Circulating cytokine associations with clinical outcomes in melanoma patients treated with combination nivolumab plus ipilimumab

Abstract

Nivolumab plus ipilimumab (aCTLA-4/aPD-1) combination therapy has significantly improved clinical outcomes in patients with metastatic melanoma, with 50%-60% of patients responding to treatment, but predictors of response are poorly characterized. We hypothesized that circulating cytokines and peripheral white blood cells may predict response to therapy and evaluated 15 cytokines and complete blood counts (CBC with differentials) from 89 patients with advanced melanoma treated with combination therapy from three points in time: pre-treatment, one month and approximately three months after starting therapy. Clinical endpoints evaluated included durable clinical benefit (DCB), progression-free survival (PFS), and overall survival (OS). A parsimonious predictive model was developed to identify cytokines predictors of response to combination therapy. In this study, we found that pre-treatment, patients with DCB had higher IL-23, lower CXCL6, and lower IL-10 levels. Lower NLR one month after starting therapy predicted better PFS and OS, primarily driven by an increase in absolute lymphocytes. A multivariate model demonstrated that baseline CXCL6, IL-10, IL-23 were independent predictors of therapy response, and the combined model has reached an area under the curve (AUC) of 0.79 in prediction of response to combination therapy. Our study identified baseline CXCL6, IL-23, and IL-10 as predictors of response to aCTLA4/aPD1 combination therapy among patients with metastatic melanoma. This study also provides a framework for identifying patients who are likely to respond to combination ICB, as well as a subset of patients with high risk of developing resistance and are thus in need of alternative therapeutic options, such as clinical trials.

Keywords: Checkpoint blockade; biomarkers for immunotherapy; combination immunotherapy; cytokines; melanoma; translational research.

Figure 1.

Association between cytokines levels and response to combination immune checkpoint blockade. A. Differential cytokines and chemokines abundance in responders (DCB, patients with durable clinical benefit) versus non-responders (NCB, patients without durable clinical benefit) at three different time points (pre, post1, post2). The comparisons were done using Wilcoxon rank-sum test. Cytokines concentration higher in responders are shown in blue while those higher in non-responders are shown in sand. Significance test results are marked with asterisks in heatmap (*p <0.05, **:p<0.01, ***:p <0.001). (Pre: DCB =51 NCB = 38 ntotal= 89; post1: DCB =43 NCB = 34 total= 77; post2: DCB =47 NCB = 29 total= 76). B. Baseline CXCL5, CXCL6, IL-23, IL-10 in responders versus non-responders. (DCB Y: Patients with durable clinical benefit. DCB N: Patients without durable clinical benefits). Responders had higher CXCL5 (MWW, p < 0.05), CXCL6 (MWW, p <0.01), higher IL-10 (MWW, p <0.05), and lower IL-23 (MWW, P<0.05) (DCB =51, NCB = 38). C. Longitudinal changes of cytokines and chemokines following treatment. Cytokines changes were evaluated with a longitudinal mixed model combining both DCB and NCB (see methods), with yellow for increasing concentration and green for decreasing concentration (*:p <0.05, **:p<0.01, ***:p <0.001).

Figure 2.

Association of peripheral neutrophil and lymphocyte counts with response to therapy and survival. A. Association of peripheral neutrophil and lymphocyte counts at three time points with response to therapy. Wilcoxon rank-sum test was performed, with asterisks indicating significance level: p- value<=0.05*, p-value<=0.01**. Counts in DCB are shown in blue and in NCB in sand. NLR: Neutrophils to Lymphocytes ratio. (Pre: n = 85 samples, post1: n = 73 samples, post2: n = 73 samples) B. Change in peripheral lymphocyte counts by response to therapy. Left, change in mean lymphocyte count at three time points in DCB and NCB patients. Whiskers indicate mean standard error. Right, fold change of lymphocyte counts from pre to post1 between responders and non-responders (Wilcoxon rank-sum, p <0.05). (Pre: n = 85 samples, post1: n = 73 samples, post2: n = 73 samples; patients with matched pre and post1: n = 72 samples, DCB = 39, NCB = 33) C.D. Survival in patients stratified by fold changes of ALC from pre to post1 time point. PFS and OS stratified patients by the median of ALC. E.F. Survival in patients stratified by high and low NLR at the post1 time point. PFS and OS, stratifying by median level of NLR at post1 time point (2.67).

Figure 3.

An integrative analysis of the association between baseline chemokine CXCL6 and neutrophils related chemokines and cytokines; IL-10 and IL-23 correlated with other circulating cytokines. A. Correlation matrix among all baseline cytokines and chemokines. (Spearman correlation, only statistically significant coefficient values displayed; n = 89 samples).

Figure 4.

Predicting response and survival with CXCL6, IL-10, andIL-23. A. Joint association of DCB with CXCL6, IL-10, and IL-23. x and y axes correspond with the levels of IL-10 and CXCL6, and the size of the dots represent the IL-23 level. Responders are colored with blue and non-responders with sand. The dotted lines represent the median value of CXCL6 and IL-10. B. ROC of the multivariate logistic regression models implemented with different features. Odds ratio of patients predicted to be DCB by the three-feature model = 8.97 (95% CI: 3.36-24.00, p = 0.0002827). C. Effect of feature scores on patients’ survival outcome. Patients were stratified into four groups using a feature score defined by the number of positive features (high IL23, low CXCL6, low IL10). D. Cox model on feature scores. (left) OS model showing hazard ratios of feature score 1 and 2, with 0 as reference. Feature score 3 was excluded from the model as the patient group with score 3 did not have any deaths. (right) PFS model showing hazard ratios of feature scores 1, 2, and 3, with 0 as reference.

Figure 5.

The effect of prior IO treatment on cytokines and their associations with response. A. Association between prior IO and DCB (Fisher’s exact test, p = 0.4, OR = 0.67). B. Systemic effect of prior IO on circulating cytokines from pre treatment time point. Van elteren tests were performed to evaluate baseline cytokines association with priorIO, adjusted by propensity scores for receiving priorIO. Significance test results are marked with asterisks in heatmap (*:p <0.05, **:p<0.01, ***:p <0.001) (patients with priorIO n = 24; patients without priorIO n= 65). C. AUC of applying three- feature model on IO treated and untreated patients subsets. (patients without priorIO: AUC = 0.8, patients with priorIO: AUC = 0.73). D. Association between response to therapy and CXCL6 levels stratified by prior IO. MWW tests were performed, with asterisks showing statistical significance (*:p <0.05, **:p<0.01, ***:p <0.001). E. Association between response to therapy and IL10 levels stratified by prior IO. MWW tests were performed, with asterisks showing statistical significance (*:p <0.05, **:p<0.01, ***:p <0.001). F. Association between response to therapy and IL23 levels stratified by prior IO. MWW tests were performed, with asterisks showing statistical significance (*:p <0.05, **:p<0.01, ***:p <0.001).