Author:
Giuliano Kenneth A.,Chen Yih-Tai,Taylor D. Lansing
Abstract
Deciphering the effects of compounds on molecular events within living cells is becoming an increasingly important component of drug discovery. In a model application of the industrial drug discovery process, the authors profiled a panel of 22 compounds using hierarchical cluster analysis of multiparameter high-content screening measurements from nearly 500,000 cells per microplate. RNAi protein knockdown methodology was used with high-content screening to dissect the effects of 2 anticancer drugs on multiple target activities. Camptothecin activated p53 in A549 lung carcinoma cells pretreated with scrambled siRNA, exhibited concentration-dependent cell cycle blocks, and induced moderate microtubule stabilization. Knockdown of camptothecin-induced p53 protein expression with p53 siRNA inhibited the G1/S blocking activity of the drug and diminished its microtubule-stabilizing activity. Paclitaxel activated p53 protein at low concentrations but exhibited G2/M cell cycle blocking activity at higher concentrations where microtubules were stabilized. In cells treated with p53 siRNA, paclitaxel failed to activate p53 protein, but the knockdown did not have a significant effect on the ability of paclitaxel to stabilize microtubules or induce a G2/M cell cycle block. Thus, this model application of the use of RNAi technology within the context of high-content screening shows the potential to provide massive amounts of combinatorial cell biological information on the temporal and spatial responses that cells mount to treatment by promising therapeutic candidates.
Cited by
46 articles.
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