Large-scale pharmacogenomics based drug discovery for ITGB3 dependent chemoresistance in mesenchymal lung cancer
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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.
KeywordsChemoresistance Mesenchymal cancer Pharmacogenomics Drug repurposing Biomarker ITGB3 NF-κB Atorvastatin Systems pharmacology
Area under fitted curve
Cancer Cell Line Encyclopedia
Connective Tissue Growth Factor
Cancer Therapeutics Response Portal
Differentially expressed gene
Genomics Data Common
Genomics of Drug Sensitivity in Cancer
Integrin beta 3
Recent studies in both in vitro cell and in vivo animal models demonstrated that the epithelial-mesenchymal transition (EMT), a major cause of metastasis, is closely associated with chemoresistance . These are consistent with the reports that cancer patients with mesenchymal gene signatures have poor prognoses or exhibit therapy resistance . However, due to the poor druggability of the EMT-associated proteins responsible for chemoresistance (e.g., ZEB1/2, SNAI2, SOX4, etc.), it is important to develop alternative strategies to make ‘undruggable but attractive targets’ druggable.
Among the down-regulated pathways by ITGB3 depletion, NF-κB was the signaling pathways most strongly associated with patients’ survival (Fig. 2e). Given that depletion of ITGB3 down-regulated NF-κB-dependent survival factors (IL8, XIAP, PLAU, BIRC2/3, BCL2, or BCL2L1), and induced negative feedback regulators such as NFKBIA and TNFAIP3 (encoding IκBα and A20 deubiquitinase, respectively), we hypothesized that inhibition of NF-κB signaling would be a key process required for cell sensitization (Fig. 2f and Additional file 1: Figure S3A). Consistently, highly chemoresistant TD cells exhibited higher levels of NF-κB activity than A549 cells, as determined by nuclear p65 localization (Fig. 2g and Additional file 1: Figure S3B), the protein level of IκBα (Additional file 1: Figure S3C) and NF-κB reporter activity (Additional file 1: Figure S3D). Furthermore, loss of ITGB3 markedly attenuated NF-κB activity, as determined by NF-κB reporter activity (Fig. 2h) and acetylation of p65 (which is critical for its DNA-binding affinity) (Fig. 2i) as well as the level of nuclear p65 (Additional file 1: Figure S3E–F). In adverse, ectopic expression of ITGB3 restored NF-κB activity, as determined by acetylation of p65 and level of IκB (Additional file 1: Figure S3G). Together, these data indicate that ITGB3 expression is closely associated with NF-κB activity. According to this prediction that elevation of NF-κB activity by ITGB3 expression could be a primary cause of the elevated hazard ratio (Fig. 2e), we assessed the cytotoxicity of doxorubicin following abrogation of NF-κB activity. Depletion of p65 with siRNA, was sufficient to sensitize cells to doxorubicin treatment (Fig. 2j), suggesting that the increase in NF-κB activity mediated by ITGB3 expression is responsible for acquisition of chemoresistance.
Most targets responsible for acquired chemoresistance in cancers, identified during extensive molecular mechanistic studies, remain undrugged  due to poor druggability or possible side effects by direct inhibition. Thus, we took advantage of CMap approach based on a large-scale drug-induced transcriptome dataset and identified ATV, one of the world’s best-selling drugs for hyperlipidemia, as a candidate drug for abrogating the pro-survival and chemoresistance effect of ITGB3; specifically, we showed that the transcriptional profile of ATV-treated cells was similar to that of ITGB3 knockdown. Consistently, ATV has a radiosensitizing effect on prostate cancer cells . Although the inhibitory effect of STATINs on NF-κB is varied markedly , our predictive analysis identified ATV as a top-ranking candidate, strongly validating our data-driven approach.
By integrating pharmacogenomics and chemical genomic data, we successfully identified both a therapeutic target and a novel chemosensitizing drug to overcome resistance to multiple chemotherapeutic drugs. Our approach can be applied to a wide range of targets beyond those associated with EMT, paving an alternative path to drug discovery even for undruggable targets.
We appreciate Seon-Young Kim and Dong-Uk Kim at Korea Research Institute of Bioscience and Biotechnology (KRIBB) for helpful discussions.
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).
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
HJC and WK conceived the overall study design and led the experiments. SKH, HL, OSK, NYS, HJL, SK, JHK and MK conducted the experiments, data analysis, and critical discussion of the results. All authors contributed to manuscript writing and revising, endorsed and approved the final manuscript.
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The authors declare that they have no competing interests.
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