The Impact of Pigment-Epithelium-Derived Factor on MCF-7 Cell Metabolism in the Context of Glycaemic Condition

Abstract

Studies have demonstrated that pigment-epithelium-derived factor (PEDF) is a robust inhibitor of tumour growth and development, implying that this may serve as a promising target for therapeutic intervention. However, the precise impact of PEDF on cancerous cell metabolic pathways remains uncertain despite ongoing research. In this light, this study aimed to employ a metabolomics approach for understanding the metabolic reprogramming events in breast cancer across different glycaemic loads and their response to PEDF. Gas chromatography-quadrupole mass spectrometry (GC/Q-MS) analysis revealed metabolic alterations in ER⁺ human cell line MCF-7 cells treated with PEDF under varying glycaemic conditions. The identification of significantly altered metabolites was accomplished through MetaboAnalyst (v.5.0) and R packages, which enabled both multivariate and univariate analyses. Out of the 48 metabolites identified, 14 were chosen based on their significant alterations in MCF-7 cells under different glycaemic conditions and PEDF treatment (p < 0.05, VIP > 0.8). Dysregulation in pathways associated with amino acid metabolism, intermediates of the TCA cycle, nucleotide metabolism, and lipid metabolism were detected, and they exhibited different responses to PEDF. Our results suggest that PEDF has a diverse influence on the metabolism of MCF-7 cells in both normo- and hyperglycaemic environments, thereby warranting studies using patient samples to correlate our findings with clinical response in the future.

Keywords: PEDF; breast cancer; cancer metabolism; glycaemia; metabolomics.

Figure 1

(A) The sunburst plot displaying the entire range of metabolomes identified in this study, including amino acids, lipids, and other classes, along with their corresponding metabolites and conjugates. (B) PLS-DA plot of MCF-7 cells under glycaemic loading with and without PEDF created with 95% confidence and cross-validated R2Y = 0.98122 and Q2 = 0.80111 coefficients.

Figure 2

Molecular network of all detected metabolites using GC/MS. Pie charts displaying the distribution of metabolite intensities under the high-glucose (H-control: blue; H-treated: red) and normal-glucose (N-control: grey; N-treated: dark yellow) conditions.

Figure 3

The boxplots display the distribution of 14 metabolites that exhibited the highest significance (p-values < 0.05 and VIP scores > 0.8) in the analysis of variance. These boxplots allow for comparing the four groups: normal and high-glucose conditions with and without PEDF. On the x-axis, each group is represented by individual metabolites, while the y-axis indicates the normalised peak intensity. Metabolites showing significant differences were calculated using Tukey’s Honestly Significant Difference (TukeyHSD) test and indicated as (*) p ≤ 0.05, and (**) p ≤ 0.01. The key for the groups is as follows: H represents high-glucose (H-control: blue; H-treated: red) and N represents normal-glucose (N-control: grey; N-treated: dark yellow).

Figure 4

A metabolite set enrichment analysis (MSEA) based on differentially altered metabolites identified among the groups. MSEA was used to detect significantly enriched metabolic pathways among the groups.