ArticleBriefings in bioinformatics2023
Validation of transcriptome signature reversion for drug repurposing in oncology.
Article in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Reviewing the Computational Landscape of Drug Repurposing: Evolution from Structure-Based Methods to LLM-Based Methods.Biomolecules · 2026Review
- Review
- Drug Repositioning for HPV Clade-Specific Cervicouterine Cancer Using the OCTAD Pipeline.International journal of molecular sciences · 2025Article
- Systematic identification of cancer pathways and potential drugs for intervention through multi-omics analysis.The pharmacogenomics journal · 2025Article
- Genomic strategies for drug repurposing.Journal of the Egyptian National Cancer Institute · 2024Review
- Atorvastatin lowers breast cancer risk by reversing an early tumorigenic signature.Scientific reports · 2024Article
- A review of computational methods for predicting cancer drug response at the single-cell level through integration with bulk RNAseq data.Current opinion in structural biology · 2024Review
- Application of perturbation gene expression profiles in drug discovery-From mechanism of action to quantitative modelling.Frontiers in systems biology · 2023Review
- Applying a Gene Reversal Rate Computational Methodology to Identify Drugs for a Rare Cancer: Inflammatory Breast Cancer.Cancer informatics · 2023Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transcriptome signature reversion (TSR) has been extensively proposed and used to discover new indications for existing drugs (i.e. drug repositioning, drug repurposing) for various cancer types. TSR relies on the assumption that a drug that can revert gene expression changes induced by a disease back to original, i.e. healthy, levels is likely to be therapeutically active in treating the disease. Here, we aimed to validate the concept of TSR using the PRISM repurposing data set, which is-as of writing-the largest pharmacogenomic data set. The predictive utility of the TSR approach as it has currently been used appears to be much lower than previously reported and is completely nullified after the drug gene expression signatures are adjusted for the general anti-proliferative downstream effects of drug-induced decreased cell viability. Therefore, TSR mainly relies on generic anti-proliferative drug effects rather than on targeting cancer pathways specifically upregulated in tumor types.
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Registered trials
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