Integration of Raman spectra with transcriptome data in glioblastoma multiforme defines tumour subtypes and predicts patient outcome

Glioblastoma Multiforme is the most aggressive form of primary brain tumors.

Raman spectroscopy is an imaging technique that has been applied to assess molecular compositions of living cells to characterize cell types and states. However, owing to the diverse molecular species in cells and challenges of assigning peaks to specific molecules, it had not yet been clear how to interpret cellular Raman spectra.

In our new publication in the Journal of Cellular and Molecular Medicine we provide firm evidence that cellular Raman spectra and transcriptomic profiles of glioblastoma can be computationally connected and thus interpreted.

From these analyses, we extract a minimal gene expression signature associated with specific RS profiles and predictive of disease outcome.

This study provides the first association between gene expression and Raman profiles associated with tumor phenotypes (e.g. immune infiltrate). The approach presented in this study could therefore pave the way for near real-time intraoperative tumor characterization and could represent a relevant tool for helping in patient management at a very early stage.

Read the publication here.

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