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

2022年，我遵循了我的研究计划，取得了一些进展。我的研究是关于使用一个数学模型来模拟不同疗法下的肿瘤进展，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，建立了两种类型的EGFR突变细胞，并对其进行了共培养。在这项实验中，我观察到，即使只有10%的耐药细胞存在，药物敏感细胞也能在药物中存活。此外，这种共培养反应不同于不同的药物，我们可能会在未来探索这种现象的机制。其次，模拟了不同治疗策略下肿瘤进展的时间进程，并通过计算机模拟分析了耐药细胞对药物敏感细胞的影响。在这一理论分析中，结果表明，尽管所有耐药细胞有望成为帮助所有药物敏感细胞存活的最有力支撑，因为它们对所有治疗药物都具有耐药性，但实际上并非如此。出乎意料的是，二次突变细胞，即一种耐药细胞，比起所有耐药细胞，更有助于ALL敏感细胞的生存。这可能是因为与相应药物中的一种耐药细胞相比，所有耐药细胞的生长速度都较慢，这意味着所有耐药细胞可能会花更多的时间来进行“自我生存”。我们也想在未来研究它的机制。

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.