ArticlePloS one2016
Drug Repositioning for Cancer Therapy Based on Large-Scale Drug-Induced Transcriptional Signatures.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.
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Who cites it
44 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.
- Repurposing neurological drugs for brain cancer therapeutics: A systematic approach to identify charged molecules for affinity-based local drug delivery systems.International journal of pharmaceutics · 2025Pooled it
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- KORE-Map 1.1: Korean medicine omics resource extension map on transcriptome data of dyspepsia herbal medicine.BMC genomic data · 2026Article
- Harnessing AI to fuse phenotypic signatures for drug target identification: progress in computational modeling.Briefings in bioinformatics · 2026Review
- Long-term survival in glioblastoma patients treated with dopamine agonists: A report of two cases and implications for drug repurposing.Surgical neurology international · 2026Article
- Benchmarking of dimensionality reduction methods to capture drug response in transcriptome data.Scientific reports · 2025Article
- Incorporation and Repair of Epigenetic Intermediates as Potential Chemotherapy Agents.Molecules (Basel, Switzerland) · 2025Article
- Integrative transcriptomic analysis identifies emetine as a promising candidate for overcoming acquired resistance to ALK inhibitors in lung cancer.Molecular oncology · 2025Article
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- KORE-Map 1.0: Korean medicine Omics Resource Extension Map on transcriptome data of tonifying herbal medicine.Scientific data · 2024Article
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- Drug repositioning targeting glutaminase reveals drug candidates for the treatment of Alzheimer's disease patients.Journal of translational medicine · 2023Article
- Identification of significant gene expression changes in multiple perturbation experiments using knockoffs.Briefings in bioinformatics · 2023Article
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- Aporphine and isoquinoline derivatives block glioblastoma cell stemness and enhance temozolomide cytotoxicity.Scientific reports · 2022Article
- Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance.Bioengineering (Basel, Switzerland) · 2022Review
- Drug Repurposing to Enhance Antitumor Response to PD-1/PD-L1 Immune Checkpoint Inhibitors.Cancers · 2022Review
- Comprehensive Survey of Recent Drug Discovery Using Deep Learning.International journal of molecular sciences · 2021Review
- An Alternative Pipeline for Glioblastoma Therapeutics: A Systematic Review of Drug Repurposing in Glioblastoma.Cancers · 2021Review
- Connectivity map-based drug repositioning of bortezomib to reverse the metastatic effect of GALNT14 in lung cancer.Oncogene · 2020Article
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
An in silico chemical genomics approach is developed to predict drug repositioning (DR) candidates for three types of cancer: glioblastoma, lung cancer, and breast cancer. It is based on a recent large-scale dataset of ~20,000 drug-induced expression profiles in multiple cancer cell lines, which provides i) a global impact of transcriptional perturbation of both known targets and unknown off-targets, and ii) rich information on drug's mode-of-action. First, the drug-induced expression profile is shown more effective than other information, such as the drug structure or known target, using multiple HTS datasets as unbiased benchmarks. Particularly, the utility of our method was robustly demonstrated in identifying novel DR candidates. Second, we predicted 14 high-scoring DR candidates solely based on expression signatures. Eight of the fourteen drugs showed significant anti-proliferative activity against glioblastoma; i.e., ivermectin, trifluridine, astemizole, amlodipine, maprotiline, apomorphine, mometasone, and nortriptyline. Our DR score strongly correlated with that of cell-based experimental results; the top seven DR candidates were positive, corresponding to an approximately 20-fold enrichment compared with conventional HTS. Despite diverse original indications and known targets, the perturbed pathways of active DR candidates show five distinct patterns that form tight clusters together with one or more known cancer drugs, suggesting common transcriptome-level mechanisms of anti-proliferative activity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.