Cao Min, Huang Ping, Xu Lun-Shan, Zhang Yi-Hua
Department of Neurosurgery, Daping Hospital, Army Medical University, Chongqing, China.
Front Pharmacol. 2024 Sep 4;15:1403864. doi: 10.3389/fphar.2024.1403864. eCollection 2024.
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 (), signaling pathway (IL-17), target (CXCL8), and metabolites (baicalin, baicalein, and compound K); we expect that these will provide a scientific basis for further study.
垂体神经内分泌肿瘤（PitNETs）是一类特殊的中枢神经系统肿瘤，与代谢、内分泌功能和免疫密切相关。在本研究中，采用网络药理学方法探讨肠道微生物群对PitNETs的调节代谢产物和药理机制。肠道微生物群的代谢产物来自gutMGene数据库，并使用公共数据库确定与这些代谢产物和PitNETs相关的靶点。从gutMGene数据库中挖掘出208种代谢产物；从相似性整合方法数据库中筛选出1192个代谢产物靶点；从GeneCards数据库中筛选出2303个与PitNETs相关的靶点。从中筛选出代谢产物与PitNETs相关靶点之间重叠的392个靶点，并将这些重叠靶点与gutMGene数据库靶点（223个靶点）的交集作为核心靶点（43个靶点）。通过蛋白质-蛋白质相互作用（PPI）网络分析、京都基因与基因组百科全书（KEGG）信号通路和代谢通路分析，获得CXCL8作为枢纽靶点，发现色氨酸代谢是关键代谢通路，筛选出IL-17信号通路作为关键KEGG信号通路。此外，还对活性代谢产物与靶点进行了分子对接分析，结果表明黄芩苷、黄芩素和化合物K与CXCL8具有良好的结合活性。我们还利用微生物群、信号通路（IL-17）、靶点（CXCL8）和代谢产物（黄芩苷、黄芩素和化合物K）的信息描述了治疗PitNETs的潜在机制；我们期望这些将为进一步研究提供科学依据。
