Uncovering the anti-cancer mechanism of cucurbitacin D against colorectal cancer through network pharmacology and molecular docking

Abstract

Colorectal cancer is a significant global health challenge due to chemoresistance, necessitating new treatments. Cucurbitacin D, with its anti-cancer properties, shows promise, but its effects on colorectal cancer are not well understood. We investigated the impact of cucurbitacin D on colorectal cancer cell lines using MTT assays and Annexin V/7-AAD staining followed by flow cytometry for apoptosis analysis. Public databases helped identify cucurbitacin D and colorectal cancer-related gene targets for network pharmacology analysis. Protein-protein interaction networks were constructed using STRING and analyzed in Cytoscape. Gene ontology and KEGG pathway enrichment analyses were performed using ClueGo. Molecular docking studies were conducted via Autodock Vina and visualized in Discovery Studio. Western blot assessed protein expression changes in key targets under cucurbitacin D. Cucurbitacin D dose-dependently reduced colorectal cancer cell viability and induced apoptosis. Network pharmacology pinpointed crucial targets like STAT3, AKT1, CCND1, and CASP3. Molecular docking confirmed strong interactions with these targets. Enrichment analysis highlighted involvement in the 'PI3K-AKT,' 'JAK-STAT,' and 'ErbB' signaling pathways. These findings suggest cucurbitacin D as a potential anti-colorectal cancer agent, demonstrating significant effects on cell viability and apoptosis, and engaging critical cancer-related pathways, making it a promising candidate for further colorectal cancer therapeutic research.

Keywords: Colorectal cancer; Cucurbitacin D; Gene ontology; KEGG; Molecular docking; Network pharmacology.

Fig. 1

Cucurbitacin D (CuD) inhibits the cell viability of Colorectal cancer (CRC) cell lines. A 2D Structure depiction of CuD, B CRC cell lines—DLD-1, LoVo, HCT-8, and HCT-15—were treated with the indicated doses of CuD for 24 h, and cell viability was measured using the MTT assay. (0: Control, cells treated with 0.1% DMSO at the final concentration as vehicle; CuD: cells were treated with CuD at final concentrations of 0.05, 0.5, or 5 μM)." C Representative images of untreated and 5 μM CuD-treated CRC cells after 24 h, highlighting morphological changes indicating cell death. The Shapiro–Wilk test was utilized to assess the normality of the data. Differences were analyzed using an unpaired two-tailed Student's t-test with Welch's correction. The data are presented as means ± standard errors of the mean (SEM), based on three independent experiments. *p < 0.05, **p < 0.01, and ***p < 0.001 (vs. “0” for each cell lines)

Fig. 2

CuD treatment induces apoptotic cell death of CRC cell lines. A Representative flow cytometry scatter plots showing cells undergoing apoptosis in response to CuD. Percentages corresponding to the four quadrants have been added to indicate viable cells, early apoptotic cells, late apoptotic cells, and necrotic cells. B Bar graph shows percentage of DLD-1, LoVo, HCT-8, and HCT-15 cells experiencing apoptosis after exposure to 0.05, 0.5, and 5 μM CuD for 24 h. The Shapiro–Wilk test was utilized to assess the normality of the data. Differences were analyzed using an unpaired two-tailed Student's t-test with Welch's correction. The data are presented as means ± standard errors of the mean (SEM), based on three independent experiments

Fig. 3

Venn diagram illustrating potential anti-CRC targets of CuD

Fig. 4

Protein–protein interaction (PPI) network analysis and identification of key targets for CuD in CRC. A–C The Degree, Betweenness Centrality, Closeness Centrality values of the identified targets in the PPI network was determined using Cytoscape software. Bar chart highlights the top 10 targets from each type of topological analysis. The bars colored red in the chart represents the core targets identified across all three centrality analyses

Fig. 5

The GO and KEGG pathway analysis. A Biological process (GO), B KEGG pathway analysis. The Y-axis represents the enriched GO terms and KEGG pathways, while the X-axis denotes the GeneRatio, representing the percentage of genes associated with each GO or KEGG term. The size of the dots indicates the Count (number of genes associated with each term), and the color of the dots corresponds to the -Log10(p-value), corrected using the Benjamini–Hochberg method for multiple comparisons

Fig. 6

Molecular Docking Analysis of Cucurbitacin D with Target Proteins. Molecular docking of A STAT3 (PDB ID: 6NJS), B AKT1 (PDB ID: 3MVH), C cyclin D1 (PDB ID: 2W96) and D caspase-3 (PDB ID: 2J30) with Cucurbitacin D

Fig. 7

Western blot analysis for examining expression levels of targeted proteins in CRC cells treated with CuD. CRC cell lines were treated with the CuD (concentration of each IC 50; DLD-1: 4.476 μM, Lovo: 4.454 μM, HCT-8: 4.036 μM, HCT-15: 3.418 μM) for 24 h. Expression of p-AKT, AKT, p-STAT3, STAT3, Cyclin D1, Cleaved caspase 3 and GAPDH was determined by western blotting. Densitometry analysis was performed using ImageJ, and the protein expression levels were normalized to GAPDH. The ratios of protein expression in CuD-treated cells to the control group (untreated) are shown below each band. Original unprocessed Western blot images are provided in the supplementary materials