期刊
BIOMOLECULES
卷 12, 期 1, 页码 -出版社
MDPI
DOI: 10.3390/biom12010008
关键词
chemoresistance; cisplatin; lung cancer; evolutionary game theory; group behavior; persister trait; phenotypic switching
资金
- NIH [R01CA218545, R01CA247471]
- Ramanujan Fellowship [SB/S2/RJN-049/2018]
- Science and Engineering Research Board (SERB), Department of Science and Technology, Government of India
This study developed a mathematical approach based on game theory to model the response of non-small cell lung cancer cells to cisplatin treatment. The findings suggest that dynamic interactions and group behavior play a role in drug resistance, with tolerant cells displaying a 'persister-like' behavior and educating sensitive cells to evade chemotherapy. Furthermore, intermittent chemotherapy may be a better treatment strategy to reduce the emergence of tolerant cells in lung cancer.
Drug resistance, a major challenge in cancer therapy, is typically attributed to mutations and genetic heterogeneity. Emerging evidence suggests that dynamic cellular interactions and group behavior also contribute to drug resistance. However, the underlying mechanisms remain poorly understood. Here, we present a new mathematical approach with game theoretical underpinnings that we developed to model real-time growth data of non-small cell lung cancer (NSCLC) cells and discern patterns in response to treatment with cisplatin. We show that the cisplatin-sensitive and cisplatin-tolerant NSCLC cells, when co-cultured in the absence or presence of the drug, display dynamic group behavior strategies. Tolerant cells exhibit a 'persister-like' behavior and are attenuated by sensitive cells; they also appear to 'educate' sensitive cells to evade chemotherapy. Further, tolerant cells can switch phenotypes to become sensitive, especially at low cisplatin concentrations. Finally, switching treatment from continuous to an intermittent regimen can attenuate the emergence of tolerant cells, suggesting that intermittent chemotherapy may improve outcomes in lung cancer.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据