Using extracellular vesicles, in patient blood, to identify patients at risk of prostate cancer progression & metastatic disease

Dr Jason Webber (Senior Lecturer, Faculty of Medicine Health & Life Sciences, Swansea University)

Prostate cancer (PCa) is a serious health concern, impacting over 50,000 patients and claiming more than 11,000 lives annually within the UK. Despite the prevalence of the disease, current diagnostic methods, such as the prostate-specific antigen (PSA) test, lack both sensitivity and specificity. While multi-parametric magnetic resonance imaging (mp-MRI) represents a major advancement in non-invasive diagnosis of disease, discrimination between patients with aggressive or non-aggressive, slow growing tumours, remains a challenge. In many cases accurate diagnosis requires biopsy which is an invasive procedure with many potential risks. Our research is therefore focussed on the development of novel biomarkers that can be used, in conjunction with current clinical practices, for non-invasive and early detection of patients with aggressive PCa.

Extracellular vesicles (EVs) have emerged as promising sauce of biomarkers for cancer diagnosis. These small, yet highly complex, packages contain vast amounts of information about their originating cells. Importantly, we have already demonstrated that EVs from prostate cancers are detectable within patient blood and can predict the outcome of biopsy (Shephard A et al, 2021). We are extremely fortunate to work with the Wales Cancer Biobank, who have supported this research through the provision of serum samples and associated clinical data required to accurately assess our biomarkers candidates.

Looking to the future, we have multiple ongoing research projects supported by funders such as Cancer Research Wales and Prostate Cancer UK to further develop our EV-based biomarkers to enable identification of patients who are at risk of PCa progression and metastatic disease. To achieve this goal, we are taking a multi-facetted approach to explore the RNA and glycan (sugar) cargoes contained within EVs. We are combining novel laboratory techniques with cutting-edge analytical approaches, such as artificial intelligence and machine learning, to combine multiple biomarkers. This has resulted in collaboration with some of the leading PCa research labs throughout the UK and beyond.

Identified biomarker candidates will be tested using samples from the Wales Cancer Biobank. Data generated will form an extremely valuable resource for future biomarker discoveries, supporting the development of novel biomarkers for identification of patients at risk from aggressive PCa as well as future studies likely to arise from this work.