Mathematical Modeling of Drug Resistance Evolution and The Optimal Treatment Strategy in EGFR Mutated Lung Cancer

EGFR突变肺癌耐药演化的数学模型及最佳治疗策略

• 批准号: 22KJ0768
• 负责人: Yu Qian
• 金额: $ 1.09万
• 依托单位: The University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for JSPS Fellows
• 财政年份: 2023
• 资助国家: 日本
• 起止时间: 2023-03-08 至 2024-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-22KJ0768/
• 关键词: EGFR; mathematical modeling; T790M; EGFR-TKIs

In 2022, I followed my research plan and made some progress. My research is about using a mathematical model to simulate tumor progression in different therapies and predict the optimal treatment strategies for patients. Firstly, in order to get the data for model simulation, I established two types of EGFR mutation cells and co-culture them. In this experiment, I observed that drug-sensitive cells survived in drugs even with only 10% existence of drug-resistant cells. Also, this kind of co-culture response is different from different drugs, we may explore the mechanism of this phenomenon in the future. Secondly, I simulated the time course of tumor progression in different therapy strategies and analyzed the influence effect of drug-resistance cells on drug-sensitive cells through computational simulation. In this theoretical analysis, results indicated that although all-drug-resistant cells are expected to be the strongest support for helping all-drug-sensitive cells to survive because they resistant all therapy drugs, but actually it does not. Out of expectation, secondary mutation cells, which are one-drug-resistant cells, help the survivor of all-drug-sensitive cells more than all-drug-resistant cells. This might because the growth of all-drug-resistant cells is slower compared with one-drug-resistant cells in the corresponding drugs, which means all-drug-resistant cells may spend more “effort” in “self-survivor”. We would like to research its mechanism in the future, too.

2022年，我按照我的研究计划取得了一些进展，我的研究是用数学模型来模拟不同疗法中的肿瘤进展，并预测患者的最佳治疗策略，首先，为了获得模型模拟的数据。我建立了两种类型的EGFR突变细胞并将它们共培养，在这个实验中，我观察到即使只有10%的耐药细胞存在，药物敏感细胞仍能存活，而且这种共培养反应是不同的。从不同的药物中，我们可以探索其次，我模拟了不同治疗策略下肿瘤进展的时间过程，并通过计算模拟分析了耐药细胞对药物敏感细胞的影响作用。全耐药细胞被期望成为帮助全药物敏感细胞生存的最有力支持，因为它们对所有治疗药物都有抵抗力，但实际上却并非如此，二次突变细胞，即一种药物——抵抗细胞，帮助幸存者全耐药细胞比全耐药细胞多，这可能是因为全耐药细胞的生长速度比相应药物中的单一耐药细胞慢，这意味着全耐药细胞。未来我们也想在“自我生存”上花更多的“功夫”来研究它的机制。