ArticleJournal of biomedical informatics2016
Drug repurposing for glioblastoma based on molecular subtypes.
Article in Journal of biomedical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed.
- Drug repurposing in cancer research: a bibliometric analysis.Discover oncology · 2025Article
- Modeling glioblastoma complexity with organoids for personalized treatments.Trends in molecular medicine · 2023Review
- Network-based drug repurposing for HPV-associated cervical cancer.Computational and structural biotechnology journal · 2023Article
- A combination of metformin and epigallocatechin gallate potentiates glioma chemotherapyFrontiers in pharmacology · 2023Article
- Article
- Adapt to Persist: Glioblastoma Microenvironment and Epigenetic Regulation on Cell Plasticity.Biology · 2022Review
- An Alternative Pipeline for Glioblastoma Therapeutics: A Systematic Review of Drug Repurposing in Glioblastoma.Cancers · 2021Review
- Multifaceted microglia - key players in primary brain tumour heterogeneity.Nature reviews. Neurology · 2021Review
- Drug perturbation gene set enrichment analysis (dpGSEA): a new transcriptomic drug screening approach.BMC bioinformatics · 2021Article
- PBX2-Mediated circTLK1 Activates JAK/STAT Signaling to Promote Gliomagenesis via miR-452-5p/SSR1 Axis.Frontiers in genetics · 2021Article
- Mechanistic models of signaling pathways deconvolute the glioblastoma single-cell functional landscape.NAR cancer · 2020Article
- Current Opinion on Molecular Characterization for GBM Classification in Guiding Clinical Diagnosis, Prognosis, and Therapy.Frontiers in molecular biosciences · 2020Review
- Context-sensitive network analysis identifies food metabolites associated with Alzheimer's disease: an exploratory study.BMC medical genomics · 2019Article
- MUDENG Expression Profiling in Cohorts and Brain Tumor Biospecimens to Evaluate Its Role in Cancer.Frontiers in genetics · 2019Article
- A systems biology approach to predict and characterize human gut microbial metabolites in colorectal cancer.Scientific reports · 2018Article
- Using a novel computational drug-repositioning approach (DrugPredict) to rapidly identify potent drug candidates for cancer treatment.Oncogene · 2018Article
- Retrospective analysis of health claims to evaluate pharmacotherapies with potential for repurposing: Association of bupropion and stimulant use disorder remission.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- Interrogating Patient-level Genomics and Mouse Phenomics towards Understanding Cytokines in Colorectal Cancer Metastasis.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2017Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
A recent multi-platform analysis by The Cancer Genome Atlas identified four distinct molecular subtypes for glioblastoma (GBM) and demonstrated that the subtypes correlate with clinical phenotypes and treatment responses. In this study, we developed a computational drug repurposing approach to predict GBM drugs based on the molecular subtypes. Our approach leverages the genomic signature for each GBM subtype, and integrates the human cancer genomics with mouse phenotype data to identify the opportunity of reusing the FDA-approved agents to treat specific GBM subtypes. Specifically, we first constructed the phenotype profile for each GBM subtype using their genomic signatures. For each approved drug, we also constructed a phenotype profile using the drug target genes. Then we developed an algorithm to match and prioritize drugs based on their phenotypic similarities to the GBM subtypes. Our approach is highly generalizable for other disorders if provided with a list of disorder-specific genes. We first evaluated the approach in predicting drugs for the whole GBM. For a combined set of approved, potential and off-label GBM drugs, we achieved a median rank of 9.3%, which is significantly higher (p<e
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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.