Oxford Classic – a novel 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.

Features	Benefits
Advanced biomarker discovery for early detection	Enables earlier diagnosis, giving patients a significantly improved chance of successful treatment by identifying HGSOC at its most treatable stages
Precision diagnostic tools for accurate results	Reduces false positives and false negatives, ensuring doctors can confidently diagnose HGSOC with higher accuracy
Targeted therapies based on biomarker profiles	Enables doctors to provide patients with personalised treatment plans that maximise effectiveness while minimising side effects
Real-time disease monitoring for optimised treatment	Helps clinicians track treatment response and adjust therapies quickly to improve outcomes
Combination therapy integration for enhanced effectiveness	Combing the biomarker-targeted drugs with existing chemotherapy or immunotherapy treatments can enhance overall effectiveness

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Oxford Classic – a novel prognostic signature to predict outcome in ovarian cancer patients

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