Myers T G, Anderson N L, Waltham M, Li G, Buolamwini J K, Scudiero D A, Paull K D, Sausville E A, Weinstein J N
Laboratory of Molecular Pharmacology, National Cancer Institute (NCI), Bethesda, MD 20852, USA.
Electrophoresis. 1997 Mar-Apr;18(3-4):647-53. doi: 10.1002/elps.1150180351.
In the last six years, the Developmental Therapeutics Program (DTP) of the US National Cancer Institute (NCI) has screened over 60,000 chemical compounds and a larger number of natural product extracts for their ability to inhibit growth of 60 different cancer cell lines representing different organs of origin. Whereas inhibition of the growth of one cancer cell type gives no information on drug specificity, the relative growth inhibitory activities against 60 different cells constitute patterns that encode detailed information on mechanisms of action and resistance (as reviewed in Boyd and Paull, Drug Devel. Res. 1995, 34, 19-109 and Weinstein et al., Science 1997, 275, 343-349). In order to correlate the patterns of activity with properties of the cells, we and other laboratories are characterizing the cells with respect to a large number of factors at the DNA, mRNA, and protein levels. As part of that effort, we have developed a two-dimensional gel electrophoresis (2-DE) protein expression database covering all 60 cell types (Buolamwini et al., submitted). Here we present analyses of the correlations among protein spots (i) in terms of their patterns of expression and (ii) in terms of their apparent relationships to the pharmacology of a set of 3989 screened compounds. The correlations tend to be stronger for the latter than for the former, suggesting that the spots have more robust signatures in terms of the pharmacology than in terms of expression levels. Links to pertinent databases and tools of analysis will be updated progressively at http:@www.nci.nih.gov/intra/lmp/jnwbio.htm and http:@epnwsl.ncifcrf.gov:2345/dis3d/dtp.++ +html.
在过去六年中,美国国立癌症研究所(NCI)的发展治疗学项目(DTP)已筛选了60000多种化合物以及大量天然产物提取物,以检测它们抑制60种代表不同起源器官的癌细胞系生长的能力。虽然抑制一种癌细胞类型的生长并不能提供药物特异性的信息,但针对60种不同细胞的相对生长抑制活性构成了编码作用机制和耐药性详细信息的模式(如Boyd和Paull在《药物研发研究》1995年第34卷第19 - 109页以及Weinstein等人在《科学》1997年第275卷第343 - 349页中所述)。为了将活性模式与细胞特性相关联,我们实验室和其他实验室正在从DNA、mRNA和蛋白质水平的大量因素方面对细胞进行表征。作为这项工作的一部分,我们建立了一个涵盖所有60种细胞类型的二维凝胶电泳(2 - DE)蛋白质表达数据库(Buolamwini等人,已提交)。在此,我们展示了对蛋白质斑点之间相关性的分析,(i)从它们的表达模式方面,以及(ii)从它们与一组3989种筛选化合物药理学的明显关系方面。后者的相关性往往比前者更强,这表明斑点在药理学方面比在表达水平方面具有更稳健的特征。与相关数据库和分析工具的链接将在http:@www.nci.nih.gov/intra/lmp/jnwbio.htm和http:@epnwsl.ncifcrf.gov:2345/dis3d/dtp.++ +html上逐步更新。