Development of farnesyl transferase inhibitors: A review

被引:225
作者
Appels, NMGM
Beijnen, JH
Schellens, JHM
机构
[1] Antoni Van Leeuwenhoek Hosp, Netherlands Canc Inst, Dept Med Oncol, NL-1066 CX Amsterdam, Netherlands
[2] Slotervaart Hosp, Netherlands Canc Inst, Dept Pharm & Pharmacol, Amsterdam, Netherlands
[3] Univ Utrecht, Div Drug Toxicol, Dept Biomed Anal, Fac Pharmaceut Sci, Utrecht, Netherlands
关键词
farnesyl transferase inhibitors; drug development; oncogenes; targeted therapy; signal transduction;
D O I
10.1634/theoncologist.10-8-565
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Farnesyl transferase inhibitors are a new class of biologically active anticancer drugs. The exact mechanism of action of this class of agents is, however, currently unknown. The drugs inhibit farnesylation of a wide range of target proteins, including Ras. It is thought that these agents block Ras activation through inhibition of the enzyme farnesyl transferase, ultimately resulting in cell growth arrest. In preclinical models, the farnesyl transferase inhibitors showed great potency against tumor cells; yet in clinical studies, their activity was far less than anticipated. Reasons for this disappointing clinical outcome might be found in the drug-development process. In this paper, we outline an algorithm that is potentially useful for the development of biologically active anticancer drugs. The development of farnesyl transferase inhibitors, from discovery to clinical trials, is reviewed on the basis of this algorithm. We found that two important steps of this algorithm were underestimated. First, understanding of the molecular biology of the defective pathway has mainly been focused on H-Ras activation, whereas activation of K-Ras or other farnesylated proteins is probably more important in tumorigenesis. Inhibition of farnesylation is possibly not sufficient, because geranylgeranylation might activate K-Ras and suppress the effect of farnesyl transferase inhibitors. Furthermore, a well-defined proof of concept in preclinical and clinical studies has not been achieved. Integrating the proposed algorithm in future studies of newly developed biologically active anticancer drugs might increase the rate of success of these compounds in patients.
引用
收藏
页码:565 / 578
页数:14
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