Biology subjects

Kong, H.-J.

Publications and source records attributed to Kong, H.-J..

2 recordsLinked to original sources

bioRxiv2020

Systematic identification of a nuclear receptor-enriched predictive signature for erastin-induced ferroptosis

Erastin, which has been initially identified as a synthetic lethal compound against cancer expressing an RAS oncogene, inhibits cystine/glutamate antiporters and causes ferroptic cell death in various cell types, including therapy-resistant mesenchymal cancer cells. However, despite recent emerging evidence for the mechanisms underlying ferroptosis, molecular biomarkers associated with erastin-dependent ferroptosis have not yet been identified. In the present study, we employed isogenic lung cancer cell models with therapy-resistant mesenchymal properties to show that a redox imbalance leads to glutathione depletion and ferroptotic cell death. Subsequent gene expression analysis of pan-cancer cell lines revealed that the activity of transcription factors, including nuclear factor erythroid 2-related factor 2 (NRF2) and aryl hydrocarbon receptor (AhR), serve as important markers of erastin resistance. Based on the integrated expression of genes in the nuclear receptor meta-pathway (NRM), we constructed an NRM model and validated its robustness using an independent pharmacogenomics dataset. The NRM model was further evaluated by employing it in the sensitivity testing of nine cancer cell lines for which erastin sensitivities had not yet been undetermined. Our pharmacogenomics approach has the potential to pave the way for the efficient classification of patients for therapeutic intervention using erastin or erastin analogs.

systems biology↗

bioRxiv2018

In silico Drug Repositioning of bortezomib to reverse metastatic effect of GALNT14 in lung cancer

Although many molecular targets for cancer therapy have been discovered, they often show poor druggability, which is a major obstacle to develop targeted drugs. As an alternative route to drug discovery, we adopted an in silico drug repositioning (in silico DR) approach based on large-scale gene expression signatures, with the goal of identifying inhibitors of lung cancer metastasis. Our analysis of clinicogenomic data identified GALNT14, an enzyme involved in O-linked N-acetyl galactosamine glycosylation, as a putative driver of lung cancer metastasis leading to poor survival. To overcome the poor druggability of GALNT14, we leveraged Connectivity Map approach, an in silico screening for drugs that are likely to revert the metastatic expression patterns. It leads to identification of bortezomib (BTZ) as a potent metastatic inhibitor, bypassing direct inhibition of poorly druggable target, GALNT14. The anti-metastatic effect of BTZ was verified in vitro and in vivo. Notably, both BTZ treatment and GALNT14 knockdown attenuated TGF{beta}-mediated gene expression and suppressed TGF{beta}-dependent metastatic genes, suggesting that BTZ acts by modulating TGF{beta} signalingTaken together, these results demonstrate that our in silico DR approach is a viable strategy to identify a candidate drug for undruggable targets, and to uncover its underlying mechanisms.

cancer biology↗