Soluble immune checkpoints and T-cell subsets in blood as biomarkers for resistance to immunotherapy in melanoma patients.
Soluble immune checkpoints and T-cell subsets in blood as biomarkers for resistance to immunotherapy in melanoma patients.
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DOI：
10.1080/2162402x.2021.1926762
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发表时间：
2021-05-25
期刊：
影响因子：
7.2
通讯作者：
Hassel JC
中科院分区：
文献类型：
--
作者：
Machiraju D;Wiecken M;Lang N;Hülsmeyer I;Roth J;Schank TE;Eurich R;Halama N;Enk A;Hassel JC
不同的机制导致免疫检查点抑制物(ICI)抵抗。识别临床有用的生物标志物可能会改善药物选择和患者的治疗。我们用ELISA法分析了ICI治疗前后黑色素瘤患者外周血中sPD1、sPDL1、sLAG3和sTIM3的可溶性免疫检查点，并用流式细胞仪分析了sPD1、sPDL1、sLAG3和sTIM3的表达。用免疫组织化学方法检测治疗前黑色素瘤转移瘤组织中TIM3和LAG3的表达。结果与治疗反应和无进展生存期(PFS)相关。对抗PD1治疗的抵抗(n=448)与治疗前血清sLAG3水平高有关(DCR：P=10.009；PFS：P=10.018；ROC截止值>；148 pg/ml)，但与sPD1、sPDL1或sTIM3无关。相比之下，对ipilimumab加nivolumab(n=42)的耐药性与高水平的sPD1(DCR：P=10.019，PFS：P=10.046；ROC截止&>167 pg/ml)有关，而与sPDL1、sLAG3或sTIM3无关。随着治疗的进行，两种治疗方案的sPD1血清水平均显著升高(p<；2.0001)。FACS分析显示，在抗PD1耐药患者中，CD3+、CD8+、PD1+T细胞频率降低(p=4.028)，而CD3+、CD4+、LAG3++T细胞频率上升是ipilimumab+nivolumab耐药患者的特征(p=10.033)。与抗PD1单药治疗不同，联合阻断显著增加增殖的T细胞(CD3+CD8+Ki67+T细胞；p<；2.0001)和嗜酸性粒细胞(p=0.001)。在黑色素瘤转移瘤中，肿瘤微环境中TIM3+T细胞或LAG3+T细胞的浸润增加与抗PD1治疗下较短的PFS相关(TIM3：P=0.019，LAG3：P=8.07)。不同的可溶性免疫检查点是检查点抑制物抵抗黑色素瘤的特征。这些血清标志物的检测有可能用于临床常规治疗。
Different mechanisms lead to immune checkpoint inhibitor (ICI) resistance. Identifying clinically useful biomarkers might improve drug selection and patients’ therapy. We analyzed the soluble immune checkpoints sPD1, sPDL1, sLAG3, and sTIM3 using ELISA and their expression on circulating T cells using FACS in pre- and on-treatment blood samples of ICI treated melanoma patients. In addition, pre-treatment melanoma metastases were stained for TIM3 and LAG3 expression by IHC. Results were correlated with treatment response and progression-free survival (PFS). Resistance to anti-PD1 treatment (n = 48) was associated with high pre-treatment serum levels of sLAG3 (DCR: p = .009; PFS: p = .018; ROC cutoff >148 pg/ml) but not sPD1, sPDL1 or sTIM3. In contrast, resistance to ipilimumab plus nivolumab (n = 42) was associated with high levels of sPD1 (DCR: p = .019, PFS: p = .046; ROC cutoff >167 pg/ml) but not sPDL1, sLAG3 or sTIM3. Both treatment regimens shared a profound increase of sPD1 serum levels with treatment (p < .0001). FACS analysis revealed reduced frequencies of CD3+ CD8+ PD1 + T cells (p = .028) in anti-PD1-resistant patients, whereas increased frequencies of CD3+ CD4+ LAG3 + T cells characterized patients resistant to ipilimumab plus nivolumab (p = .033). Unlike anti-PD1 monotherapy, combination blockade significantly increased proliferating T cells (CD3+ CD8+ Ki67 + T cells; p < .0001) and eosinophils (p = .001). In melanoma metastases, an increased infiltration with TIM3+ or LAG3 + T cells in the tumor microenvironment correlated with a shorter PFS under anti-PD1 treatment (TIM3: p = .019, LAG3: p = .07). Different soluble immune checkpoints characterized checkpoint inhibitor-resistant melanoma. Measuring these serum markers may have the potential to be used in clinical routine.