The multi-target mechanism of action of Selaginella doederleinii Hieron in the treatment of nasopharyngeal carcinoma: a network pharmacology and multi-omics analysis

卷柏治疗鼻咽癌的多靶点作用机制:网络药理学和多组学分析

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Abstract

Nasopharyngeal carcinoma (NPC) presents significant treatment challenges due to its complex etiology and late-stage diagnosis. The traditional Chinese medicine Selaginella doederleinii Hieron (S. doederleinii) has shown potentiality in NPC treatment due to its multi-target, multi-pathway anti-cancer mechanisms. First, we identified NPC related target genes from databases like GeneCards, OMIM, and DisGeNET, and performed WGCNA analysis on the GSE53819 dataset to identify several important gene modules related to NPC. Active components and their targets in S. doederleinii were screened from the TCMSP and other databases, identifying 32 overlapping genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that these genes are primarily involved in critical biological processes like protein phosphorylation and cell cycle regulation. A protein-protein interaction network was constructed, and cytoHubba identified six key genes (BCL2, MAPK14, ABCB1, PLK1, ATM, HMOX1). Kaplan-Meier analysis and immune infiltration analysis further showed that these key genes are closely related to the prognosis and immune microenvironment of NPC patients. Single-cell RNA sequencing analysis revealed the expression distribution of key genes across different immune cell types and explored their roles in the differentiation process of malignant cells through pseudotime trajectory analysis. Molecular docking and dynamics simulation results indicated that the Berberine-MAPK14 and Matairesinol-PLK1 complexes have high binding affinity and stability. Binding free energy calculations confirmed the stability of these complexes. Based on our comprehensive multi-level analysis, the active components of S. doederleinii may play a significant role in the treatment of NPC through multi-pathway and multi-target synergistic effects.

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