A prognostic signature to predict outcome in ovarian cancer patients

Image from Licence Details: A prognostic signature to predict outcome in ovarian cancer patients

Applications: Ovarian cancer prognosis, ovarian cancer patient stratification

The Oxford Classic enables accurate prediction of ovarian cancer prognosis via the identification of the “EMT-high” subtype gene signature. This will help identify new treatment options for poor outcome cancers and assist in the stratification of patients into promising new clinical trials.

The graph is from Cancer Cell paper Volume 37, Issue 2, 10 February 2020, Pages 226-242.e7


Features Benefits
  • Discovered that the “EMT-high” subtype is associated with poor treatment response and low survival rate
  • Uses “EMT-high” subtype for accurate prediction of patient ovarian cancer outcome
  • First to link tumour subtypes to cell-of-origin subtypes in ovarian cancer
  • Novel, innovative technology
  • Successfully identified a group of poor prognosis patients in 8 independent published studies
  • Proven to be effective in a clinical setting
  • Proves to be a reliable gene signature
  • Potential for use in stratifying patients for promising cancer therapies
  • Patients can avoid painful, unnecessary surgeries once prognosis is detected by Oxford Classic
  • Identifies patients eligible for early inclusion in clinical trials targeting EMT
  • Able to help build patient relevant models of EMT using organoids to guide drug discovery
  • Encourages the development of new personalised therapies for the Oxford Classic-defined “EMT-high” subtype
  • Provides a method of testing efficacy of new drugs in patients
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