Abstract
Metabolic profiling of cancer cells can play a vital role in revealing the molecular bases of cancer development and progression. In this study, gas chromatography coupled with mass spectrometry (GC-MS) was employed for the determination of signatures found in ER+/PR+ breast cancer cells derived from MCF-7 using different extraction solvents including: A, formic acid in water; B, ammonium hydroxide in water; C, ethyl acetate; D, methanol: water (1:1, v/v); and E, acetonitrile: water (1:1, v/v). The greatest extraction rate and diversity of metabolites occurs with extraction solvents A and E. Extraction solvent D showed moderate extraction efficiency, whereas extraction solvent B and C showed inferior metabolite diversity. Metabolite set enrichment analysis (MSEA) results showed energy production pathways to be key in MCF-7 cell lines. This study showed that mass spectrometry could identify key metabolites associated with cancers. The highest enriched pathways were related to energy production as well as Warburg effect pathways, which may shed light on how energy metabolism has been hijacked to encourage tumour progression and eventually metastasis in breast cancer.
Highlights
Metabolic profiling of cancer cells and biomarkers identifications has drawn the attention of many researchers to understand the complexity and diversity of cancer cell biology
We explore the optimal metabolite extraction protocol from MCF-7 breast cancer cells[37] and the subsequent metabolic profiling utilizing gas chromatography coupled with tandem mass spectrometry (MS)
The GC/MS chromatograms of the extracted cells using the five extraction solutions under investigation are shown in Fig. 1, the greatest extraction rate and diversity of metabolites is noticed when employing 0.2% formic acid and acetonitrile: water mixture, whereas 0.2% ammonium hydroxide and ethyl acetate showed inferior metabolite diversity, whereas methanol: water showed moderate extraction efficiency
Summary
Metabolic profiling of cancer cells and biomarkers identifications has drawn the attention of many researchers to understand the complexity and diversity of cancer cell biology. Metabolomics is a promising analytical tool which is described as a large scale investigation of small molecules (metabolites) in a biological sample that are characterized using mass spectrometry or other suitable biophysical techniques. The huge advancement in the applications of these modern analytical techniques allow the analysis of large metabolomics data at different molecular levels, including the organism, www.nature.com/scientificreports/. Such data can provide critical information about biomolecular function and the biochemical relationships of metabolites, which might lead to a better understanding of the biological system under investigation. Gas chromatography–mass spectrometry (GC-MS) is the most commonly used and standardized technique in metabolomics, with more than 50 years of established protocols for metabolite characterization of amino acids[14], hydroxyl acids[15], fatty acids[16], catecholamines[17], sugars[18], hormones[19], and many other metabolic intermediates. In the last four decades, mass spectra have been accumulated and stored in libraries under standard conditions of 70 eV electron ionization energy[20,21,22], More importantly, tremendous efforts have been made to computationally match mass spectra with experimental data to help in the identification of compounded via their unique fragmentation pattern[23,24,25]
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