Dr. Rafiq Zakaria Campus, Y. B. Chavan College of Pharmacy, Aurangabad, Maharashtra, India.
Nutr Cancer. 2022;74(6):2222-2234. doi: 10.1080/01635581.2021.1986080. Epub 2021 Oct 6.
In our previous study (AV) has appeared as a promising target for breast cancer hence we have screened potential targets by , In Vitro and In Vivo methods. A network pharmacology (NP) approach involves prediction and validating of targets via molecular modeling, western blotting and In Vivo MNU-induced mammary cancer. The PPI network showed the 573 edges between 214 nodes (targets) that are involved in breast cancer and important one are ESR-1, ESR-2, AR, EGFR, NOS3, MAPK, KDR, SRC and MET. Compound-target-pathway network involves 04 compounds and 221 interactive protein targets associated with breast cancer. GO and KEGG enrichment analysis predicted the ERR, c-MET, PDGFR-α/β, EGFR, and VEGF as a key targets in the breast cancer treatment which are validated via molecular modeling. Expression of ER-α, AR and EGFR were significantly down regulated by AV in MCF-7 cell line. In addition, the immunoreactivity of ER-α was reduced significantly in MNU-induced mammary carcinoma, which is a key target in ER + breast cancer. Overall, this study scientifically light ups the pharmacological mechanism of AV in the treatment of breast cancer, strongly associated with the regulation of ESR signaling pathway.
在我们之前的研究中,AV 似乎是乳腺癌的一个有前途的靶点,因此我们通过体外和体内方法筛选了潜在的靶点。网络药理学 (NP) 方法涉及通过分子建模、western blot 和体内 MNU 诱导的乳腺癌来预测和验证靶点。PPI 网络显示,214 个节点(靶点)之间有 573 条边,涉及乳腺癌和重要的靶点有 ESR-1、ESR-2、AR、EGFR、NOS3、MAPK、KDR、SRC 和 MET。化合物-靶点-通路网络涉及 04 种化合物和 221 个与乳腺癌相关的相互作用蛋白靶点。GO 和 KEGG 富集分析预测 ERR、c-MET、PDGFR-α/β、EGFR 和 VEGF 是乳腺癌治疗的关键靶点,这些靶点通过分子建模得到了验证。AV 在 MCF-7 细胞系中显著下调 ER-α、AR 和 EGFR 的表达。此外,AV 还显著降低了 MNU 诱导的乳腺癌中 ER-α 的免疫反应性,这是 ER+乳腺癌的一个关键靶点。总的来说,这项研究从科学上阐明了 AV 治疗乳腺癌的药理学机制,与 ESR 信号通路的调节密切相关。