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.

中文翻译：

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通路分析和模式识别的融合预测了 IAP 拮抗作用对最新一代 TRAIL 疗法的敏感性。

第二代基于 TRAIL 的疗法与致敏联合疗法相结合，最近已进入临床试验。然而，用于最佳患者选择的可靠反应预测指标尚不可用。在这里，我们证明了一种新的和翻译相关的六价 TRAIL 受体激动剂 IZI1551 与经临床测试的 IAP 拮抗剂 Birinapant 结合，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。在一组 16 个黑色素瘤细胞系中，对 IZI1551/Birinapant 的反应是异质的，观察到完全抗性和明显的协同作用。TRAIL 通路调节因子的表达模式使我们能够开发出一种组合标记，可以高精度预测有效的细胞杀伤。IZI1551/Birinapant 反应性不仅可以预测细胞系，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（80-100% 预测准确率）。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 连锁凋亡蛋白抑制剂 (XIAP) 和 procaspase-3 得分最高，Bcl-2 家族成员代表强烈。在计算机概念验证试验中应用于 n = 365 名转移性黑色素瘤患者队列的表达数据，预测因子表明 IZI1551/Birinapant 反应性可预期高达 30% 的患者肿瘤。总体，