ArticleFrontiers in pharmacology2024
Analysis of gut microbiota-derived metabolites regulating pituitary neuroendocrine tumors through network pharmacology.
Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Multi-omics analysis: Gut microbial metabolites in ovarian lesions.The Journal of international medical research · 2026Article
- The metastatic spectrum in functional and non-functional NENs: mechanistic insights from multi-omics.Frontiers in endocrinology · 2026Review
- Exploring the association between gut microbiota metabolites and hepatocellular carcinoma via network pharmacology.Translational gastroenterology and hepatology · 2026Article
- Baicalin alleviates HScientific reports · 2025Article
- The identification of metabolites from gut microbiota in autism spectrum disorder via network pharmacology.Scientific reports · 2025Article
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Authors and funding
4 authors.
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Abstract
Pituitary neuroendocrine tumors (PitNETs) are a special class of tumors of the central nervous system that are closely related to metabolism, endocrine functions, and immunity. In this study, network pharmacology was used to explore the metabolites and pharmacological mechanisms of PitNET regulation by gut microbiota. The metabolites of the gut microbiota were obtained from the gutMGene database, and the targets related to the metabolites and PitNETs were determined using public databases. A total of 208 metabolites were mined from the gutMGene database; 1,192 metabolite targets were screened from the similarity ensemble approach database; and 2,303 PitNET-related targets were screened from the GeneCards database. From these, 392 overlapping targets were screened between the metabolite and PitNET-related targets, and the intersection between these overlapping and gutMGene database targets (223 targets) were obtained as the core targets (43 targets). Using the protein-protein interaction (PPI) network analysis, Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway and metabolic pathway analysis, CXCL8 was obtained as a hub target, tryptophan metabolism was found to be a key metabolic pathway, and IL-17 signaling was screened as the key KEGG signaling pathway. In addition, molecular docking analysis of the active metabolites and target were performed, and the results showed that baicalin, baicalein, and compound K had good binding activities with CXCL8. We also describe the potential mechanisms for treating PitNETs using the information on the microbiota (
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