ArticleNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2013
Bioinformatics analysis reveals potential candidate drugs for different subtypes of glioma.
Article in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Quantitative study of bioinformatics analysis on glioma: a bibliometric analysis.Frontiers in oncology · 2023Pooled it
- Using Advanced Bioinformatics Tools to Identify Novel Therapeutic Candidates for Proliferative Vitreoretinopathy.Translational vision science & technology · 2023Article
- Identifying novel candidate compounds for therapeutic strategies in retinopathy of prematurity via computational drug-gene association analysis.Frontiers in pediatrics · 2023Article
- Using Computational Drug-Gene Analysis to Identify Novel Therapeutic Candidates for Retinal Neuroprotection.International journal of molecular sciences · 2022Article
- Using Advanced Bioinformatics Tools to Identify Novel Therapeutic Candidates for Age-Related Macular Degeneration.Translational vision science & technology · 2022Article
- Development of a prognostic model of glioma based on immune-related genes.Oncology letters · 2021Article
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Authors and funding
5 authors.
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Abstract
Gliomas are the most common primary brain tumors of the central nervous system. However, current approaches for treating glioma have limited success, with a low 5-year survival rate. Besides, gliomas can be classified based on various criteria and the exact method of grading changes over time, it is hard for the surgeons to choose the suitable treatment strategies for glioma patients. In present study, we sought to explore the commonalities between different subtypes of glioma, and then identify biologically active small molecules capable of targeting all subtypes of glioma using a computational bioinformatics analysis of gene expression. Results showed that there were common differentially expressed genes between different subtypes of glioma. Pathways related to tumorigenesis and signaling transduction were dysfunctional in the progression of glioma. Further, we identified a group of small molecules. Candidate agents identified by our approach may provide the groundwork for a combination therapy approach for glioma. However, further evaluation for their potential use in the treatment of glioma is still needed.
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