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Title: Identification of prostate cancer diagnostic and prognostic biomarkers in urine expression data with a focus on extracellular vesicles
Author: Curley, Helen
ISNI:       0000 0004 7962 7569
Awarding Body: University of East Anglia
Current Institution: University of East Anglia
Date of Award: 2018
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Prostate Cancer (PCa) is a major clinical problem worldwide with considerable variability in clinical outcome of patients. PCa diagnostics and prognostics currently lack specific and sensitive clinical biomarkers and treatment is not well individualised. The PCA3 test, amongst others, highlights the utility of urine in PCa diagnostics and prognostics. Urine contains cells and extracellular vesicles (EV) that originate in the prostate. There are many areas of the PCa clinical process that could be aided with an expression based urine test, including diagnosis, prognosis and response to therapy. NanoString data (167 transcripts) from 485 EV RNA samples were collected from PCa patients and used to build models that would aid in PCa diagnosis and prognosis i.e. i) PCa (low- (L), intermediate-(I), and high-risk(H)) vs CB (Clinically Benign/No evidence for cancer), ii) high-risk PCa vs CB, and iii) trend in expression across CB > L > I > H. These models were validated in 235 samples, with AUCs of i) 0.851 ii) 0.897 and iii) 0.709, respectively. The potential of using urine EVs to predict patient response to treatments was also investigated. In a pilot data set a signature of seven transcripts was identified that could optimally predict progression of patients on hormone therapy (p = 2.3x10-05; HR = 0.04288). Models were also built using NanoString data from 92 cell RNA samples. Intercomparing expression data from matched cell and EV fractions of urine showed that transcripts significantly higher in the EV samples were associated with the prostate, PCa and cancer in general, supporting them as a viable source of biomarkers in the clinical management of PCa. In conclusion my analyses have demonstrated the utility of examining urine RNA for the diagnosis and prognosis of PCa. My studies have formed the basis of the production of a Prostate Urine Risk test that is currently under development at UEA.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available