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.
Highlights
Recent advances in scientific, technological, and managerial efforts have been made to improve efficiency of drug discovery and development
All drugs were grouped using the Anatomical Therapeutic Chemical Classification System codes, which were downloaded from DrugBnak database (v3.0; ref. 23), and were further annotated using the Medical Subject Headings (MeSH) and unified medical language system (UMLS) vocabularies [27]
We examined whether the elevated autophagic flux contributed to the impaired growth of EGFR tyrosine kinase inhibitors (TKIs)–resistant non–small cell lung cancer (NSCLC) cells triggered by the sertraline-containing treatments
Summary
Technological, and managerial efforts have been made to improve efficiency of drug discovery and development. The number of new the US Food and Drug Administration– approved (FDA-approved) drugs has decreased since 1950, and costs in drug discovery process has largely increased [1]. Scientists in both academic and industrial fields have been seeking innovative technologies and approaches to decrease costs and augment efficiency in drug discovery. A potentially novel drug development technology, namely drug repurposing that screens existing drugs for new uses, draws great attention and delivers productivity [2,3,4]. Developing innovative strategies with low costs and high efficiency, such as computational approaches, is urgently needed
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