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

ABSTRACT:

Background

Formalin-fixed, paraffin-embedded (FFPE) tissue slides are routinely used in cancer diagnosis, clinical decision-making, and stored in biobanks, but their utilization in Raman spectroscopy-based studies has been limited due to the background coming from embedding media.

Methods

Spontaneous Raman spectroscopy was used for molecular fingerprinting of FFPE tissue from 46 patient samples with known methylation subtypes. Spectra were used to construct tumor/non-tumor, IDH1WT/IDH1mut, and methylation-subtype classifiers. Support vector machine and random forest were used to identify the most discriminatory Raman frequencies. Stimulated Raman spectroscopy was used to validate the frequencies identified. Mass spectrometry of glioma cell lines and TCGA were used to validat

SUBMITTER: Lita A 

PROVIDER: S-EPMC11534323 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature