代谢组学
计算生物学
代谢组
小桶
生物
生物化学
生物信息学
转录组
基因
基因表达
作者
Shulong Shi,Xinchen Tian,Yining Gong,Mingliang Sun,Juan Liu,Jiaqi Zhang,Ya-Ping Liu,Luning Li,Shulong Jiang
标识
DOI:10.1016/j.ijbiomac.2024.135209
摘要
This study aimed to evaluate the efficacy and therapeutic mechanism of parthenolide (PTL) in breast cancer (BC) through a comprehensive strategy integrating network pharmacology, single-cell RNA sequencing (scRNA-seq) and metabolomics. In network pharmacology, 70 therapeutic targets were identified, of which 16 core targets were filtered out through seven classical algorithms of Cytohubba plugin. Additionally, the hub module of PPI network was extracted using MCODE plugin. Molecular docking and molecular dynamics simulation showed a potent binding affinity between PTL and JNK, subsequently validated by MST and SPR assays. Further, Mendelian randomization analysis indicated that JNK was causally associated with BC. GO and KEGG enrichment analyses revealed that PTL counteracted BC via promoting ROS generation, inducing apoptosis and suppressing proliferation, which potentially involved the coordinated regulation of MAPK and FoxO1 pathways. Moreover, ssGSEA and scRNA-seq analysis suggested that PTL may act on T cell immune microenvironment of BC. Subsequently, these bioinformatics-based predictions were experimentally validated using in-vitro and in-vivo models. Finally, metabolome profiling unveiled that PTL remodeled the glycine, serine and threonine metabolism as well as biosynthesis of unsaturated fatty acids, and thereby contributed to BC inhibition. From molecular, immune and metabolic perspectives, this study not only provided a unique insight into the mechanistic details of PTL against BC, but also proposed a novel promising therapeutic strategy for BC.
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