Lestaurtinib

Many diseases emerge from dysregulated cellular signaling, and drugs are often designed to target specific signaling proteins. Off-target effects are, however, common and may ultimately result in failed clinical trials. Here we develop a computer model of the cell's transcriptional response to drugs for improved understanding of their mechanisms of action. The model is based on ensembles of artificial neural networks and simultaneously infers drug-target interactions and their downstream effects on intracellular signaling. With this, it predicts transcription factors' activities, while recovering known drug-target interactions and inferring many new ones, which we validate with an independent dataset. As a case study, we analyze the effects of the drug Lestaurtinib on downstream signaling. Alongside its intended target, FLT3, the model predicts an inhibition of CDK2 that enhances the downregulation of the cell cycle-critical transcription factor FOXM1. Our approach can therefore enhance our understanding of drug signaling for therapeutic design.

Yingxiao Cao, Shiqi Kong, Yuling Xin, Yan Meng, Shuling Shang, Yanhui Qi. Lestaurtinib potentiates TRAIL‐induced apoptosis in glioma via CHOP‐dependent DR5 induction. J Cell Mol Med. 2020; 24: 7829–7840. https://doi-org.libproxy1.nus.edu.sg/10.1111/jcmm.15415.The above article, published online on 22 May 2020 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the authors, the journal Editor‐in‐Chief, Stefan Constantinescu, The Foundation for Cellular and Molecular Medicine, and John Wiley and Sons Ltd. The retraction has been agreed upon following an investigation into concerns raised by a third party, which revealed inappropriate duplications of images between this and other articles that were either previously published or published later in the same year in a different scientific context. Thus, the editors consider the conclusions of this manuscript substantially compromised.