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Network Pharmacology-Based Approach to Investigate the Molecular Targets of Sinomenine for Treating Breast Cancer

Authors Li XM, Li MT, Jiang N, Si YC, Zhu MM, Wu QY, Shi DC, Shi H, Luo Q, Yu B

Received 25 October 2020

Accepted for publication 18 January 2021

Published 9 February 2021 Volume 2021:13 Pages 1189—1204


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 4

Editor who approved publication: Dr Sanjeev Srivastava

Xiao-Mei Li,1,2,* Mao-Ting Li,2,3,* Ni Jiang,1 Ya-Chen Si,3 Meng-Mei Zhu,2 Qiao-Yuan Wu,1 Dong-Chen Shi,4 Hui Shi,4 Qing Luo,1 Bing Yu2

1Cancer Research Laboratory, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou Province, 563003, People’s Republic of China; 2Department of Cell Biology, Center for Stem Cell and Medicine, Navy Medical University (Second Military Medical University), Shanghai, 200433, People’s Republic of China; 3Student Brigade, Second Military Medical University, Shanghai, People’s Republic of China; 4Department of Respiratory and Critical Care Medicine, Shanghai Changhai Hospital, Shanghai, 200433, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Bing Yu; Qing Luo Email;

Purpose: Sinomenine has been known to inhibit the proliferation of breast cancer cells. However, its targets have not been found yet. This study aimed to search for molecular targets of sinomenine for treating breast cancer via network pharmacology.
Methods: Potential targets of sinomenine or breast cancer were separately screened from indicated databases. The common targets of both sinomenine and breast cancer were considered as the targets of sinomenine for treating breast cancer. A sinomenine-target-pathway network was constructed based on the obtained results from Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The putative targets of sinomenine were further determined by using protein–protein interaction (PPI) analysis and molecular docking. Finally, the putative targets were verified in vitro and in vivo.
Results: Twenty predicted targets were identified through network pharmacological analysis. Gene Ontology (GO) and KEGG pathway enrichment indicated that these predicted targets enriched in the process of MAP kinase activity, VEGF signaling pathway, Relaxin signaling pathway, Growth hormone synthesis, secretion and action. MAPK1, NOS3, NR3C1, NOS1 and NOS2 were further identified as the putative targets by using PPI and molecular docking analysis. Expression of MAPK1, NR3C1, NOS1, NOS2 and NOS3 genes were significantly regulated by sinomenine in both MCF-7 cells and MDA-MB-231 cells. Furthermore, the expression of NR3C1 in human breast cancer specimens was lower than that in para-tumor normal tissues. Meanwhile, the expression of NR3C1 in xenograft tumors was up-regulated after sinomenine treatment.
Conclusion: MAPK1, NR3C1, NOS1, NOS2 and NOS3 were identified as the putative targets of sinomenine for treating breast cancer. NR3C1 was preliminarily confirmed as a target of sinomenine in two breast cancer cell lines, xenograft tumor models and human breast cancer specimens. These data indicated that the network pharmacology-based prediction of sinomenine targets for treating breast cancer could be reliable.

Keywords: sinomenine, breast cancer, network pharmacology, targets screen, NR3C1

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