Psychopathology · 2006
Persistent auditory hallucinations.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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González J C, Aguilar E J, Berenguer V, Leal C, Sanjuan J
Аннотация
OBJECTIVE: Ursolic acid (UA) has been proven to inhibit various cancer signaling pathways; however, the involvement of UA in overcoming tamoxifen resistance remains unclear and needs further investigation. This study aims to discover the potential gene targets and explore how ursolic acid interacts with those genes to restore sensitivity to tamoxifen.
METHODS: Analyzing gene expression data from GeneCards and Swisstargetprediction for UA related genes, and the Gene Expression Omnibus (GEO) for tamoxifen resistance genes. DEGs were analyzed for functional annotation and molecular pathways using DAVID v6.8, continued with constructing a protein-protein interaction (PPI) network to highlight crucial genes associated with tamoxifen resistance using STRING-DB and Cytoscape. Genetic alteration analysis using cBioportal for target validation and consideration. Molecular docking was done using Autodock4 and PyMoL for visualisation.
RESULTS: The KEGG pathway and PPI network suggest that MDM2, STAT3, TGFB1, and MAPK1 were indicated as potential target genes of UA. Genetic alteration analysis further confirms that MDM2 has the highest alteration, which becomes potentially targeted by UA. Molecular docking analysis confirms that UA can target MDM2 by targeting the N-terminus site on 4HBM and 5ZXF structure. The binding energy of UA is -5.36 for 4HBM and -8.71 for 5ZXF, with all RMSD values below 2. This result shows that UA has a lower docking score than the native ligand for the 5ZXF structure. Additionally, MDM2 is mainly involved in the PI3K-Akt pathway, which plays a role in the chemotherapy resistance mechanism.
CONCLUSION: MDM2 has become a potential target for UA to reverse the tamoxifen resistance mechanism in breast cancer.
METHODS: Analyzing gene expression data from GeneCards and Swisstargetprediction for UA related genes, and the Gene Expression Omnibus (GEO) for tamoxifen resistance genes. DEGs were analyzed for functional annotation and molecular pathways using DAVID v6.8, continued with constructing a protein-protein interaction (PPI) network to highlight crucial genes associated with tamoxifen resistance using STRING-DB and Cytoscape. Genetic alteration analysis using cBioportal for target validation and consideration. Molecular docking was done using Autodock4 and PyMoL for visualisation.
RESULTS: The KEGG pathway and PPI network suggest that MDM2, STAT3, TGFB1, and MAPK1 were indicated as potential target genes of UA. Genetic alteration analysis further confirms that MDM2 has the highest alteration, which becomes potentially targeted by UA. Molecular docking analysis confirms that UA can target MDM2 by targeting the N-terminus site on 4HBM and 5ZXF structure. The binding energy of UA is -5.36 for 4HBM and -8.71 for 5ZXF, with all RMSD values below 2. This result shows that UA has a lower docking score than the native ligand for the 5ZXF structure. Additionally, MDM2 is mainly involved in the PI3K-Akt pathway, which plays a role in the chemotherapy resistance mechanism.
CONCLUSION: MDM2 has become a potential target for UA to reverse the tamoxifen resistance mechanism in breast cancer.