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

Area of Science:

• Pharmacology and Bioinformatics
• Oncology Research
• Traditional Chinese Medicine

Background:

• Breast cancer (BRCA) remains a significant health concern globally.
• Understanding the molecular mechanisms of therapeutic agents like Si-Wu-Tang (SWT) is crucial for developing effective treatments.
• Network pharmacology and bioinformatics offer powerful tools for dissecting complex drug-target interactions.

Purpose of the Study:

• To identify the targets and mechanisms of Si-Wu-Tang (SWT) against breast cancer (BRCA).
• To construct a novel prognostic model for breast cancer using key identified genes.
• To validate the role of specific SWT compounds and their protein targets.

Main Methods:

• Network pharmacology and bioinformatic analysis to identify SWT targets in BRCA.
• Construction of a prognostic model using eleven key genes.
• In vitro experiments using MCF-7 cells to assess compound-protein interactions and gene expression.
• Analysis of receptor tyrosine kinases signaling pathways.

Main Results:

• Identified 72 anti-BRCA targets for SWT; eleven genes (MAOA, SQLE, CACNA2D1, GLI1, RORB, ITGB3, TACR1, NR3C2, CA3, RBP4, PTK6) formed a prognostic model.
• SWT's anti-cancer activity is linked to modulating receptor tyrosine kinases signaling pathways.
• Mairin and senkyunone directly bind to ITGB3 and RORB, which were significantly down-regulated in MCF-7 cells treated with SWT.

Conclusions:

• Mairin and senkyunone are key active compounds in SWT.
• ITGB3 and RORB are major protein targets affected by SWT.
• The developed prognostic model can predict outcomes for BRCA patients.