Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, Atlanta, GA, USA.
Parker H. Petit Institute for Bioengineering and Bioscience, Atlanta, GA, USA.
Nat Biomed Eng. 2022 Mar;6(3):310-324. doi: 10.1038/s41551-022-00852-y. Epub 2022 Mar 3.
Immune checkpoint blockade (ICB) therapy does not benefit the majority of treated patients, and those who respond to the therapy can become resistant to it. Here we report the design and performance of systemically administered protease activity sensors conjugated to anti-programmed cell death protein 1 (αPD1) antibodies for the monitoring of antitumour responses to ICB therapy. The sensors consist of a library of mass-barcoded protease substrates that, when cleaved by tumour proteases and immune proteases, are released into urine, where they can be detected by mass spectrometry. By using syngeneic mouse models of colorectal cancer, we show that random forest classifiers trained on mass spectrometry signatures from a library of αPD1-conjugated mass-barcoded activity sensors for differentially expressed tumour proteases and immune proteases can be used to detect early antitumour responses and discriminate resistance to ICB therapy driven by loss-of-function mutations in either the B2m or Jak1 genes. Biomarkers of protease activity may facilitate the assessment of early responses to ICB therapy and the classification of refractory tumours based on resistance mechanisms.
免疫检查点阻断 (ICB) 疗法并不能使大多数接受治疗的患者受益,而那些对该疗法有反应的患者可能会对其产生耐药性。在这里,我们报告了系统给药的蛋白酶活性传感器与抗程序性细胞死亡蛋白 1(αPD1)抗体的设计和性能,用于监测对 ICB 治疗的抗肿瘤反应。这些传感器由一组质量标记的蛋白酶底物组成,当被肿瘤蛋白酶和免疫蛋白酶切割时,它们会被释放到尿液中,在那里可以通过质谱法检测到。通过使用结直肠癌的同源小鼠模型,我们表明,使用随机森林分类器对来自一组 αPD1 偶联的质量标记活性传感器的质谱特征进行训练,用于区分表达差异的肿瘤蛋白酶和免疫蛋白酶,可以用于检测早期抗肿瘤反应,并区分由 B2m 或 Jak1 基因失活突变驱动的 ICB 治疗耐药性。蛋白酶活性的生物标志物可能有助于评估 ICB 治疗的早期反应,并根据耐药机制对难治性肿瘤进行分类。