Anti-Inflammatory Effect of Sparstolonin B through Inhibiting Expression of NF-κB and STAT-1

Sparstolonin B Suppresses Proliferation and Modulates Toll-like Receptor Signaling and Inflammatory Pathways in Human Colorectal Cancer Cells

Background: Sparstolonin B (SsnB), a natural compound with anti-inflammatory and anti-proliferative properties, was investigated for its effects on cell viability, apoptosis, and inflammatory pathways in human colorectal cancer cells (HCT-116) and healthy human fibroblasts (BJ). Phorbol 12-myristate 13-acetate (PMA), a tumor promoter and inflammatory activator, was used to stimulate proliferation and inflammatory pathways. Methods: HCT-116 and BJ cells were treated with SsnB (3.125-50 μM) or PMA (1-10 nM) for 12-18 h. Cell viability was assessed using MTT analysis, while apoptosis was evaluated through cleaved caspase-3 staining, terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), and flow cytometry. Proliferation was analyzed through proliferating cell nuclear antigen (PCNA) staining. Toll-like receptor (TLR) signaling, cytokine expression, and sphingolipid levels were measured using immunofluorescence, enzyme-linked immunosorbent assay (ELISA), and mass spectrometry, respectively. Results: SsnB reduced HCT-116 cell viability in a dose- and time-dependent manner with minimal effects on BJ cells. SsnB (25 μM, 12 h) decreased HCT-116 viability 0.6-fold, while PMA (10 nM, 12 h) increased it 2-fold (p < 0.01). No significant change was observed in BJ cells. PCNA fluorescence staining increased 2-fold with PMA and decreased 0.4-fold with SsnB (p < 0.001). PMA upregulated TLR2 and TLR4 mRNA and protein levels, with MyD88, p-ERK, and pNF-κB fluorescence increasing 2.1-, 1.5-, and 1.7-fold, respectively (p < 0.001). PMA elevated TNF-α, IL-1β, and IL-6 levels (p < 0.01). SsnB suppressed PMA-induced effects and promoted apoptosis, increasing cleaved caspase-3 levels by 1.5-fold and TUNEL staining by 1.9-fold (p < 0.01). Flow cytometry confirmed a significant increase in early and late apoptotic cells in the SsnB group. SsnB also increased ceramide (C18, C20, C22, and C24) levels (1.3- to 2.5-fold, p < 0.01) while reducing PMA-induced S1P and C1P increases (p < 0.01). Conclusions: SsnB selectively inhibits proliferation, induces apoptosis, and modulates inflammatory and sphingolipid pathways in colorectal cancer cells, with minimal toxicity to healthy fibroblasts, supporting its potential as a targeted therapeutic agent.

Sparstolonin B Reduces Estrogen-Dependent Proliferation in Cancer Cells: Possible Role of Ceramide and PI3K/AKT/mTOR Inhibition

Background: The aim of this study was to determine the effect of Sparstolonin B (SsnB) on cell proliferation and apoptosis in human breast cancer (MCF-7) and human ovarian epithelial cancer (OVCAR-3) cell lines in the presence and absence of estradiol hemihydrate (ES). Phosphoinositol-3 kinase (PI3K), phosphorylated protein kinase B alpha (p-AKT), phosphorylated mTOR (mechanistic target of rapamycin) signaling proteins, and sphingomyelin/ceramide metabolites were also measured within the scope of the study. Methods: The anti-proliferative effects of SsnB therapy were evaluated over a range of times and concentrations. Cell proliferation was determined by measuring the Proliferating Cell Nuclear Antigen (PCNA). PCNA was quantified by ELISA and cell distribution was assessed by immunofluorescence microscopy. MTT analysis was used to test the vitality of the cells, while LC-MS/MS was used to analyze the amounts of ceramides (CERs), sphingosine-1-phosphate (S1P), and sphingomyelins (SMs). TUNEL labeling was used to assess apoptosis, while immunofluorescence staining and enzyme-linked immunosorbent assay (ELISA) were used to measure the levels of PI3K, p-AKT, and p-mTOR proteins. Results: Sparstolonin B administration significantly decreased cell viability in MCF-7 and OVCAR-3 cells both in the presence and absence of ES, while it did not cause toxicity in healthy human fibroblasts. In comparison to controls, cancer cells treated with SsnB showed a significant drop in the levels of S1P, PI3K, p-AKT, and p-mTOR. In cancer cells cultured with SsnB, a significant increase in intracellular concentrations of C16-C24 CERs and apoptosis was observed. Conclusions: SsnB downregulated the levels of S1P, PI3K, p-AKT, and p-mTOR while reducing cell proliferation and promoting ceramide buildup and apoptosis.

The Toll-like Receptor-2/4 Antagonist, Sparstolonin B, and Inflammatory Diseases: A Literature Mining and Network Analysis

BACKGROUND

Sparstolonin B (SsnB) is characterized as a new toll-like receptor (TLR)-2/4 antagonist. However, the effects of SsnB on different inflammatory diseases have not been systemically reviewed.

METHODS

We investigated the effects of SsnB on inflammatory diseases with data mining and network analysis of literature, including frequency description, cluster analysis, association rule mining, functional enrichment, and protein-protein interaction (PPI) mining.

RESULTS

A total of 27 experimental reports were included. The ARRIVE 2.0 guidelines were used to evaluate the quality of animal studies. Frequency analysis revealed 13 different diseases (cardio-cerebrovascular system diseases account for 23.53%), 12 pharmacological effects (anti-inflammatory effect accounts for 53.85%), and 67 therapeutic targets. The overview of investigation sequence of SsnB studies was depicted by Sankey diagram. Cluster analysis classified the therapeutic targets for SsnB into four main categories: (1) NF-κB; (2) IL-1β, IL-6, and TNF-α; (3) TLR2, TLR4, and MyD88; (4) the other targets. Moreover, the Apriori association discovered two main association pairs: (1) TNF-α, IL-1β, and IL-6 and (2) TLR2, TLR4, and MyD88 (support range 33.33-50%, confidence range 83.33-88.89%). Functional enrichment of the therapeutic targets for SsnB showed that the top enriched items in the biological process were mainly the response to lipopolysaccharide (LPS)/bacterial origin and regulation of cytokine production. Finally, the PPI network and hub gene selection by maximal clique centrality (MCC) algorithm indicated the top ranked proteins were TNF-α, IL-1β, IL-6, AKT1, PPAR-γ, TLR4, CCL2, and TLR2.

CONCLUSION

These results emphasized the importance of TLR2/TLR4-MyD88-NF-κB-IL-1β/IL-6/TNF-α pathways as therapeutic targets of SsnB in inflammatory diseases.