一种对脑肿瘤有效的抗癌药物临床前筛选算法。

ISRN Pharmacology Pub Date : 2012-01-01 Epub Date: 2012-07-03 DOI:10.5402/2012/513580
Juan Sebastian Yakisich
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引用次数: 3

摘要

抗癌药物筛选程序是一个漫长而昂贵的过程。据估计,只有5%的进入临床试验的药物得到了FDA的批准。此外,许多进入临床试验的药物在临床实践中的应用往往有限,而且大多数癌症仍然无法治愈。脑肿瘤尤其难以治疗,因为血脑屏障的存在限制了抗癌药物的渗透。此外,从大多数脑肿瘤中分离出的假定的癌症干细胞和癌症干细胞生物学的新模型表明,抗癌药物应该以更长的时间和更高的浓度递送,以耗尽任何潜在的致瘤细胞。本文结合肿瘤干细胞生物学的最新概念和抗癌药物筛选的新概念,开发了一个七步算法,作为脑肿瘤治疗活性化合物临床前评估的指导方针。该算法的灵活性允许纳入替代研究,以详尽地研究抗癌药物,并为决定是否参与早期临床试验创造了多种机会,为神经肿瘤学的转化研究提供了有用的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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An Algorithm for the Preclinical Screening of Anticancer Drugs Effective against Brain Tumors.

The anticancer drugs screening program is a long and expensive process. It is estimated that only 5% of drugs entering clinical trials are approved by the FDA. Moreover, many of the drugs that enter clinical trials are often of limited use in clinical practice, and most cancers remain untreatable. Brain tumors are particularly difficult to treat due to the presence of the blood brain barrier that limits the penetration of anticancer drugs. Additionally the isolation from most brain tumors of putative cancer stem cells and novel models of cancer stem cell biology suggest that anticancer drugs should be delivered for prolonged time and at higher concentrations to deplete any potential tumorigenic cell. In this paper, current concepts of cancer stem cell biology and novel concepts of anticancer drugs screening are integrated to develop a seven-steps algorithm as a guideline for the preclinical evaluation of active compounds for the treatment of brain tumors. The flexibility of the algorithm allows the inclusion of alternative studies to exhaustively investigate anticancer drugs and creates multiple opportunities where decisions to engage or not in early clinical trials can be made providing a useful tool for translational research in neurooncology.

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