By Amanda Maxwell –
Clark et al. used tandem mass tagging (TMT) technology in association with support vector machine (SVM) multivariate cluster analysis to define the proteome contained within breast cancer exosomes.1 With a view to full characterization for liquid biopsy diagnostics, the team presents a workflow that both completes protein identification and ensures exclusion of non-exosome contaminants.
Exosomes are packages of endocytic contents released by cells. Cancer exosomes contain a well-conserved range of elements such as mRNA, miRNA and other proteins, including oncogenic materials that take part in tumor development and metastasis. Typically 40–130 nm in size with a distinctive cup-shaped morphology, these vesicles circulate in the blood and show great potential in liquid biopsy diagnostics as circulating cancer markers. Clinicians may eventually be able to diagnose and characterize cancers, monitor response to treatment, and offer prognostic advice from a simple blood draw.
However, defining the exosome proteome conclusively is difficult, as non-exosomal contaminants from the cell itself and other circulating factors can confuse identification. For this reason, researchers frequently employ enrichment techniques such as immunoaffinity, ultracentrifugation and electron microscopy (EM) to prepare samples and validate findings.
Clark et al. looked to TMT multiplexing to enable a liquid chromatography–tandem mass spectrometry (LC-MS/MS) approach that would allow direct comparison of proteins within various enrichment fractions generated during sample preparation. The researchers theorized that they could readily identify exosomal proteins by this comparison, as they would show an increase only in the enriched fractions. They explored this using 24-hour conditioned medium (CM) from metastatic breast cancer cell line SKBR3B.
First, the team collected three fractions from the cell-free CM supernatant according to the following centrifugation and enrichment protocols, each showing progressive accumulation of exosomal contents:
- Centrifuge at 10,000 xg for 30 minutes = 10 K pellet
- Centrifuge at 100,000 xg for 70 minutes = 100 K pellet
- Density gradient preparation using a commercial kit, selecting exosome-containing fractions using exosome-specific marker antibodies = Opti pellet
Once the fractions were collected, Clark et al. lysed the fraction contents before following a standard trypsin digestion protocol. After subjecting the peptide preparations to modified filter-aided sample preparation, they added the TMT 6-plex labeling reagents and proceeded with LC-MS/MS analysis on an LTQ Orbitrap XL mass spectrometer (Thermo Scientific).
Once the researchers obtained the spectral data, they identified proteins and measured abundancies in the three experimental fractions. They also compared findings with those obtained from traditional size exclusion chromatography to prepare exosome-enriched samples, validating protein identification using Western immunoblotting. The team also examined fractions by EM to confirm typical size and exosome morphology.
Having validated the methodology, Clark et al. set up SVM cluster analysis to determine exosomal origin. They identified 2,179 proteins from LC-MS/MS analysis; by assessing five exosome and eight non-exosome markers with SVM cluster analysis, the distinct groupings showed that 251 proteins came from the exosome proteome.
As a further validation step, the researchers reexamined the data, quantifying levels of 12 plasma membrane markers that might indicate fragmentation and contamination in the enriched exosome fractions. They found that only Integrin α-V and CD151 clustered with the exosome proteins, but with low probability following SVM analysis.
In conclusion, Clark et al. are confident that the methodology results in accurate characterization of the breast cancer exosome proteome with adequate identification of contaminants that might confuse results. Furthermore, they suggest that with modification, this workflow could be a valuable tool in exosome characterization in other cancers.