Spectroscopic analysis of apoptotic tumour cell-derived extracellular vesicles

Abstract

Extracellular vesicles (EVs) are small, membrane delimited particles which are released from cells of all types and disease status. When EVs were first discovered they were thought to be a mechanism to remove waste from cells, but it has since been shown that EVs are important intercellular messengers. EVs contain biomolecules such as proteins and nucleic acids, including mRNA and miRNA, which reflect the status of the parental cell. EVs can be found in almost every bodily fluid, including blood, urine, saliva, and ascites. They are released into the extracellular milieu where they can be endocytosed by neighbouring cells. As EVs are enclosed with a lipid membrane their cargo is protected from degradation in circulation, so they can also travel to distal parts of the body and retain activity. Because of this EVs have been implicated in the pathogenesis of many diseases by transferral of biomolecules from diseased cells to healthy cells, for example transfer of oncogenes to induce oncogenic transformation in healthy cells. EVs have the potential to be used as non-invasive disease biomarkers, if suitable detection and characterisation methods were available. Currently, the gold standard method of EV isolation is a process of differential centrifugation followed by ultracentrifugation. There is no current gold standard method of EV characterisation. Quantification and size determination of EVs can be done by methods such as nanoparticle tracking analysis (NTA), tunable resistive pulse sensing (TRPS), or dynamic light scattering (DLS). Size and morphology can be analysed by electron microscopy. Flow cytometry, invaluable for cell phenotyping, cannot be used on EVs because their small diameter does not sufficiently scatter the laser light in order to be detected. Protein analysis can be done by Western blot; however, this is a bulk technique and cannot distinguish rare subpopulations. Similarly, proteomic studies have been carried out on EV populations, but this is also a bulk technique and requires a large, highly purified sample and the results are not inherently quantitative. New methods of EV characterisation are required which are sensitive, high-throughput, and can analyse individual EVs. In this work, EVs were isolated from Burkitt lymphoma (BL) cells, a type of high-grade non- Hodgkin lymphoma. In vivo these tumours have a high rate of constitutive apoptosis, which promotes the accumulation and activation of tumour associated macrophages (TAMs). TAMs have been shown to have pro-tumour phenotype, including the promoting tumour cell growth and angiogenesis, and may even play a role in metastasis due to their ability to remodel the extracellular matrix. It could be that the EVs released from the apoptotic tumour cells (apoEVs) are impacting the microenvironment to promote the growth of the tumour. To determine if this could be the case, apoEVs and EVs derived from viable cancer cells were analysed to determine if there are any distinguishable biochemical differences between these EV groups which may imply a functional difference. Raman spectroscopy was used to characterise both apoEVs and EVs released from viable tumour cells. This is a vibrational spectroscopy technique which can produce a molecular fingerprint of the analyte. By comparing the spectra of EVs and apoEVs using principal component analysis (PCA), a difference could be seen between the apoEVs and EVs. Differences could also be seen between EVs derived from cells of different lineages (HeLa cervical epithelial cells and BL cells). This implies that EVs derived from different sources have different chemical constituents, and Raman spectroscopy could be a useful tool for characterising and distinguishing different types of EVs. A more targeted approach of detecting EVs would be to use surface enhanced Raman spectroscopy (SERS). Incubating EVs with gold nanoparticles functionalised with Raman reporter molecules and antibodies would allow for sensitive detection of EV subpopulations. In order to identify target proteins for SERS analysis, a non-biased bioinformatic approach was carried out. First, gene expression profile data were obtained from the online repository gene expression omnibus (GEO). Gene expression levels in B cell samples were compared to levels in lymphoma samples. Genes with a higher expression in lymphoma samples were identified, with the view that these would preferentially identify lymphoma EVs in a blood sample, which would contain a mixed population of EVs deriving from both lymphoma and healthy B cells, as well as epithelial cells and other sources. The proteins identified by this analysis did not appear to be transferred onto the EV surface. Proteomics had been carried out on the BL apoEVs and viable BL cell EVs, so the results from this analysis were used to identify membrane proteins which were common to both EV subgroups, and proteins which were only found on the apoEVs in order to selectively detect this population. The pan-B cell marker CD20 was identified in both populations, while the lymphocyte receptor CD53 was found only on the apoEVs, so these proteins were used as targets for detection with SERS. A nitrocellulose membrane was used to non-specifically capture EVs by hydrophobic interactions with proteins. A pilot study with BL cells showed that SERS signal of anti-CD20 functionalised gold nanoparticles increased with an increasing number of cells captured, with low levels of non-specific binding. However, when the assay was repeated with apoEVs and EVs, the signals obtained from both anti-CD20 functionalised nanoparticles and anti-CD53 functionalised nanoparticles were at a similar level or lower than the signal obtained from the EV-free controls. Western blots of the EV populations showed that there was no detectable CD20 or CD53 in either population, despite showing up in the proteomic analysis. This work shows that Raman spectroscopy can be used to differentiate between EVs of different types. SERS also has great potential in detecting EV sub-populations, however the target proteins chosen for this study were not present on the surface of the EV. Other markers could be used as targets for EV detection by SERS, such as proteins identified by proteomics which have been experimentally validated to be present on the EV surface, or lipid markers such as phosphatidylserine.