Bioinformatics Strategies to Identify Shared Molecular Biomarkers That Link Ischemic Stroke and Moyamoya Disease with Glioblastoma

Expanding data suggest that glioblastoma is accountable for the growing prevalence of various forms of stroke formation, such as ischemic stroke and moyamoya disease. However, the underlying deterministic details are still unspecified. Bioinformatics approaches are designed to investigate the relati...

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Bibliographic Details
Published in:Pharmaceutics 2022-07, Vol.14 (8), p.1573
Main Authors: Islam, Md Khairul, Islam, Md Rakibul, Rahman, Md Habibur, Islam, Md Zahidul, Amin, Md Al, Ahmed, Kazi Rejvee, Rahman, Md Ataur, Moni, Mohammad Ali, Kim, Bonglee
Format: Article
Language:English
Subjects:
association
Bioinformatics
Biomarkers
Brain cancer
Brain research
Carotid arteries
Complications and side effects
Computational biology
Datasets
Development and progression
Disease
Gene expression
glioblastoma
Glioblastoma multiforme
GSEA
Health aspects
Hypotheses
Hypoxia
Ischemia
ischemic stroke
Methods
moyamoya
Moyamoya disease
Radiation therapy
Risk factors
Sample size
Stem cells
Stroke
Stroke (Disease)
Tumors
Veins & arteries
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Summary:Expanding data suggest that glioblastoma is accountable for the growing prevalence of various forms of stroke formation, such as ischemic stroke and moyamoya disease. However, the underlying deterministic details are still unspecified. Bioinformatics approaches are designed to investigate the relationships between two pathogens as well as fill this study void. Glioblastoma is a form of cancer that typically occurs in the brain or spinal cord and is highly destructive. A stroke occurs when a brain region starts to lose blood circulation and prevents functioning. Moyamoya disorder is a recurrent and recurring arterial disorder of the brain. To begin, adequate gene expression datasets on glioblastoma, ischemic stroke, and moyamoya disease were gathered from various repositories. Then, the association between glioblastoma, ischemic stroke, and moyamoya was established using the existing pipelines. The framework was developed as a generalized workflow to allow for the aggregation of transcriptomic gene expression across specific tissue; Gene Ontology (GO) and biological pathway, as well as the validation of such data, are carried out using enrichment studies such as protein-protein interaction and gold benchmark databases. The results contribute to a more profound knowledge of the disease mechanisms and unveil the projected correlations among the diseases.
ISSN:1999-4923
1999-4923
DOI:10.3390/pharmaceutics14081573