Center for Cancer Immunotherapy, La Jolla Institute for Immunology, La Jolla, CA, United States.
Cancer Research Program, Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain.
Front Immunol. 2022 Apr 14;13:842653. doi: 10.3389/fimmu.2022.842653. eCollection 2022.
Non-small cell lung carcinoma (NSCLC) is the leading cause of cancer-related deaths globally. Immune checkpoint blockade (ICB) has transformed cancer medicine, with anti-programmed cell death protein 1 (anti-PD-1) therapy now well-utilized for treating NSCLC. Still, not all patients with NSCLC respond positively to anti-PD-1 therapy, and some patients acquire resistance to treatment. There remains an urgent need to find markers predictive of anti-PD-1 responsiveness. To this end, we performed mass cytometry on peripheral blood mononuclear cells from 26 patients with NSCLC during anti-PD-1 treatment. Patients who responded to anti-PD-1 ICB displayed significantly higher levels of antigen-presenting myeloid cells, including CD9 nonclassical monocytes, and CD33 classical monocytes. Using matched pre-post treatment samples, we found that the baseline pre-treatment frequencies of CD33 monocytes predicted patient responsiveness to anti-PD-1 therapy. Moreover, some of these classical and nonclassical monocyte subsets were associated with reduced immunosuppression by T regulatory (CD4FOXP3CD25) cells in the same patients. Our use of machine learning corroborated the association of specific monocyte markers with responsiveness to ICB. Our work provides a high-dimensional profile of monocytes in NSCLC and links CD33 expression on monocytes with anti-PD-1 effectiveness in patients with NSCLC.
非小细胞肺癌(NSCLC)是全球癌症相关死亡的主要原因。免疫检查点阻断(ICB)已经改变了癌症治疗方法,抗程序性细胞死亡蛋白 1(抗 PD-1)疗法现在已广泛用于治疗 NSCLC。然而,并非所有 NSCLC 患者都对抗 PD-1 治疗有积极反应,有些患者对治疗产生耐药性。因此,迫切需要寻找预测抗 PD-1 反应性的标志物。为此,我们对 26 名接受抗 PD-1 治疗的 NSCLC 患者的外周血单核细胞进行了质谱细胞术分析。对 ICB 有反应的患者表现出明显更高水平的抗原呈递髓系细胞,包括 CD9 非经典单核细胞和 CD33 经典单核细胞。使用匹配的治疗前后样本,我们发现 CD33 单核细胞的基线预处理频率可预测患者对抗 PD-1 治疗的反应性。此外,在同一患者中,这些经典和非经典单核细胞亚群中的一些与 T 调节(CD4FOXP3CD25)细胞的免疫抑制作用降低有关。我们使用机器学习进一步证实了特定单核细胞标志物与 ICB 反应性之间的关联。我们的工作提供了 NSCLC 中单核细胞的高维图谱,并将单核细胞上的 CD33 表达与 NSCLC 患者对抗 PD-1 治疗的有效性联系起来。