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Repurposing sertraline sensitizes non–small cell lung cancer cells to erlotinib by inducing autophagy
Xingwu Jiang, … , Zhongming Zhao, Xiufeng Pang
Xingwu Jiang, … , Zhongming Zhao, Xiufeng Pang
Published June 7, 2018
Citation Information: JCI Insight. 2018;3(11):e98921. https://doi.org/10.1172/jci.insight.98921.
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Research Article Oncology Therapeutics

Repurposing sertraline sensitizes non–small cell lung cancer cells to erlotinib by inducing autophagy

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Abstract

Lung cancer patients treated with tyrosine kinase inhibitors (TKIs) often develop resistance. More effective and safe therapeutic agents are urgently needed to overcome TKI resistance. Here, we propose a medical genetics–based approach to identify indications for over 1,000 US Food and Drug Administration–approved (FDA-approved) drugs with high accuracy. We identified a potentially novel indication for an approved antidepressant drug, sertraline, for the treatment of non–small cell lung cancer (NSCLC). We found that sertraline inhibits the viability of NSCLC cells and shows a synergy with erlotinib. Specifically, the cotreatment of sertraline and erlotinib effectively promotes autophagic flux in cells, as indicated by LC3-II accumulation and autolysosome formation. Mechanistic studies further reveal that dual treatment of sertraline and erlotinib reciprocally regulates the AMPK/mTOR pathway in NSCLC cells. The blockade of AMPK activation decreases the anticancer efficacy of either sertraline alone or the combination. Efficacy of this combination regimen is decreased by pharmacological inhibition of autophagy or genetic knockdown of ATG5 or Beclin 1. Importantly, our results suggest that sertraline and erlotinib combination suppress tumor growth and prolong mouse survival in an orthotopic NSCLC mouse model (P = 0.0005). In summary, our medical genetics–based approach facilitates discovery of new anticancer indications for FDA-approved drugs for the treatment of NSCLC.

Authors

Xingwu Jiang, Weiqiang Lu, Xiaoyang Shen, Quan Wang, Jing Lv, Mingyao Liu, Feixiong Cheng, Zhongming Zhao, Xiufeng Pang

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Figure 1

Diagram of medical genetics–based approach for drug repositioning.

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Diagram of medical genetics–based approach for drug repositioning.
(A) A...
(A) A comprehensive drug-gene interactions (DGIs) was set up by integrating 3 public databases: DrugBank, PharmGKB, and Therapeutic Target Database. (B) A global disease-gene associations (DGAs) model was built by collecting data from 4 well-known data sources: the OMIM, HuGE Navigator, PharmGKB, and Comparative Toxicogenomics Database. (C) A new statistical model for predicting new indications for old drugs by integrating the DGIs and the DGAs. The performance of the medical genetics–based model was evaluated using a benchmark dataset. (D) The chemical structures and the dose-response curves of sertraline and fluphenazine in 5 representative NSCLC cell lines (A549, PC9, PC9/R, H1975, and H522) harboring different genetic characteristics. Cells were treated with a series of concentrations of sertraline or fluphenazine for 72 hours. The CellTiter 96 AQueous one solution cell proliferation kit was used to determine cell viability.

Copyright © 2023 American Society for Clinical Investigation
ISSN 2379-3708

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