ArticlePloS one2018
New drug candidates for treatment of atypical meningiomas: An integrated approach using gene expression signatures for drug repurposing.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
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- Use of Drug Sensitisers to Improve Therapeutic Index in Cancer.Pharmaceutics · 2024Review
- Ensemble deep learning enhanced with self-attention for predicting immunotherapeutic responses to cancers.Frontiers in immunology · 2022Article
- Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer.NAR genomics and bioinformatics · 2021Article
- Evaluation of connectivity map shows limited reproducibility in drug repositioning.Scientific reports · 2021Article
- Identification of Novel Drug Candidate for Epithelial Ovarian CancerFrontiers in oncology · 2021Article
- Machine and deep learning approaches for cancer drug repurposing.Seminars in cancer biology · 2021Review
- Integrating Differential Gene Expression Analysis with Perturbagen-Response Signatures May Identify Novel Therapies for Thyroid-Associated Orbitopathy.Translational vision science & technology · 2020Article
- Cellular Stress-Modulating Drugs Can Potentially Be Identified by in Silico Screening with Connectivity Map (CMap).International journal of molecular sciences · 2019Review
- Drug repurposing: a promising tool to accelerate the drug discovery process.Drug discovery today · 2019Review
- Influence of batch effect correction methods on drug induced differential gene expression profiles.BMC bioinformatics · 2019Article
- Novel drug candidates for treating esophageal carcinoma: A study on differentially expressed genes, using connectivity mapping and molecular docking.International journal of oncology · 2019Article
- Microenvironment of ruptured cerebral aneurysms discovered using data driven analysis of gene expression.PloS one · 2019Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundAtypical meningiomas are common central nervous system neoplasms with high recurrence rate and poorer prognosis compared to their grade I counterparts. Surgical excision and radiotherapy remains the mainstay therapy but medical treatments are limited. We explore new drug candidates using computational drug repurposing based on the gene expression signature of atypical meningioma tissue with subsequent analysis of drug-generated expression profiles. We further explore possible mechanisms of action for the identified drug candidates using ingenuity pathway analysis (IPA).
methodsWe extracted gene expression profiles for atypical meningiomas (12 samples) and normal meningeal tissue (4 samples) from the Gene Expression Omnibus, which were then used to generate a gene signature comprising of 281 differentially expressed genes. Drug candidates were explored using both the Board Institute Connectivity Map (cmap) and Library of Integrated Network-Based Cellular Signatures (LINCS). Functional analysis of significant differential gene expression for drug candidates was performed with IPA.
resultsUsing our integrated approach, we identified multiple, already licensed, drug candidates such as emetine, verteporfin, phenoxybenzamine and trazodone. Analysis with IPA revealed that these drugs target signal cascades potentially relevant in pathogenesis of meningiomas, particular examples are the effect on ERK by trazodone, MAP kinases by emetine, and YAP-1 protein by verteporfin.
conclusionGene expression profiling and use of drug expression profiles have yielded several plausible drug candidates for treating atypical meningioma, some of which have already been suggested by preceding studies. Although our analyses suggested multiple anti-tumour mechanisms for these drugs, further in vivo studies are required for validation. IMPORTANCE OF THE STUDY: To our knowledge this is the first study which combines relatively new, yet established computational techniques to identify additional treatments for a difficult to manage cerebral neoplasm. Beyond proposing already approved drug candidates in the management of atypical meningioma the study highlights the promise held by computational techniques in improving our management strategies.
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