Characterisation of exosomes using a flow cytometry multiplex assay

Abstract

Lung cancer is an extremely morbid condition, with an estimated 2.48 million new diagnoses occurring globally each year. Alarmingly, 70% of these cases are identified at stages III and IV, when the disease is significantly advanced and treatment options become limited and less effective (Aktary et al., 2022). This late-stage diagnosis underscores the urgent need for the development of newer and more effective diagnostic methods that can detect lung cancer at earlier stages, thereby improving prognosis and survival rates. One promising avenue for early diagnosis lies in the study of extracellular vesicles (ECVs). ECVs are nanoscale particles shed by cells, which carry a rich cargo of biomolecules including proteins, cell-free DNA (cfDNA), and RNA (Shedden et al., 2003; Cohen et al., 2017; Okudela et al., 2012). These vesicles play a crucial role in cell-to-cell communication, tumour growth, prognosis, metastasis, and more as such the characterisation of theses vesicles would provide a plethora of information for diagnosis and treatment planning (Kong et al., 2019; Kim, J. et al., 2016; Hasan et al., 2022). In this thesis, lung cancer cell lines were utilized to isolate and characterize ECVs, with the aim of identifying potential biomarkers for early detection of the disease. ECVs were isolated from the cell lines using polyethylene glycol (PEG) precipitation and size exclusion chromatography. These methods are widely used for their efficiency and reliability in purifying ECVs from complex biological samples. Following isolation, the ECVs were characterised using the Luminex xMap® technology, which allows for the simultaneous detection and quantification of multiple biomarkers in a single sample. Multiplexing approaches were employed for the simultaneous detection of multiple cell surface markers, hence increasing specificity. Through the characterisation of ECVs using the methods found in this study. Further developments are liquid biopsy via identifying specific protein markers on the surface of ECVs, it may be possible to develop non-invasive tests for early detection of lung cancer, which could be implemented in routine clinical practice.