返回主站|会员中心|保存桌面|手机浏览
108

苏州佰通生物科技有限公司

生物技术的研发及技术咨询服务;销售:非危险化工产品、化妆品。

新闻分类
  • 暂无分类
站内搜索
 
荣誉资质
友情链接
您当前的位置:首页 » 新闻中心 » PLoS Comput Biol:抑制肺癌患者对药物产生耐受性的新策略
新闻中心
PLoS Comput Biol:抑制肺癌患者对药物产生耐受性的新策略
发布时间:2016-08-29        浏览次数:190        返回列表
  

图片来自:news.liv.ac.uk

近日,一项刊登于国际杂志PLoS Computational Biology上的研究报告中,研究者通过研究发现,正确的治疗用药,比如缺氧激活前体药物(HAPs)或可帮助抑制特定类型肺癌患者出现的药物耐受性。

HAPs可以通过在肿瘤的低氧斑块下杀灭癌细胞来发挥作用,而标准的药物很难渗入到肿瘤的低氧斑块中;然而在临床试验中HAPs对患者并没有表现出明显的效益,本文研究中来自明尼苏达大学和南加利福尼亚大学的研究者就开始进行研究调查如何使HAPs变得更加有效。

研究者建立了一种数学模型来监控携带EGFR基因突变的非小细胞肺癌(NSCLC)患者机体药物耐受性的产生情况,大多数携带此类亚型癌症的患者都会在埃罗替尼标准药物疗法后的12至18个月产生药物耐受性。研究者利用这种模型探索了药物埃罗替尼和名为evofosfamide的HAP的多种可能性组合,同时研究者还检测了广谱的药物剂量和疗法计划来观察到底哪种组合可以成功抑制肿瘤细胞出现埃罗替尼耐受性。

在所有的组合中,一种最有效的模式就是药物埃罗替尼和evofosfamide轮流治疗,其可以尽量减少每次evofosfamide剂量和下一次埃罗替尼的作用时间,而相比目前使用的疗法而言,这种新型组合疗法也可以更好地抑制肿瘤细胞对埃罗替尼的耐受性。研究者Jasmine Foo说道,利用缺氧激活前体药物,如果可以和当前的标准疗法进行精确组合,那么或许可以更加有利于消除非小细胞肺癌患者机体的肿瘤细胞。

尽管本文研究发现阐明了一种由EGFR驱动的非小细胞肺癌的最佳治疗体系,即药物埃罗替尼和evofosfamide的组合,但研究者认为,在这种组合性疗法用于临床患者试验之前还应当进行大量的临床前试验来证实其效力。

 

Leveraging Hypoxia-Activated Prodrugs to Prevent Drug Resistance in Solid Tumors.

Lindsay D1, Garvey CM2, Mumenthaler SM2, Foo J1.

 

Experimental studies have shown that one key factor in driving the emergence of drug resistance in solid tumors is tumor hypoxia, which leads to the formation of localized environmental niches where drug-resistant cell populations can evolve and survive. Hypoxia-activated prodrugs (HAPs) are compounds designed to penetrate to hypoxic regions of a tumor and release cytotoxic or cytostatic agents; several of these HAPs are currently in clinical trial. However, preliminary results have not shown a survival benefit in several of these trials. We hypothesize that the efficacy of treatments involving these prodrugs depends heavily on identifying the correct treatment schedule, and that mathematical modeling can be used to help design potential therapeutic strategies combining HAPs with standard therapies to achieve long-term tumor control or eradication. We develop this framework in the specific context of EGFR-driven non-small cell lung cancer, which is commonly treated with the tyrosine kinase inhibitor erlotinib. We develop a stochastic mathematical model, parametrized using clinical and experimental data, to explore a spectrum of treatment regimens combining a HAP, evofosfamide, with erlotinib. We design combination toxicity constraint models and optimize treatment strategies over the space of tolerated schedules to identify specific combination schedules that lead to optimal tumor control. We find that (i) combining these therapies delays resistance longer than any monotherapy schedule with either evofosfamide or erlotinib alone, (ii) sequentially alternating single doses of each drug leads to minimal tumor burden and maximal reduction in probability of developing resistance, and (iii) strategies minimizing the length of time after an evofosfamide dose and before erlotinib confer further benefits in reduction of tumor burden. These results provide insights into how hypoxia-activated prodrugs may be used to enhance therapeutic effectiveness in the clinic.