Professor Vincent Gnanapragasam
Professor Vincent Gnanapragasam is pleased to consider applications from prospective PhD students.
Vincent J Gnanapragasam holds a personal Chair in Urology at the University of Cambridge and is an Honorary Consultant Urologist at Addenbrooke’s Hospital, Cambridge. He graduated from Newcastle University and following basic surgical training, was a recipient of a CRUK PhD studentship and subsequently the first surgeon to be awarded a CRUK Clinician Scientist Fellowship.
Vincent’s academic work has covered the full spectrum of basic science, translational, clinical and epidemiological disciplines in prostate cancer. His laboratory work as group leader has previously led to discoveries into the pivotal role of endogenous signalling regulators (SEF/SPRED) in prostate cancer and mechanistic insights into growth factor signalling in disease progression and treatment resistance. His work is focused on risk-based management of prostate cancer and understanding the key factors needed for personalised management decisions for patients and the value and place of genetic and molecular markers over and above clinical factors.
His clinical work integrates research into practice and is based on the management of early prostate cancer including personalised risk and prognostic stratification and optimal strategies for surveillance. He has developed and implemented novel prognostic prediction models for both group stratified cohorts Cambridge Prognostic Groups and for individualised prediction Predict Prostate for personalised management of prostate cancer. In 2021 the Cambridge Prognostic Groups was officially adopted by the UK National Institute of Clinical Excellence as the recommended risk stratification tool in the national prostate cancer guidelines (NG131). Predict Prostate is the only decision aid endorsed by the UK NICE National Guidelines on prostate cancer for decision making and has been translated into 6 other languages. Both innovations have also been adopted into the East of England Cancer Alliance guidelines. He has pioneered risk stratified managment for active surveillance (STRATCANS) in early prosate cancer and setup one of the first dedicated early prostate cancer clinics in the UK.
He has developed, led and completed numerous investigator led multicentre clinical trials including; Predict Prostate RCT, PRIM biomarker study, TAPS01 and the NIHRi4i funded CamPROBE study (based on his invention of a simple device for infection free prostate biopsies). The CamPROBE has been successfully awarded CE and UKCA mark and has now been commercially licensed for dissemination across the NHS offering a low-cost solution for safer diagnostic prostate biopsies. The invention won the Cambridgeshire Live Business award for Innovation in 2023.
He is Chief Investigator of the DIAMOND study which hold over 2000 bio-samples, tissue and annotated clinical data for biomarker discovery in urological diseases (to date used in over 70 research studies). In recent years he has developed a new clinical trials programme exploring the concept of therapeutic intervention to slow or abrogate early disease progression in prostate cancer. The first of these (TAPS01) has been published and a follow on national RCT (TAPS02) has now started.
To further interdisciplinary research in prostate cancer he established the Cambridge Prostate Cancer collaborative group with colleagues from urology, oncology, radiology, pathology and basic sciences. This collaborative has so far produced >70 peer reviewed papers with a combined grant income of >£6M. Most recently this group collaborated in developing, trialling and reporting on a pragmatic approach to introducing real-time routine genomic profiling into the prostate cancer clinical diagnostic pathway.
He established the Cambridge Urology Translational Research and Clinical Trials office which has to date recruited>2000 patients to various NIHR and portfolio urology trials. He has also established links with STEM scientists to develop a number of innovations including biosensors for cancer detection, machine learning algorithms for disease prediction and novel statistical modelling methods. He has collaborated with national and international colleagues including from the Universities of Manchester, East Anglia, Stanford, Yale, UCLA, Singapore, Korea, Gothenburg, Melbourne, Oslo and Valencia amongst others.
He is a member of the UK ICGC prostate group and on the clinical steering committee of the International Pan Prostate Cancer Collaborative. He is a founder member of the International GAP3 Active Surveillance consortium. To date he has raised over £7M in personal research funding covering basic, translational and clinical trials research, over £6M as co-investigator and published over 200 peer reviewed papers. He is also joint applicant on research collaboratives that have secured over £70M in funding. His work has been cited in prostate cancer guidelines by NICE, the European Association of Urology and Swedish Prostate Cancer Guidelines. He is clinical department lead for urology research and chair of the University MD committee. He is also Visiting Professor at Anglia Ruskin University (ARU) having developed a collaboration between Cambridge University Hospitals and ARU to establish a Masters in Urology programme for early stage clinicians aspiring to a career in Urology. He holds patents and CE marks (Predict Prostate and CamPROBE) and won numerous prizes for research, including the CE Alken prize, Urological Research Society Medal and a RCS England Hunterian Professorship. In the University of Cambridge, he is a recipient of the Vice-Chancellors Award for Research Impact (Established Researcher).
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Selected publications in the last 2 years
Massie C*, Gnanapragasam VJ*, Barrett T, Warren A, Anand S, Keates A, Pacey S. Implementation and yield of upfront genomic profiling in a clinical prostate cancer diagnostic pathway. BJU Int. (2023) Jul 10. doi: 10.1111/bju.16101. *Joint first author
Thankapannair V, Keates A, Barrett T, Gnanapragasam VJ. Prospective Implementation and Early Outcomes of a Risk-stratified Prostate Cancer Active Surveillance Follow-up Protocol. Eur Urol Open Sci. (2023) Jan 24;49:15-22.
Hamdy FC, Donovan JL, Lane JA, Metcalfe C, Davis M, Turner EL, Martin RM, Young GJ, Walsh EI, Bryant RJ, Bollina P, Doble A, Doherty A, Gillatt D, Gnanapragasam V, Hughes O, Kockelbergh R, Kynaston H, Paul A, Paez E, Powell P, Rosario DJ, Rowe E, Mason M, Catto JWF, Peters TJ, Oxley J, Williams NJ, Staffurth J, Neal DE; ProtecT Study Group. Fifteen-Year Outcomes after Monitoring, Surgery, or Radiotherapy for Prostate Cancer. N Engl J Med. (2023) Mar 11. doi: 10.1056/NEJMoa2214122.
Lee C, Light A, Saveliev ES, van der Schaar M, Gnanapragasam VJ. Developing machine learning algorithms for dynamic estimation of progression during active surveillance for prostate cancer. NPJ Digit Med (2022) Aug 6;5(1):110. doi: 10.1038/s41746-022-00659-w.
Gnanapragasam VJ, Greenberg D, Burnet N. Urinary symptoms and prostate cancer-the misconception that may be preventing earlier presentation and better survival outcomes. BMC Med(2022) Aug 4;20(1):264. doi: 10.1186/s12916-022-02453-7.
Wardale L, Cardenas R, Gnanapragasam VJ, Cooper CS, Clark J, Brewer DS. Combining Molecular Subtypes with Multivariable Clinical Models Has the Potential to Improve Prediction of Treatment Outcomes in Prostate Cancer at Diagnosis. Curr Oncol (2022) Dec 22;30(1):157-170. doi: 10.3390/curroncol30010013.
Barrett T, Pacey S, Leonard K, Wulff J, Funingana IG, Gnanapragasam V. A Feasibility Study of the Therapeutic Response and Durability of Short-term Androgen-targeted Therapy in Early Prostate Cancer Managed with Surveillance: The Therapeutics in Active Prostate Surveillance (TAPS01) Study. Eur Urol Open Sci (2022) Feb 10;38:17-24.
Thurtle D, Jenkins V, Freeman A, Pearson M, Recchia G, Tamer P, Leonard K, Pharoah P, Aning J, Madaan S, Goh C, Hilman S, McCracken S, Ilie C, Lazarowicz H, Gnanapragasam VJ Clinical impact of the Predict Prostate risk communication tool in men newly diagnosed with non-metastatic prostate cancer: a multi-centre randomised controlled trial. Eur Urology. (2021) Sep 4:S0302-2838(21)01933-3.
Lee C, Light A, Alaa A, Thurtle D, van der Schaar M, Gnanapragasam VJ. Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database. Lancet Digital Health. (2021) Mar;3(3):e158-e165. doi: 10.1016/S2589-7500(20)30314-9.