“Cancer 2015”: A prospective, population-based cancer cohort—phase 1: Feasibility of genomics-guided precision medicine in the clinic

John P. Parisot, Heather Thorne, Andrew Fellowes, Ken Doig, Mark Lucas, John J. McNeil, Brett Doble, Alexander Dobrovic, Thomas John, Paul A. James, Lara Lipton, David Ashley, Theresa Hayes, Paul McMurrick, Gary Richardson, Paula Lorgelly, Stephen B. Fox, David M. Thomas

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9 Citations (Scopus)


“Cancer 2015” is a longitudinal and prospective cohort. It is a phased study whose aim was to pilot recruiting 1000 patients during phase 1 to establish the feasibility of providing a population-based genomics cohort. Newly diagnosed adult patients with solid cancers, with residual tumour material for molecular genomics testing, were recruited into the cohort for the collection of a dataset containing clinical, molecular pathology, health resource use and outcomes data. 1685 patients have been recruited over almost 3 years from five hospitals. Thirty-two percent are aged between 61–70 years old, with a median age of 63 years. Diagnostic tumour samples were obtained for 90% of these patients for multiple parallel sequencing. Patients identified with somatic mutations of potentially “actionable” variants represented almost 10% of those tumours sequenced, while 42% of the cohort had no mutations identified. These genomic data were annotated with information such as cancer site, stage, morphology, treatment and patient outcomes and health resource use and cost. This cohort has delivered its main objective of establishing an upscalable genomics cohort within a clinical setting and in phase 2 aims to develop a protocol for how genomics testing can be used in real-time clinical decision-making, providing evidence on the value of precision medicine to clinical practice.

Original languageEnglish
Pages (from-to)354-369
Number of pages16
JournalJournal of Personalized Medicine
Issue number4
Publication statusPublished - 29 Oct 2015


  • Cancer genomics cohort
  • Health economics
  • Next-Gen sequencing
  • Precision medicine

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