Raman-based machine-learning platform reveals unique metabolic differences between IDHmut and IDHwt glioma

Abstract

Our results demonstrate the potential of label-free Raman spectroscopy to classify glioma subtypes from FFPE slides and to extract meaningful biological information thus opening the door for future applications on these archived tissues in other cancers.