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Quantifying the Propagation of Resistance to Chemotherapy in Cancer

量化癌症化疗耐药性的传播

基本信息

批准号：
1713109
负责人：
Doron Levy
金额：
$ 25万
依托单位：
University of Maryland, College Park
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-01 至 2021-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1713109&HistoricalAwards=false
关键词：
Quantifying Propagation Resistance Chemotherapy Cancer

项目摘要

Drug resistance represents a major obstacle to improving the overall response and survival of cancer patients. While most tumors initially respond well to drug therapies, the majority will relapse at a certain point following treatment. Therapeutic failure may be attributed to intrinsic tumor heterogeneity prior to therapy or induced tumor heterogeneity after initiation of therapy. This project aims at developing mathematical models for studying the emergence and the spatial and temporal propagation of single or multidrug resistance under drug-specific treatment protocols. The tools developed in this project will provide a foundation for designing personalized therapy that can be adjusted based on the dynamics of the resistance to chemotherapy. The project involves training of graduate students as well as curriculum and outreach initiatives.The PI will focus on developing, simulating, and analyzing new mathematical models for describing the dynamics of drug resistance in cancer, as mediated by intratumoral heterogeneity. Biologically-based mathematical models will include: hybrid discrete-continuous models, integro-differential equations, stochastic models, and partial-differential equations. The project opens new research opportunities that are guided by PI's established collaborations with clinicians and experimentalists. The focus of this funded project is on the mathematical aspects of the study. A successful completion of this project will provide us with a wide range of mathematical approaches for future translational research in experimental and clinical studies.

耐药性是改善癌症患者总体反应和生存的主要障碍。虽然大多数肿瘤最初对药物治疗反应良好，但大多数会在治疗后的某个时间点复发。治疗失败可能归因于治疗前固有的肿瘤异质性或治疗开始后诱导的肿瘤异质性。该项目旨在开发数学模型，用于研究特定药物治疗方案下单药或多药耐药性的出现以及时空传播。该项目开发的工具将为设计个性化治疗奠定基础，可以根据化疗耐药的动态进行调整。该项目涉及研究生培训以及课程和推广计划。PI 将专注于开发、模拟和分析新的数学模型，用于描述由肿瘤内异质性介导的癌症耐药性动态。基于生物学的数学模型将包括：混合离散连续模型、积分微分方程、随机模型和偏微分方程。该项目开辟了新的研究机会，这些机会以 PI 与临床医生和实验人员建立的合作为指导。该资助项目的重点是研究的数学方面。该项目的成功完成将为我们未来实验和临床研究的转化研究提供广泛的数学方法。