Results: Low baseline LDH, absolute monocyte counts (AMC), Lin−CD14+HLA-DR−/low-MDSC frequencies, and high absolute eosinophil counts (AEC), relative lymphocyte counts (RLC), and CD4+CD25+FoxP3+-Treg frequencies were significantly associated with better survival, and were considered in a combination model. Patients (43.5%) presenting with the best biomarker signature had a 30% response rate and median survival of 16 months. In contrast, patients with the worst biomarkers (27.5%) had only a 3% response rate and median survival of 4 months. The occurrence of adverse events correlated with neither baseline biomarker signatures nor the clinical benefit of ipilimumab. In another model, limited to the routine parameters LDH, AMC, AEC, and RLC, the number of favorable factors (4 vs. 3 vs. 2–0) was also associated with OS (P < 0.001 for all pairwise comparisons) in the main study and additionally in an independent validation cohort.Conclusions: A baseline signature of low LDH, AMC, and MDSCs as well as high AEC, Tregs, and RLC is associated with favorable outcome following ipilimumab. Prospective investigation of the predictive impact of these markers following ipilimumab and other treatments, e.g., PD-1 antibodies, is warranted. Clin Cancer Res; 22(12); 2908–18. ©2016 AACR.
