Elucidating the protective mechanism of ganoderic acid DM on breast cancer based on network pharmacology and in vitro experimental validation

乳腺癌 癌症 对接(动物) 癌症研究 细胞凋亡 药理学 体外 表皮生长因子受体 表皮生长因子受体抑制剂 化学 生物 受体 医学 生物化学 内科学 护理部
作者
Mohammed Sharif Swallah,Precious Bondzie‐Quaye,Xin Yu,Monia Ravelonandrasana Fetisoa,Changsheng Shao,Qing Huang
出处
期刊:Biotechnology and Applied Biochemistry [Wiley]
被引量:1
标识
DOI:10.1002/bab.2673
摘要

Abstract Ganoderma lucidum , a popular medicinal fungus, has been utilized to treat a variety of diseases. It possesses a unique therapeutic and pharmacological reputation in suppressing cancer/tumor progression, especially breast cancer, due to its embedded rich bioactive chemical constituents, mainly triterpenoids (ganoderic acids). The most prevalent malignant tumor in women with a high mortality and morbidity rate is breast cancer. Ganoderic acids A, D, DM, F, and H are evidenced in previous research to have breast cancer–preventive properties by exhibiting autophagic and apoptosis, anti‐proliferative, and anti‐angiogenesis effects. However, the anti‐breast cancer mechanism remains unclear. The putative targets of the ganoderic acids were further determined using bioinformatics techniques and molecular docking calculation. Finally, the key targets were verified in vitro. A total of 53 potential target proteins associated with 202 pathways were predicted to be related to breast cancer. The potential targets were narrowed down to six key targets (AKT1, PIK3CA, epidermal growth factor receptor [EGFR], STAT1, ESR1, and CTNNB1), using different algorithms of the CytoHubba plugin, which were further validated using molecular docking analysis. The ganoderic acid DM (GADM) and the targets (PIK3CA and EGFR) with the strongest interactions were validated via MDA‐MB‐231 and MCF7 cells. The expression level of PIK3CA in both MDA‐MB‐231 and MCF7 cells was dose‐dependently suppressed by GADM, whereas EGFR expression was unexpectedly increased, which warrants further investigation. These data indicated that the network pharmacology–based prediction of GADM targets for treating human breast cancer could be reliable.
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