ArticleJournal of Cancer2024
Network Pharmacology and Bioinformatics Analysis to Identify the Molecular Targets and its Biological Mechanisms of Sciadopitysin against Glioblastoma.
Article in Journal of Cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Abstract
Glioblastoma multiform (GBM) is categorized as the most malignant subtype of gliomas, which comprise nearly 75% of malignant brain tumors in adults. Increasing evidence suggests that network pharmacology will be a novel method for identifying the systemic mechanism of therapeutic compounds in diseases like cancer. The present study aimed to use a network pharmacology approach to establish the predictive targets of sciadopitysin against GBM and elucidate its biological mechanisms. Firstly, targets of sciadopitysin were obtained from the SwissTargetPrediction database, and genes associated with the pathogenesis of GBM were identified from the DiGeNET database. Sixty-four correlative hits were identified as anti-glioblastoma targets of sciadopitysin. Functional enrichment and pathway analysis revealed significant biological mechanisms of the targets. Interaction of protein network and cluster analysis using STRING resulted in two crucial interacting hub genes, namely, HSP90 and AKT1. Additionally, the
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