Identification of Key Therapeutic Targets of Triptolide Against Breast Cancer by Integrated Transcriptomic Analysis and Co-expression Network Approach

Abstract

Abstract Background:Triptolide, a natural product extracted from Tripterygium wilfordii, has shown anti-tumor activities against breast cancer (BC). This study aimed to identify potential therapeutic targets of triptolide for treating breast cancer using bioinformatics approaches. Methods:The transcriptomic data of breast cancer tissues and triptolide-treated breast cancer cells were obtained from public databases. Differentially expressed genes (DEGs) were identified using limma package. Weighted gene co-expression network analysis (WGCNA) was performed to detect modules related to breast cancer progression and triptolide treatment. Hub genes in relevant modules were identified as candidate targets based on module membership and gene significance. The common hub genes were determined as potential therapeutic targets. Functional enrichment was conducted to investigate the biological functions and pathways involved in these therapeutic targets. Then, PPI networks were constructed to explore interactions between them and identify key therapeutic targets. Finally, independent datasets were utilized to validate the expression and diagnostic value of key targets. Results:A total of 5206 and 2113 targets were identified associated with breast cancer progression and triptolide treatment, respectively. By integrating these two groups of targets, 122 common targets were determined as candidate therapeutic targets of triptolide, which were significantly enriched in tumor-related metabolic pathways, such as pyruvate metabolism, glycolysis/gluconeogenesis, citrate cycle. PPI network analysis identified 10 hub targets, including VIM, DLD, ACAT1, RABIF, ALDH2, RPS20, BIN1, TUBB6, CALM1 and PINK1. Their aberrant expression in cancer was validated, and triptolide could reverse this aberrance. ROC analysis showed their potential as diagnostic markers and therapeutic targets. Conclusions:Integrated transcriptomic and network analysis identified potential therapeutic targets of triptolide against breast cancer, including key therapeutic targets VIM, DLD, ACAT1, RABIF, ALDH2, RPS20, BIN1, TUBB6, CALM1 and PINK1. Our findings provide novel insights into the mechanisms of triptolide against breast cancer.