Muller Mirte, Hummelink Karlijn, Hurkmans Daan P, Niemeijer Anna-Larissa N, Monkhorst Kim, Roder Joanna, Oliveira Carlos, Roder Heinrich, Aerts Joachim G, Smit Egbert F
Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands.
Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands.
Clin Cancer Res. 2020 Oct 1;26(19):5188-5197. doi: 10.1158/1078-0432.CCR-20-0538. Epub 2020 Jul 6.
Pretreatment selection of patients with non-small cell lung cancer (NSCLC) who would derive clinical benefit from treatment with immune checkpoint inhibitors (CPIs) would fulfill an unmet clinical need by reducing unnecessary toxicities from treatment and result in substantial health care savings.
In a retrospective study, mass spectrometry (MS)-based proteomic analysis was performed on pretreatment sera derived from patients with advanced NSCLC treated with nivolumab as part of routine clinical care ( = 289). Machine learning combined spectral and clinical data to stratify patients into three groups with good ("sensitive"), intermediate, and poor ("resistant") outcomes following treatment in the second-line setting. The test was applied to three independent patient cohorts and its biology was investigated using protein set enrichment analyses (PSEA).
A signature consisting of 274 MS features derived from a development set of 116 patients was associated with progression-free survival (PFS) and overall survival (OS) across two validation cohorts ( = 98 and = 75). In pooled analysis, significantly better OS was demonstrated for "sensitive" relative to "not sensitive" patients treated with nivolumab; HR, 0.58 (95% confidence interval, 0.38-0-87; = 0.009). There was no significant association with clinical factors including PD-L1 expression, available from 133 of 289 patients. The test demonstrated no significant association with PFS or OS in a historical cohort ( = 68) of second-line NSCLC patients treated with docetaxel. PSEA revealed proteomic classification to be significantly associated with complement and wound-healing cascades.
This serum-derived protein signature successfully stratified outcomes in cohorts of patients with advanced NSCLC treated with second-line PD-1 CPIs and deserves further prospective study.
对非小细胞肺癌（NSCLC）患者进行预处理筛选，以确定哪些患者能从免疫检查点抑制剂（CPI）治疗中获得临床益处，这将满足一项未被满足的临床需求，即减少治疗带来的不必要毒性，并节省大量医疗费用。
在一项回顾性研究中，对作为常规临床护理一部分接受纳武单抗治疗的晚期NSCLC患者的预处理血清进行了基于质谱（MS）的蛋白质组分析（n = 289）。机器学习结合光谱和临床数据，将患者分为三组，在二线治疗后分别具有良好（“敏感”）、中等和不良（“耐药”）结局。该测试应用于三个独立的患者队列，并使用蛋白质集富集分析（PSEA）对其生物学特性进行了研究。
由116例患者的开发集得出的包含274个MS特征的特征图谱与两个验证队列（n = 98和n = 75）中的无进展生存期（PFS）和总生存期（OS）相关。在汇总分析中，接受纳武单抗治疗的“敏感”患者相对于“不敏感”患者显示出显著更好的OS；风险比（HR）为0.58（95%置信区间，0.38 - 0.87；P = 0.009）。与包括PD-L1表达在内的临床因素无显著关联，289例患者中有133例可获得该数据。该测试在接受多西他赛治疗的二线NSCLC患者的历史队列（n = 68）中与PFS或OS无显著关联。PSEA显示蛋白质组分类与补体和伤口愈合级联反应显著相关。
这种源自血清的蛋白质特征图谱成功地对接受二线PD - 1 CPI治疗的晚期NSCLC患者队列的结局进行了分层，值得进一步进行前瞻性研究。
