Pedersen Jesper Geert, Sokac Mateo, Sørensen Boe Sandahl, Luczak Adam Andrzej, Aggerholm-Pedersen Ninna, Birkbak Nicolai Juul, Øllegaard Trine Heide, Jakobsen Martin Roelsgaard
Department of Biomedicine, Aarhus University, 8000 Aarhus C, Denmark.
Department of Molecular Medicine (MOMA), Aarhus University Hospital, 8200 Aarhus N, Denmark.
Cancers (Basel). 2022 Jul 9;14(14):3342. doi: 10.3390/cancers14143342.
Checkpoint inhibitors have revolutionized the treatment of metastatic melanoma, yielding long-term survival in a considerable proportion of the patients. Yet, 40-60% of patients do not achieve a long-term benefit from such therapy, emphasizing the urgent need to identify biomarkers that can predict response to immunotherapy and guide patients for the best possible treatment. Here, we exploited an unsupervised machine learning approach to identify potential inflammatory cytokine signatures from liquid biopsies, which could predict response to immunotherapy in melanoma.
We studied a cohort of 77 patients diagnosed with unresectable advanced-stage melanoma undergoing treatment with first-line nivolumab plus ipilimumab or pembrolizumab. Baseline and on-treatment plasma samples were tested for levels of PD-1, PD-L1, IFNγ, IFNβ, CCL20, CXCL5, CXCL10, IL6, IL8, IL10, MCP1, and TNFα and analyzed by Uniform Manifold Approximation and Projection (UMAP) dimension reduction method and k-means clustering analysis.
Interestingly, using UMAP analysis, we found that treatment-induced cytokine changes measured as a ratio between baseline and on-treatment samples correlated significantly to progression-free survival (PFS). For patients treated with nivolumab plus ipilimumab we identified a group of patients with superior PFS that were characterized by significantly higher baseline-to-on-treatment increments of PD-1, PD-L1, IFNγ, IL10, CXCL10, and TNFα compared to patients with worse PFS. Particularly, a high PD-1 increment was a strong individual predictor for superior PFS (HR = 0.13; 95% CI 0.034-0.49; = 0.0026). In contrast, decreasing levels of IFNγ and IL6 and increasing levels of CXCL5 were associated with superior PFS in the pembrolizumab group, although none of the cytokines were individually predictors for PFS.
In short, our study demonstrates that a high increment of PD-1 is associated with superior PFS in advanced-stage melanoma patients treated with nivolumab plus ipilimumab. In contrast, decreasing levels of IFNγ and IL6, and increasing levels of CXCL5 are associated with response to pembrolizumab. These results suggest that using serial samples to monitor changes in cytokine levels early during treatment is informative for treatment response.
检查点抑制剂彻底改变了转移性黑色素瘤的治疗方式,使相当一部分患者获得了长期生存。然而,40 - 60%的患者并未从这种治疗中获得长期益处,这凸显了迫切需要识别能够预测免疫治疗反应并指导患者选择最佳治疗方案的生物标志物。在此,我们采用无监督机器学习方法从液体活检中识别潜在的炎症细胞因子特征,以预测黑色素瘤对免疫治疗的反应。
我们研究了一组77例被诊断为不可切除的晚期黑色素瘤患者,这些患者正在接受一线纳武利尤单抗加伊匹木单抗或帕博利珠单抗治疗。检测基线和治疗期间血浆样本中PD - 1、PD - L1、IFNγ、IFNβ、CCL20、CXCL5、CXCL10、IL6、IL8、IL10、MCP1和TNFα的水平,并通过均匀流形近似和投影(UMAP)降维方法以及k均值聚类分析进行分析。
有趣的是,通过UMAP分析,我们发现以基线和治疗期间样本之间的比率衡量的治疗诱导的细胞因子变化与无进展生存期(PFS)显著相关。对于接受纳武利尤单抗加伊匹木单抗治疗的患者,我们识别出一组PFS较好的患者,与PFS较差的患者相比,他们的PD - 1、PD - L1、IFNγ、IL10、CXCL10和TNFα的基线至治疗期间增量显著更高。特别是,高PD - 1增量是PFS较好的一个强有力的个体预测指标(HR = 0.13;95% CI 0.034 - 0.49;P = 0.0026)。相比之下,在帕博利珠单抗组中,IFNγ和IL6水平降低以及CXCL5水平升高与较好的PFS相关,尽管没有一种细胞因子是PFS的个体预测指标。
简而言之,我们的研究表明,在接受纳武利尤单抗加伊匹木单抗治疗的晚期黑色素瘤患者中,高PD - 1增量与较好的PFS相关。相比之下,IFNγ和IL6水平降低以及CXCL5水平升高与对帕博利珠单抗的反应相关。这些结果表明,在治疗早期使用系列样本监测细胞因子水平的变化对治疗反应具有指导意义。