Author Information
1Cancer Science Institute of Singapore, National University of Singapore, Singapore.
2The N.1 Institute for Health, National University of Singapore, Singapore; The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
3Cancer Science Institute of Singapore, National University of Singapore, Singapore; The N.1 Institute for Health, National University of Singapore, Singapore; The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Biomedical Engineering, National University of Singapore, Singapore. Electronic address: csikce@nus.edu.sg.
Abstract:
Deregulation of MYC is among the most frequent oncogenic drivers of cancer. Developing targeted therapies against MYC is, therefore, one of the most critical unmet needs of cancer therapy. Unfortunately, MYC has been labelled as undruggable due to the lack of success in developing clinically relevant MYC-targeted therapies. Synthetic lethality is a promising approach that targets MYC-dependent vulnerabilities in cancer. However, translating the synthetic lethality targets to the clinics is still challenging due to the complex nature of cancers. This review highlights the most promising mechanisms of MYC synthetic lethality and how these discoveries are currently translated into the clinic. Finally, we discuss how in silico computational platforms can improve clinical success of synthetic lethality-based therapy.
Keywords: MYC; cancer; computational; drug targets; synthetic lethality.
Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.
PMID: 33422376 DOI: 10.1016/j.tips.2020.11.014