Department of Systems Biology and Engineering, Silesian University of Technology, 44100 Gliwie, Poland.
Int J Mol Sci. 2023 Oct 31;24(21):15801. doi: 10.3390/ijms242115801.
Drug resistance is a bottleneck in cancer treatment. Commonly, a molecular treatment for cancer leads to the emergence of drug resistance in the long term. Thus, some drugs, despite their initial excellent response, are withdrawn from the market. Lung cancer is one of the most mutated cancers, leading to dozens of targeted therapeutics available against it. Here, we have developed a mechanistic mathematical model describing sensitization to nine groups of targeted therapeutics and the emergence of intrinsic drug resistance. As we focus only on intrinsic drug resistance, we perform the computer simulations of the model only until clinical diagnosis. We have utilized, for model calibration, the whole-exome sequencing data combined with clinical information from over 1000 non-small-cell lung cancer patients. Next, the model has been applied to find an answer to the following questions: When does intrinsic drug resistance emerge? And how long does it take for early-stage lung cancer to grow to an advanced stage? The results show that drug resistance is inevitable at diagnosis but not always detectable and that the time interval between early and advanced-stage tumors depends on the selection advantage of cancer cells.
耐药性是癌症治疗的一个瓶颈。通常，癌症的分子治疗会导致长期出现耐药性。因此，一些药物尽管最初反应良好，但还是被撤出了市场。肺癌是突变最多的癌症之一，针对它已经有几十种靶向治疗药物。在这里，我们开发了一个描述对九组靶向治疗药物的敏感性和内在耐药性出现的机制数学模型。由于我们只关注内在耐药性，因此我们仅在临床诊断之前对模型进行计算机模拟。我们利用全外显子组测序数据并结合来自 1000 多名非小细胞肺癌患者的临床信息对模型进行了校准。接下来，该模型被用于回答以下问题：内在耐药性何时出现？早期肺癌需要多长时间发展到晚期？结果表明，耐药性在诊断时是不可避免的，但并非总是可检测到的，早期和晚期肿瘤之间的时间间隔取决于癌细胞的选择优势。
