ArticleScientific reports2019
Computational Drug Repositioning for Gastric Cancer using Reversal Gene Expression Profiles.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 33 citations in OpenAlex.
- Circ_0004592: An auxiliary diagnostic biomarker for gastric cancer.World journal of gastrointestinal oncology · 2024Article
- Relationship between drug targets and drug-signature networks: a network-based genome-wide landscape.BMC medical genomics · 2023Article
- Validation of transcriptome signature reversion for drug repurposing in oncology.Briefings in bioinformatics · 2023Article
- A novel method for drug-target interaction prediction based on graph transformers model.BMC bioinformatics · 2022Article
- PLOD3 regulates the expression of YAP1 to affect the progression of non-small cell lung cancer via the PKCδ/CDK1/LIMD1 signaling pathway.Laboratory investigation; a journal of technical methods and pathology · 2022Article
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- Identification of Nifurtimox and Chrysin as Anti-Influenza Virus Agents by Clinical Transcriptome Signature Reversion.International journal of molecular sciences · 2022Article
- Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer.NAR genomics and bioinformatics · 2021Article
- Identification of new target proteins of a Urotensin-II receptor antagonist using transcriptome-based drug repositioning approach.Scientific reports · 2021Article
- DDIT: An Online Predictor for Multiple Clinical Phenotypic Drug-Disease Associations.Frontiers in pharmacology · 2021Article
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- Universal Nature of Drug Treatment Responses in Drug-Tissue-Wide Model-Animal Experiments Using Tensor Decomposition-Based Unsupervised Feature Extraction.Frontiers in genetics · 2020Article
- Predicting associations among drugs, targets and diseases by tensor decomposition for drug repositioning.BMC bioinformatics · 2019Article
- Transcriptome-Guided Drug Repositioning.Pharmaceutics · 2019Article
- A multiparametric pharmacogenomic strategy for drug repositioning predicts therapeutic efficacy for glioblastoma cell lines.Neuro-oncology advancesArticle
Corrections and comments
- Retraction · 2022-06-13Concerns/Issues about Referencing/Attributions ·
- Retracted
Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Treatment of gastric cancer (GC) often produces poor outcomes. Moreover, predicting which GC treatments will be effective remains challenging. Computational drug repositioning using public databases is a promising and efficient tool for discovering new uses for existing drugs. Here we used a computational reversal of gene expression approach based on effects on gene expression signatures by GC disease and drugs to explore new GC drug candidates. Gene expression profiles for individual GC tumoral and normal gastric tissue samples were downloaded from the Gene Expression Omnibus (GEO) and differentially expressed genes (DEGs) in GC were determined with a meta-signature analysis. Profiles drug activity and drug-induced gene expression were downloaded from the ChEMBL and the LINCS databases, respectively. Candidate drugs to treat GC were predicted using reversal gene expression score (RGES). Drug candidates including sorafenib, olaparib, elesclomol, tanespimycin, selumetinib, and ponatinib were predicted to be active for treatment of GC. Meanwhile, GC-related genes such as PLOD3, COL4A1, UBE2C, MIF, and PRPF5 were identified as having gene expression profiles that can be reversed by drugs. These findings support the use of a computational reversal gene expression approach to identify new drug candidates that can be used to treat GC.
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