Department of Pulmonary Medicine, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
Department of Medical Oncology, Erasmus University Medical Center, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
Cancer Immunol Immunother. 2020 May;69(5):771-777. doi: 10.1007/s00262-020-02506-x. Epub 2020 Feb 12.
A minority of NSCLC patients benefit from anti-PD1 immune checkpoint inhibitors. A rational combination of biomarkers is needed. The objective was to determine the predictive value of tumor mutational load (TML), CD8 T cell infiltration, HLA class-I and PD-L1 expression in the tumor.
Metastatic NSCLC patients were prospectively included in an immune-monitoring trial (NTR7015) between April 2016-August 2017, retrospectively analyzed in FFPE tissue for TML (NGS: 409 cancer-related-genes) and by IHC staining to score PD-L1, CD8 T cell infiltration, HLA class-I. PFS (RECISTv1.1) and OS were analyzed by Kaplan-Meier methodology.
30 patients with adenocarcinoma (67%) or squamous cell carcinoma (33%) were included. High TML was associated with better PFS (p = 0.004) and OS (p = 0.025). Interaction analyses revealed that patients with both high TML and high total CD8 T cell infiltrate (p = 0.023) or no loss of HLA class-I (p = 0.026), patients with high total CD8 T cell infiltrate and no loss of HLA class-I (p = 0.041) or patients with both high PD-L1 and high TML (p = 0.003) or no loss of HLA class-I (p = 0.032) were significantly associated with better PFS. Unsupervised cluster analysis based on these markers revealed three sub-clusters, of which cluster-1A was overrepresented by patients with progressive disease (15 out of 16), with significant effect on PFS (p = 0.007).
This proof-of-concept study suggests that a combination of PD-L1 expression, TML, CD8 T cell infiltration and HLA class-I functions as a better predictive biomarker for response to anti-PD-1 immunotherapy. Consequently, refinement of this set of biomarkers and validation in a larger set of patients is warranted.
少数非小细胞肺癌 (NSCLC) 患者受益于抗 PD-1 免疫检查点抑制剂。需要合理组合生物标志物。本研究旨在确定肿瘤突变负荷 (TML)、CD8 T 细胞浸润、HLA Ⅰ类和肿瘤 PD-L1 表达的预测价值。
2016 年 4 月至 2017 年 8 月，前瞻性纳入转移性 NSCLC 患者进行免疫监测试验 (NTR7015)，对 FFPE 组织进行 TML（NGS：409 个癌症相关基因）分析，并通过免疫组化染色对 PD-L1、CD8 T 细胞浸润、HLA Ⅰ类进行评分。采用 Kaplan-Meier 法分析无进展生存期 (RECISTv1.1) 和总生存期 (OS)。
30 例患者中腺癌 (67%) 或鳞状细胞癌 (33%)。高 TML 与更好的无进展生存期 (p=0.004) 和总生存期 (p=0.025) 相关。交互分析显示，高 TML 且总 CD8 T 细胞浸润高 (p=0.023) 或 HLA Ⅰ类不失活 (p=0.026)、总 CD8 T 细胞浸润高且 HLA Ⅰ类不失活 (p=0.041)、高 PD-L1 且高 TML 或 HLA Ⅰ类不失活 (p=0.003) 的患者无进展生存期显著延长。基于这些标志物的无监督聚类分析显示，有 3 个亚群，其中簇 1A 以进展性疾病患者为主 (16 例中有 15 例)，对无进展生存期有显著影响 (p=0.007)。
本概念验证研究表明，PD-L1 表达、TML、CD8 T 细胞浸润和 HLA Ⅰ类功能的组合可作为抗 PD-1 免疫治疗反应的更好预测生物标志物。因此，需要对这组生物标志物进行细化，并在更大的患者群体中进行验证。
