Novel urinary and serological markers of prostate cancer using proteomics techniques: an important tool for early cancer diagnosis and treatment monitoring

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dc.contributor.advisorZerbini, Luiz Fen_ZA
dc.contributor.advisorBlackburn, Jonathan Men_ZA
dc.contributor.authorAdeola, Henry Ademolaen_ZA
dc.date.accessioned2016-07-28T12:19:34Z
dc.date.available2016-07-28T12:19:34Z
dc.date.issued2016en_ZA
dc.description.abstractIn Africa, Prostate cancer (PCa) is the most frequently diagnosed solid organ tumour in males and use of prostate specific antigen (PSA) is presently fraught with diagnostic inaccuracies. Not least, in a multi-ethnic society like South Africa, proteome differences between African, Caucasian and Mixed-Ancestry PCa patients are largely unknown. Hence, discovery and validation of affordable, non-invasive and reliable diagnostic biomarkers of PCa would expand the frontiers of PCa management. We have employed two high-throughput proteomics technologies to identify novel urine- and blood-based biomarkers for early diagnosis and treatment monitoring of prostate cancer in a South African cohort as well as elucidate proteome differences in patients from our heterogeneous cohort. We compared the urinary proteomes of PCa, Benign Prostatic Hyperplasia (BPH), disease controls comprising patients with other uropathies (DC) and normal healthy controls (NC) both by pooling and individual discovery shotgun proteomic assessment on a nano-Liquid chromatography (nLC) coupled Hybrid Quadrupole-Orbitrap Mass Spectrometer platform. In-silico verification of identified biomarkers was performed using the Human Protein Atlas (HPA) as well as SRMAtlas; and verified potential biomarkers were experimentally prevalidated using a targeted parallel reaction monitoring (PRM) proteomics approach. Further, we employed the CT100+ antigen microarray platform to assess the differential humoral antibody response of PCa, DC and BPH patients in our cohort to a panel of 123 tumour-associated cancer antigens. Candidate antigen biomarkers were analyzed for ethnic group variation in our cohort and potential cancer diagnostic and immunotherapeutic inferences were drawn. Using these approaches, we identified 5595 and 9991 non-redundant peptides from the pooled and individual experiments respectively. While nine proteins demonstrated ethnic trend, 37 and 73 proteins were differentially expressed by pooled and individual analysis respectively. All 32 verified biomarkers were prevalidated with parallel reaction monitoring. Good PRM signals for 12 top ranking biomarker was observed, including PSA and prostatic acid phosphatase. We also identified 41 potential diagnostic and immunotherapeutic antigen biomarkers. Proteogenomic functional pathway analyses of differentially expressed antigens showed similar enrichments of biologic processes. We identified herein novel urinary and blood-based potential diagnostic biomarkers and immunotherapeutic targets of PCa in a South African PCa Cohort using multiple proteomics approaches.en_ZA
dc.identifier.apacitationAdeola, H. A. (2016). <i>Novel urinary and serological markers of prostate cancer using proteomics techniques: an important tool for early cancer diagnosis and treatment monitoring</i>. (Thesis). University of Cape Town ,Faculty of Health Sciences ,Division of Medical Biochemistry. Retrieved from http://hdl.handle.net/11427/20955en_ZA
dc.identifier.chicagocitationAdeola, Henry Ademola. <i>"Novel urinary and serological markers of prostate cancer using proteomics techniques: an important tool for early cancer diagnosis and treatment monitoring."</i> Thesis., University of Cape Town ,Faculty of Health Sciences ,Division of Medical Biochemistry, 2016. http://hdl.handle.net/11427/20955en_ZA
dc.identifier.citationAdeola, H. 2016. Novel urinary and serological markers of prostate cancer using proteomics techniques: an important tool for early cancer diagnosis and treatment monitoring. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Adeola, Henry Ademola AB - In Africa, Prostate cancer (PCa) is the most frequently diagnosed solid organ tumour in males and use of prostate specific antigen (PSA) is presently fraught with diagnostic inaccuracies. Not least, in a multi-ethnic society like South Africa, proteome differences between African, Caucasian and Mixed-Ancestry PCa patients are largely unknown. Hence, discovery and validation of affordable, non-invasive and reliable diagnostic biomarkers of PCa would expand the frontiers of PCa management. We have employed two high-throughput proteomics technologies to identify novel urine- and blood-based biomarkers for early diagnosis and treatment monitoring of prostate cancer in a South African cohort as well as elucidate proteome differences in patients from our heterogeneous cohort. We compared the urinary proteomes of PCa, Benign Prostatic Hyperplasia (BPH), disease controls comprising patients with other uropathies (DC) and normal healthy controls (NC) both by pooling and individual discovery shotgun proteomic assessment on a nano-Liquid chromatography (nLC) coupled Hybrid Quadrupole-Orbitrap Mass Spectrometer platform. In-silico verification of identified biomarkers was performed using the Human Protein Atlas (HPA) as well as SRMAtlas; and verified potential biomarkers were experimentally prevalidated using a targeted parallel reaction monitoring (PRM) proteomics approach. Further, we employed the CT100+ antigen microarray platform to assess the differential humoral antibody response of PCa, DC and BPH patients in our cohort to a panel of 123 tumour-associated cancer antigens. Candidate antigen biomarkers were analyzed for ethnic group variation in our cohort and potential cancer diagnostic and immunotherapeutic inferences were drawn. Using these approaches, we identified 5595 and 9991 non-redundant peptides from the pooled and individual experiments respectively. While nine proteins demonstrated ethnic trend, 37 and 73 proteins were differentially expressed by pooled and individual analysis respectively. All 32 verified biomarkers were prevalidated with parallel reaction monitoring. Good PRM signals for 12 top ranking biomarker was observed, including PSA and prostatic acid phosphatase. We also identified 41 potential diagnostic and immunotherapeutic antigen biomarkers. Proteogenomic functional pathway analyses of differentially expressed antigens showed similar enrichments of biologic processes. We identified herein novel urinary and blood-based potential diagnostic biomarkers and immunotherapeutic targets of PCa in a South African PCa Cohort using multiple proteomics approaches. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - Novel urinary and serological markers of prostate cancer using proteomics techniques: an important tool for early cancer diagnosis and treatment monitoring TI - Novel urinary and serological markers of prostate cancer using proteomics techniques: an important tool for early cancer diagnosis and treatment monitoring UR - http://hdl.handle.net/11427/20955 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/20955
dc.identifier.vancouvercitationAdeola HA. Novel urinary and serological markers of prostate cancer using proteomics techniques: an important tool for early cancer diagnosis and treatment monitoring. [Thesis]. University of Cape Town ,Faculty of Health Sciences ,Division of Medical Biochemistry, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/20955en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDivision of Medical Biochemistryen_ZA
dc.publisher.facultyFaculty of Health Sciencesen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherProstate canceren_ZA
dc.titleNovel urinary and serological markers of prostate cancer using proteomics techniques: an important tool for early cancer diagnosis and treatment monitoringen_ZA
dc.typeDoctoral Thesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnamePhDen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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