Prognostic model construction and target identification of Si-Wu-Tang against breast cancer

Zeye Zhang; Zexin Zhang; Jinqin Song; Wenfeng Wu; Yiqi Chen; Jing Li; Yongchen Wang; Piwen Zhao

doi:10.1016/j.heliyon.2023.e20709

Prognostic model construction and target identification of Si-Wu-Tang against breast cancer

Heliyon. 2023 Oct 12;9(10):e20709. doi: 10.1016/j.heliyon.2023.e20709. eCollection 2023 Oct.

Authors

Zeye Zhang¹, Zexin Zhang², Jinqin Song³, Wenfeng Wu², Yiqi Chen², Jing Li⁴, Yongchen Wang², Piwen Zhao¹

Affiliations

¹ School of Life Sciences, Beijing University of Chinese Medicine, Beijing, 100029, China.
² The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510405, China.
³ School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510405, China.
⁴ The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510405, China.

Abstract

The targets and mechanisms of Si-Wu-Tang (SWT) against (Breast cancer) BRCA were identified and a survival model and nomogram was construted by network pharmacology, bioinformatic analysis and in vitro experiments. A total of 72 anti-breast cancer SWT targets were selected, among which eleven genes (MAOA、SQLE、CACNA2D1、GLI1、RORB、ITGB3、TACR1、NR3C2、CA3、RBP4 and PTK6) were used to construct a novel prognostic model of breast cancer. The anti-breast cancer activity of SWT was related to the modulation of the receptor tyrosine kinases signaling pathways. Moreover, two compounds, mairin and senkyunone were found to bind directly to ITGB3 and RORB proteins. Finally, mRNA and protein expression of ITGB3 and RORB was observed to be significantly down-regulated after incubation of MCF-7 cells with SWT. Overall, our results indicated that mairin and senkyunone were the key ingredients present in SWT, and ITGB3 as well as RORB proteins were the major targets affected by SWT. The prognostic model can be used to predict the outcome of BRCA patients.

Keywords: Bioinformatics analysis; Breast cancer; Network pharmacology; Si-Wu-Tang.