Patient-specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies
Patient-specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies
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DOI：
10.15252/msb.20188664
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发表时间：
2020-02-01
影响因子：
9.9
通讯作者：
Saez-Rodriguez, Julio
中科院分区：
文献类型：
--
作者：
Eduati, Federica;Jaaks, Patricia;Saez-Rodriguez, Julio
对介导患者特异性治疗反应的信号通路进行机械建模有助于揭示耐药机制和改进治疗策略。然而，为患者，特别是实体恶性肿瘤患者创建这样的模型是具有挑战性的。建立这些模型的一个主要障碍是可获得的材料有限，无法产生大规模的扰动数据。在这里，我们提出了一种方法，将使用微流控技术对癌症活检组织进行体外高通量筛选与基于逻辑的建模相结合，以生成特定于患者的外部和内部细胞凋亡信号通路的动态模型。我们使用得到的模型来研究胰腺癌患者的异质性，显示出不同之处，特别是在PI3K-Akt通路上。模型参数的变化较好地反映了肿瘤的不同分期。最后，我们使用我们的动态模型来有效地预测新的个性化组合治疗。我们的结果表明，我们的微流控实验和数学模型的结合可以成为癌症精确医学的一种新工具。
Mechanistic modeling of signaling pathways mediating patient-specific response to therapy can help to unveil resistance mechanisms and improve therapeutic strategies. Yet, creating such models for patients, in particular for solid malignancies, is challenging. A major hurdle to build these models is the limited material available that precludes the generation of large-scale perturbation data. Here, we present an approach that couples ex vivo high-throughput screenings of cancer biopsies using microfluidics with logic-based modeling to generate patient-specific dynamic models of extrinsic and intrinsic apoptosis signaling pathways. We used the resulting models to investigate heterogeneity in pancreatic cancer patients, showing dissimilarities especially in the PI3K-Akt pathway. Variation in model parameters reflected well the different tumor stages. Finally, we used our dynamic models to efficaciously predict new personalized combinatorial treatments. Our results suggest that our combination of microfluidic experiments and mathematical model can be a novel tool toward cancer precision medicine.