Baseline Peripheral Blood Biomarkers Associated with Clinical Outcome of Advanced Melanoma Patients Treated with Ipilimumab

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.

Figure 1. Overall survival according to confirmed biomarkers

Kaplan-Meier analysis of overall survival in the identification and confirmation cohort (n=209) according to LDH-ratio (the measured LDH serum concentration divided by the upper limit of normal) (A), relative lymphocyte count (B), frequency of Lin⁻CD14⁺HLA-DR^−/low myeloid-derived suppressor cells (MDSCs, C), absolute monocyte count (D), absolute eosinophil count (E), and frequency of CD4⁺CD25⁺FoxP3⁺ regulatory T cells (Tregs, F). Censoring is indicated by vertical lines; p-values were calculated by log rank statistics.

Figure 2. Overall survival and tumor response according to combination model 1

A nomogram-based linear predictor measure was calculated for each patient considering the relative impact of single factors according to Cox regression analysis (A). In combination model 1, the LDH-ratio (at two cut-off points), the absolute eosinophil and monocyte counts, the relative lymphocyte count, the frequency of Lin⁻CD14⁺HLA-DR^−/low myeloid-derived suppressor cells (MDSCs) and CD4⁺CD25⁺FoxP3⁺ regulatory T cells (Tregs) were considered. Kaplan-Meier analysis of overall survival is presented according to the patient´s individual risk score, which was calculated as the sum of the values of 7 separate factors. Censoring is indicated by vertical lines (B). The best overall tumor response according to immune-related response criteria (irRC) was analyzed either as the rate of patients with irRC benefit (sum of those with complete responses, partial responses and stable disease) or irRC response (sum of those with complete or partial responses) (C). * p < 0.05; ** p < 0.01; *** p < 0.001.

Figure 3. Overall survival and tumor response according to combination model 2

In combination model 2, only routine biomarkers, available in daily practice, were considered. In addition to the absolute eosinophil and monocyte counts, the relative lymphocyte counts and LDH (categorized as elevated vs. normal) was integrated. Patients were stratified according to the number of favorable factors for Kaplan-Meier analysis of overall survival. Censoring is indicated by vertical lines (A). The best overall tumor response according to immune-related response criteria (irRC) was analyzed either as the rate of patients with irRC benefit (sum of those with complete responses, partial responses and stable disease) or irRC response (sum of those with complete or partial responses) (B). The association with overall survival of combination model 2 was confirmed in an independent validation cohort of 378 patients with available data for all 4 factors (C). * p < 0.05; ** p < 0.01; *** p < 0.001.