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. 2024 Apr 10:18:1115-1131.
doi: 10.2147/DDDT.S394287. eCollection 2024.

Unveiling the Mechanism of the ChaiShao Shugan Formula Against Triple-Negative Breast Cancer

Teng Fan #  1   2   3 , Yuanyuan Huang #  1   2   3 , Zeyu Liu #  1   2 , Jinsheng Huang  1   2 , Bin Ke  1   2   3 , Yuming Rong  1   2 , Huijuan Qiu  1   2 , Bei Zhang  1   2   3
Affiliations

Unveiling the Mechanism of the ChaiShao Shugan Formula Against Triple-Negative Breast Cancer

Teng Fan et al. Drug Des Devel Ther. .

Abstract

Background: The ChaiShao Shugan Formula (CSSGF) is a traditional Chinese medicine formula with recently identified therapeutic value in triple-negative breast cancer (TNBC). This study aimed to elucidate the underlying mechanism of CSSGF in TNBC treatment.

Methods: TNBC targets were analyzed using R and data were from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The major ingredients and related protein targets of CSSGF were explored via the Traditional Chinese Medicine Systems Pharmacology database, and an ingredient-target network was constructed via Cytoscape to identify hub genes. The STRING database was used to construct the PPI network. GO and KEGG enrichment analyses were performed via R to obtain the main targets. The online tool Kaplan‒Meier plotter was used to identify the prognostic genes. Molecular docking was applied to the core target genes and active ingredients. MDA-MB-231 and MCF-7 cell lines were used to verify the efficacy of the various drugs.

Results: A total of 4562 genes were screened as TNBC target genes. The PPI network consisted of 89 nodes and 845 edges. Our study indicated that quercetin, beta-sitosterol, luteolin and catechin might be the core ingredients of CSSGF, and EGFR and c-Myc might be the latent therapeutic targets of CSSGF in the treatment of TNBC. GO and KEGG analyses indicated that the anticancer effect of CSSGF on TNBC was mainly associated with DNA binding, transcription factor binding, and other biological processes. The related signaling pathways mainly involved the TNF-a, IL-17, and apoptosis pathways. The molecular docking data indicated that quercetin, beta-sitosterol, luteolin, and catechin had high affinity for EGFR, JUN, Caspase-3 and ESR1, respectively. In vitro, we found that CSSGF could suppress the expression of c-Myc or promote the expression of EGFR. In addition, we found that quercetin downregulates c-Myc expression in two BC cell lines.

Conclusion: This study revealed the effective ingredients and latent molecular mechanism of action of CSSGF against TNBC and confirmed that quercetin could target c-Myc to induce anti-BC effects.

Keywords: c-Myc; chaishao shugan formula; molecular docking; network pharmacology; triple-negative breast cancer.

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Conflict of interest statement

The authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
Compounds of CSSGF scanned by LC-MS/MS. (a) MRM of CSSGF (positive mode). (b) MRM chromatogram of CSSGF (negative mode).
Figure 2
Figure 2
Prediction of TNBC related targets. (a) Identification of deferentially expressed genes (DEGs) between breast cancer and breast normal tissues.(b)The volcano data of different gene between breast cancer and breast normal tissues. The blue part shows the downregulated genes. The red part indicates the upregulated genes. And the black part represents the stable genes. (c) Identification of deferentially expressed genes in GEO data set with GSM38959.(d) The volcano data of different gene in the GSM38959 dataset. (e)The intersecting genes in the GEO and TCGA databases. (f)The volcano data of different gene of intersecting genes in the GEO and TCGA databases.
Figure 3
Figure 3
CSSGF-ingredient-target-network. (a)Venn diagram of the target of CSSGF and the target of TNBC. (b) CSSGF ingredient-TNBC target. (c)The PPI network of CSSGF and TNBC targets. (d)The top 30 gene of CSSGF ingredient-TNBC.(e) Top 10 hub genes.
Figure 4
Figure 4
GO and KEGG enrichment analysis of CSSGF -TNBC targets. (a) GO-BP enrichment analysis for potential targets of CSSGF-TNBC. (b). GO-CC enrichment analysis for potential targets of CSSGF-TNBC.(c). GO-MF enrichment analysis for potential targets of CSSGF-TNBC.(d) KEGG pathway enrichment analysis for potential targets of CSSGF-TNBC. (q value refers to -log10 P value). (e) “CSSGF -TNBC target–key pathways” network.
Figure 5
Figure 5
The survival analysis via the Kaplan–Meier plotter. (a) The survival plot of JUN gene.(b) The survival plot of EGFR gene. (c) The survival plot of IL-6 gene.(d) The survival plot of ESR1 gene. (e) The survival plot of PTGS2 gene.(f) The survival plot of c-Myc gene.(g)The survival plot of MMP1 gene.(h)The survival plot of Apopain (Caspase-3) gene.
Figure 6
Figure 6
CSSGF could down-regulate the expression of c-Myc and up-regulate the expression of EGFR both in MDA-MB-231 and MCF-7 cells. (a) WB results after drug treatetment in MDA-MB-231 cells.(b) Statistic results of a.**p<0.01,*: p<0.05, ns: no significant difference. (c) WB results after drug treatetment in MCF-7 cells.(d) Statistic results of c.**: p<0.01.*: p<0.05.
Figure 7
Figure 7
Molecular docking results of core chemical components of CSSGF. (a) Quercetin- EGFR; (b) Quercetin- EGF; (c) Quercetin- c-Myc; (d) Beta-sitosterol-JUN; (e) Luteolin- CASP3; (f) Catechin- ESR1.
Figure 8
Figure 8
Quercetin could downregulate the expression of C-Myc both in MCF-7 cells and MDA-MB-231 cells. (a) CCK-8 assay in quercetin treated MDA-MB-231 cells.(b) CCK-8 assay in quercetin treated MCF-7 cells. (c)WB results of quercetin treated MDA-MB-231 cells.(d) Statistic results of c.**p<0.01.(e) WB results of quercetin treated MCF-7 cells.(f) Statistic results of e.**p<0.01.
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