AI-Driven Plasma Denaturation Profiling for Multi-Cancer Detection

Résumé fourni par la source

Abstract Many cancers cannot be detected early due to lack of effective disease biomarkers, leading to poor prognosis. We applied an existing biophysical technology nanoDSF in a novel way to answer this unmet biomedical need. We developed a breakthrough digital biomarker method for cancer detection based on AI-classification of plasma denaturation profiles (PDPs) obtained by nanoDSF technology. PDPs from 300 plasma samples from patients with melanoma, brain, digestive or lung cancers were automatically distinguished from ‘healthy’ profiles with an accuracy of 94%. Moreover, our method was able to distinguish different types of cancers from each other with an accuracy of 80%, making it an effective way to help cancer diagnosis and monitoring. Our technology thus paves the way for a long-sought multi-cancer early detection (MCED) test that is blood-based, cost-effective and easy-to-implement in any clinical setting.

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