Even when targets responsible for chemoresistance are identified, drug development is often hampered due to the poor druggability of these proteins. We systematically analyzed therapy-resistance with a large-scale cancer cell transcriptome and drug-response datasets and predicted the candidate drugs based on the gene expression profile. Our results implicated the epithelial-mesenchymal transition as a common mechanism underlying resistance to chemotherapeutic drugs. Notably, we identified ITGB3, whose expression was abundant in both drug resistance and mesenchymal status, as a promising target to overcome chemoresistance. We also confirmed that depletion of ITGB3 sensitized cancer cells to conventional chemotherapeutic drugs by modulating the NF-κB signaling pathway. Considering the poor druggability of ITGB3 and the lack of feasible drugs to directly inhibit this protein, we took an in silico screening for drugs mimicking the transcriptome-level changes caused by knockdown of ITGB3. This approach successfully identified atorvastatin as a novel candidate for drug repurposing, paving an alternative path to drug screening that is applicable to undruggable targets.
Bibliographical noteFunding Information:
This work was supported by a grant from the National Research Foundation of Korea (NRF-2017M3C9A5028691 from HJC, NRF-2017M3C9A5028690 from WKK and NRF-2017R1A6A3A11030794 from HSL).
© 2018 The Author(s).
All Science Journal Classification (ASJC) codes
- Molecular Medicine
- Cancer Research