Targeting metabolic vulnerabilities in breast cancer cells by combining PEDF and doxorubicin: pathway insights from GC/MS-based metabolomics

Authors

  • Raziyeh Abooshahab Curtin Medical School, Curtin University, Bentley 6102, Australia; Curtin Health Innovation Research Institute, Bentley 6102, Australia https://orcid.org/0000-0001-7379-0339
  • Hani Al-Salami Curtin Medical School, Curtin University, Bentley 6102, Australia; Biotechnology and Drug Development Research Laboratory, Curtin Health Innovation Research Institute, Bentley 6102, Australia https://orcid.org/0000-0003-0049-6969
  • Crispin R. Dass Curtin Medical School, Curtin University, Bentley 6102, Australia. Office: Curtin Health Innovation Research Institute, Bldg 305, Room 124, Curtin University, Bentley campus. Phone: +61 8 9266 1489 E-mail: Crispin.Dass@curtin.edu.au https://orcid.org/0000-0001-7087-7957

DOI:

https://doi.org/10.17179/excli2025-8508

Keywords:

breast cancer, PEDF, doxorubicin, GC/MS, metabolomics, metabolic profiling

Abstract

Breast cancer (BC), characterised by its diverse subtypes and molecular heterogeneity, remains a major challenge in oncology. Despite advances in chemotherapy, such as doxorubicin (Dox), limitations persist due to toxicity and drug resistance. Pigment epithelium-derived factor (PEDF) is a multifunctional protein with unique anti-tumour properties. The aim here was to elucidate metabolic reprogramming in human BC cell lines using a metabolomics approach. Untargeted gas chromatography-quadrupole mass spectrometry (GC/Q-MS) was employed to identify the metabolic alterations in BC cell lines MCF-7 (ER-positive) and MDA-MB-231 (TNBC) following treatment with PEDF, Dox, and their combination (Dox+PEDF) in comparison to untreated controls. Statistical models were employed using a combination of multivariate and univariate analyses, including partial least squares discriminant analysis (PLS-DA) and one-way ANOVA, applied by MetaboAnalyst and SIMCA software. To address the potential for multiple-testing errors, false discovery rate (FDR)-adjusted p-values were calculated to ensure robust statistical reliability. The overall analysis revealed significant metabolic alterations across the treatment groups, with distinct patterns emerging in carbohydrate, lipid, and amino acid metabolisms. In MCF-7 cells, PEDF combined with Dox significantly decreased cystine levels and modulated aspartic acid and lipid-related metabolites, indicating potential shifts in redox homeostasis and membrane composition. In MDA-MB-231 cells, the combination treatment significantly reduced glucose-6-phosphate and lactate levels, suggesting remodeling of glycolytic flux and redox balance. Furthermore, the combination of PEDF and Dox influenced amino acid and lipid metabolism. Pathway enrichment and correlation analyses revealed significant perturbations in glutathione metabolism, energy pathways, and lipid signaling, with notable differences between the two cell lines. Combining Dox and PEDF induced coordinated changes in metabolic networks, suggesting synergistic and antagonistic mechanisms that impact multiple biochemical pathways. These findings underline the importance of combining PEDF with chemotherapy to improve treatment outcomes in BC.

Published

2025-08-18

How to Cite

Abooshahab, R., Al-Salami, H., & Dass, C. R. (2025). Targeting metabolic vulnerabilities in breast cancer cells by combining PEDF and doxorubicin: pathway insights from GC/MS-based metabolomics. EXCLI Journal, 24, 1037–1055. https://doi.org/10.17179/excli2025-8508

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Original articles

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