Institute of Cell Biology and Immunology, University of Stuttgart, Stuttgart, Germany.
Department of Physiology & Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland.
Cell Death Differ. 2020 Aug;27(8):2417-2432. doi: 10.1038/s41418-020-0512-5. Epub 2020 Feb 21.
Second generation TRAIL-based therapeutics, combined with sensitising co-treatments, have recently entered clinical trials. However, reliable response predictors for optimal patient selection are not yet available. Here, we demonstrate that a novel and translationally relevant hexavalent TRAIL receptor agonist, IZI1551, in combination with Birinapant, a clinically tested IAP antagonist, efficiently induces cell death in various melanoma models, and that responsiveness can be predicted by combining pathway analysis, data-driven modelling and pattern recognition. Across a panel of 16 melanoma cell lines, responsiveness to IZI1551/Birinapant was heterogeneous, with complete resistance and pronounced synergies observed. Expression patterns of TRAIL pathway regulators allowed us to develop a combinatorial marker that predicts potent cell killing with high accuracy. IZI1551/Birinapant responsiveness could be predicted not only for cell lines, but also for 3D tumour cell spheroids and for cells directly isolated from patient melanoma metastases (80-100% prediction accuracies). Mathematical parameter reduction identified 11 proteins crucial to ensure prediction accuracy, with x-linked inhibitor of apoptosis protein (XIAP) and procaspase-3 scoring highest, and Bcl-2 family members strongly represented. Applied to expression data of a cohort of n = 365 metastatic melanoma patients in a proof of concept in silico trial, the predictor suggested that IZI1551/Birinapant responsiveness could be expected for up to 30% of patient tumours. Overall, response frequencies in melanoma models were very encouraging, and the capability to predict melanoma sensitivity to combinations of latest generation TRAIL-based therapeutics and IAP antagonists can address the need for patient selection strategies in clinical trials based on these novel drugs.
第二代以 TRAIL 为基础的治疗药物与增敏联合治疗最近已进入临床试验。然而,对于最佳患者选择,还没有可靠的反应预测因子。在这里,我们证明了一种新型的、具有转化相关性的六价 TRAIL 受体激动剂 IZI1551,与已在临床测试的 IAP 拮抗剂 Birinapant 联合使用,可有效诱导各种黑色素瘤模型中的细胞死亡,并且可以通过结合通路分析、数据驱动建模和模式识别来预测反应性。在 16 个黑色素瘤细胞系的面板中,对 IZI1551/Birinapant 的反应性存在异质性,观察到完全耐药和明显的协同作用。TRAIL 通路调节剂的表达模式使我们能够开发出一种组合标志物,能够以高精度预测有效的细胞杀伤。不仅可以预测 IZI1551/Birinapant 对细胞系的反应性,还可以预测 3D 肿瘤细胞球体和直接从患者黑色素瘤转移灶中分离的细胞的反应性(预测准确率为 80-100%)。数学参数减少确定了 11 种对确保预测准确性至关重要的蛋白质,其中 X 连锁凋亡抑制剂蛋白 (XIAP) 和前半胱天冬酶-3 评分最高,Bcl-2 家族成员也强烈代表。在概念验证的计算临床试验中,对 n = 365 名转移性黑色素瘤患者的队列表达数据进行应用,该预测器表明,多达 30%的患者肿瘤可能对 IZI1551/Birinapant 有反应。总体而言,黑色素瘤模型中的反应频率非常令人鼓舞,并且能够预测黑色素瘤对最新一代以 TRAIL 为基础的治疗药物和 IAP 拮抗剂的组合的敏感性,可以满足基于这些新型药物的临床试验中患者选择策略的需求。