Background
Prostate cancer (PCa) is the most diagnosed cancer in Australia in 2022, with more than 20,000 new cases and over 3,500 deaths each year. PCa diagnosis mainly relies on several detection tools such as serum prostatic-specific antigens (PSA) test, MRI and tissue biopsy. Because of different grades, stages and tumour heterogeneity, these conventional detection methods might yield misleading results. Extracellular vesicles (EVs) are nano-sized vesicles and secreted by virtually all living cells into the extracellular milieu and contain cellular components encapsulated by lipid membranes. This is known as a liquid biopsy and can provide an alternative solution that is less invasive and more reliable. Unlike other -omics platforms, metabolomics showed the most comprehensive analysis of EVs’ cargo. In this study, we hypothesise that EVs’ metabolic profiles are different between PCa cell lines and normal prostate cell line or between small EVs (sEVs) and large EVs (lEVs). Our objective is to isolate sEVs and lEVs from a panel of PCa cell lines and a normal prostate cell line to identify differences in key metabolites using global approaches.
Methods
Using ultracentrifugation (UC), EVs were isolated from different PCa cell lines (PC3, DU145, LNCaP and 22RV1) and a normal prostate epithelial cell line (RWPE-1). Isolated EVs were characterised into lEVs and sEVs. Confirmation tests such as nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM) and western blotting (WB) were conducted to check the characteristics of isolated EVs for metabolomic analysis. Ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) was employed to investigate the metabolomic profiles of isolated EVs from different cell lines.
Results
Both NTA and TEM confirmed that both sEVs and lEVs are within the typical size and morphology. WB showed distinct protein expression between sEVs and lEVs. EVs concentration of at least 108 vesicles is required to achieve reliable metabolomics outcomes. We have preliminarily identified differences in sEVs and lEVs metabolite content between PCa cell lines and a control cell line.
Conclusion
Our established protocol of EVs isolation using UC is confirmed to yield EVs of high purity and quality for metabolomic analysis. The metabolites identified from different EV subpopulations have the potential to aid in PCa early detection, risk stratification and monitoring metastasis progression. In our following study, further experiments will be run to validate the identified metabolite candidates.