ArticleMolecules (Basel, Switzerland)2020
The Performance of Gene Expression Signature-Guided Drug-Disease Association in Different Categories of Drugs and Diseases.
Article in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 14 citations in OpenAlex.
- Review
- Integration of Pan-Cancer Cell Line and Single-Cell Transcriptomic Profiles Enables Inference of Therapeutic Vulnerabilities in Heterogeneous Tumors.Cancer research · 2024Article
- Inferring therapeutic vulnerability within tumors through integration of pan-cancer cell line and single-cell transcriptomic profiles.bioRxiv : the preprint server for biology · 2023Article
- Combination of antidepressants and antipsychotics as a novel treatment option for psychosis in Alzheimer's disease.CPT: pharmacometrics & systems pharmacology · 2023Article
- Targeting the post-synaptic proteome has therapeutic potential for psychosis in Alzheimer Disease.Communications biology · 2023Article
- Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics.Molecules (Basel, Switzerland) · 2021Article
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
A gene expression signature (GES) is a group of genes that shows a unique expression profile as a result of perturbations by drugs, genetic modification or diseases on the transcriptional machinery. The comparisons between GES profiles have been used to investigate the relationships between drugs, their targets and diseases with quite a few successful cases reported. Especially in the study of GES-guided drugs-disease associations, researchers believe that if a GES induced by a drug is opposite to a GES induced by a disease, the drug may have potential as a treatment of that disease. In this study, we data-mined the crowd extracted expression of differential signatures (CREEDS) database to evaluate the similarity between GES profiles from drugs and their indicated diseases. Our study aims to explore the application domains of GES-guided drug-disease associations through the analysis of the similarity of GES profiles on known pairs of drug-disease associations, thereby identifying subgroups of drugs/diseases that are suitable for GES-guided drug repositioning approaches. Our results supported our hypothesis that the GES-guided drug-disease association method is better suited for some subgroups or pathways such as drugs and diseases associated with the immune system, diseases of the nervous system, non-chemotherapy drugs or the mTOR signaling pathway.
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