Overview

• Researchers from the Universities of Manchester and Colorado reported results in AACR’s Cancer Research Communications using two independent retrospective sample sets.
• AOA Dx’s test analyzes lipid and protein fragments shed by tumors and applies an algorithm trained on thousands of patient samples to identify ovarian cancer signatures.
• In University of Colorado samples, accuracy was 93% across all stages and 91% in early stages, while Manchester samples showed 92% overall and 88% in early stages.
• Experts said the platform could improve early diagnosis and patient outcomes but stressed that prospective validation and regulatory review are needed before clinical use.
• Clinicians noted potential future NHS integration, and highlighted that ovarian cancer is often diagnosed late in the UK, which sees about 7,500 new cases each year with often vague symptoms.