ArticleCurrent medicinal chemistry2026
Identification of Key Genes and miRNA-mRNA Regulatory Networks Associated with Intracranial Aneurysm Progression by Integrative Bioinformatics Analysis.
Article in Current medicinal chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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
2 citing papers in PubMed.
- Precision tumor targeting: gamma-irradiated ellagic acid therapy for ferroptosis and necroptosis modulation via GPX4/ALOX/RIPK/MLKL pathway inhibition.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Molecular Targets for Intracranial Aneurysm Treatment.International journal of molecular sciences · 2025Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntracranial aneurysms (IAs) are the leading cause of nontraumatic subarachnoid hemorrhage (SAH), accounting for up to 85% of all cases of intracranial hemorrhage. The aim of this study was to identify core genes and pathways revealing IAs progression. MATERIALS AND
methodsWe screened differentially expressed genes (DEGs) using mRNA expression profile data from Gene Expression Omnibus (GEO). Then functional and pathway enrichment analyses of DEGs were performed utilizing the database for annotation, visualization, and integrated discovery (DAVID) and the GEO Data Analysis Module within the ACBI Bioinformation tool. Target genes with differential expression of miRNAs were predicted using the miRWalk (Version 3.0) database, and the intersection between these predictions and DEGs was selected as differentially expressed miRNAtarget genes. In addition, a protein-protein interaction (PPI) network and an miRNAmRNA regulatory network were constructed. Finally, L1000CDS2 database analyses were performed to identify the potential therapeutic targets for IAs.
resultsIn total, 742 DEGs and 171 DEGs were identified from the GSE13353 and GSE15629 datasets, respectively. The PPI of DEGs consisted of 868 nodes and 618 edges, including 392 upregulated genes and 521 downregulated genes, respectively, while 10 hub genes were identified. Among the top 10 hub genes, justification of CXCR4, IL6, CCR5, CCL5, CXCR2, CXCL1, CCL2, CCL20, CD4, and CXCL10. These hub genes were primarily augmented in the atherosclerosis process, cytokine-cytokine receptor interaction and cell adhesion molecules pathways. Through the miRNAs-hub gene network construction, 7 miRNAs associated with the hub genes were identified. The results suggest that the sensitivity toward simvastatin, curcumin, parthenolide, celastrol, BMS-345541, etc., correlates with the expression of 10 hub genes.
conclusionIn summary, this study reveals some crucial genes and pathways potentially involved in the pathogenesis of IAs progression. These findings provide a new insight into the research and treatment of IAs.
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