A genome-wide positioning systems network algorithm for in silico drug repurposing.
Feixiong ChengWeiqiang LuChuang LiuJiansong FangYuan HouDiane E HandyRuisheng WangYuzheng ZhaoYi YangJin HuangDavid E HillMarc VidalCharis EngJoseph LoscalzoPublished in: Nature communications (2019)
Recent advances in DNA/RNA sequencing have made it possible to identify new targets rapidly and to repurpose approved drugs for treating heterogeneous diseases by the 'precise' targeting of individualized disease modules. In this study, we develop a Genome-wide Positioning Systems network (GPSnet) algorithm for drug repurposing by specifically targeting disease modules derived from individual patient's DNA and RNA sequencing profiles mapped to the human protein-protein interactome network. We investigate whole-exome sequencing and transcriptome profiles from ~5,000 patients across 15 cancer types from The Cancer Genome Atlas. We show that GPSnet-predicted disease modules can predict drug responses and prioritize new indications for 140 approved drugs. Importantly, we experimentally validate that an approved cardiac arrhythmia and heart failure drug, ouabain, shows potential antitumor activities in lung adenocarcinoma by uniquely targeting a HIF1α/LEO1-mediated cell metabolism pathway. In summary, GPSnet offers a network-based, in silico drug repurposing framework for more efficacious therapeutic selections.
Keyphrases
- genome wide
- single cell
- heart failure
- dna methylation
- protein protein
- machine learning
- network analysis
- end stage renal disease
- adverse drug
- rna seq
- cancer therapy
- single molecule
- molecular docking
- ejection fraction
- left ventricular
- newly diagnosed
- deep learning
- circulating tumor
- squamous cell carcinoma
- peritoneal dialysis
- drug delivery
- climate change
- bone marrow
- molecular dynamics simulations
- pluripotent stem cells
- catheter ablation