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肿瘤炎症和上皮-间质转化 (EMT) 的基因特征可高精度预测肺癌对免疫检查点阻断的反应。

Gene signatures of tumor inflammation and epithelial-to-mesenchymal transition (EMT) predict responses to immune checkpoint blockade in lung cancer with high accuracy.

机构信息

Division of Pulmonary, Allergy and Critical Care Medicine, Thoracic Oncology Group, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.

Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, United States; Abramson Cancer Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.

出版信息

Lung Cancer. 2020 Jan;139:1-8. doi: 10.1016/j.lungcan.2019.10.012. Epub 2019 Oct 18.


DOI:10.1016/j.lungcan.2019.10.012
PMID:31683225
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7176049/
Abstract

OBJECTIVES: Treatment of non-small cell lung cancer (NSCLC) with immune checkpoint blockade (ICB) has resulted in striking clinical responses, but only in a subset of patients. The goal of this study was to evaluate transcriptional signatures previously reported in the literature in an independent cohort of NSCLC patients receiving ICB. MATERIALS AND METHODS: This retrospective study analyzed transcriptional profiles from pre-treatment tumor samples of 52 chemotherapy-refractory advanced NSCLC patients treated with anti-PD1/PD-L1 therapy. Gene signatures based on published reports were created and examined for their association with response to therapy and progression-free and overall survival (PFS, OS). RESULTS: Two signatures predicting response and outcomes were identified. One reflected the degree of immune infiltration and upregulation of interferon-gamma-induced genes. A second reflected the EMT status. Compared to those not responding to therapy, patients whose tumors responded to ICB had higher scores in an inflammatory gene signature (6.0 ± 2.9 vs -5.5 ± 3.4, p = 0.014) or a more epithelial phenotype (-1.7 ± 1.0 vs 2.1 ± 1.2, p = 0.016). Both signatures demonstrated a satisfactory predictive accuracy for response: AUC of 0.69 (95% CI: 0.54, 0.84) for the inflammatory and 0.70 (95% CI: 0.55, 0.85) for EMT signatures, respectively. A weighted score combining EMT and inflammatory signatures showed increased predictive value with AUC of 0.92 (95% CI: 0.85, 0.99). Kaplan-Meier curves for patients above and below the median combined score showed a significant separation for PFS and OS (all p < 0.01, log rank test). CONCLUSIONS: The EMT/Inflammation signature score may be useful in directing checkpoint inhibitor therapy in lung cancer and suggests that reversal of EMT might augment efficacy of ICB.

摘要

目的:免疫检查点阻断(ICB)治疗非小细胞肺癌(NSCLC)导致了显著的临床反应,但仅在一部分患者中。本研究的目的是在接受 ICB 的 NSCLC 患者的独立队列中评估文献中先前报道的转录特征。

材料和方法:这项回顾性研究分析了 52 例接受抗 PD1/PD-L1 治疗的化疗耐药晚期 NSCLC 患者治疗前肿瘤样本的转录谱。根据已发表的报告创建了基于基因的特征,并研究了它们与治疗反应、无进展生存期(PFS)和总生存期(OS)的相关性。

结果:确定了两个预测反应和结局的特征。一个反映了免疫浸润的程度和干扰素-γ诱导基因的上调。第二个反映了 EMT 状态。与那些对治疗无反应的患者相比,肿瘤对 ICB 有反应的患者的炎症基因特征评分较高(6.0±2.9 与-5.5±3.4,p=0.014)或上皮表型较高(-1.7±1.0 与 2.1±1.2,p=0.016)。这两个特征对反应均具有良好的预测准确性:炎症特征的 AUC 为 0.69(95%CI:0.54,0.84),EMT 特征的 AUC 为 0.70(95%CI:0.55,0.85)。结合 EMT 和炎症特征的加权评分显示出更高的预测价值,AUC 为 0.92(95%CI:0.85,0.99)。中位数联合评分高于或低于中位数的患者的 Kaplan-Meier 曲线显示 PFS 和 OS 有显著分离(所有 p<0.01,对数秩检验)。

结论:EMT/炎症特征评分可能有助于指导肺癌的检查点抑制剂治疗,并表明 EMT 的逆转可能增强 ICB 的疗效。

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本文引用的文献

[1]
T-Cell-Inflamed Gene-Expression Profile, Programmed Death Ligand 1 Expression, and Tumor Mutational Burden Predict Efficacy in Patients Treated With Pembrolizumab Across 20 Cancers: KEYNOTE-028.

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Nat Rev Mol Cell Biol. 2019-2

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