Details

Autor(en) / Beteiligte

• Le Reste, Pierre‐Jean
• Pilalis, Eleftherios
• Aubry, Marc
• McMahon, Mari
• Cano, Luis
• Etcheverry, Amandine
• Chatziioannou, Aristotelis
• Chevet, Eric
• Fautrel, Alain

Titel

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

Ist Teil von

• Journal of cellular and molecular medicine, 2021-12, Vol.25 (23), p.10846-10856

Ort / Verlag

England: John Wiley & Sons, Inc

Erscheinungsjahr

2021

Quelle

Wiley Online Library Journals【Remote access available】

Beschreibungen/Notizen

• 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 has not been clear how to interpret cellular Raman spectra. Here, we provide firm evidence that cellular Raman spectra (RS) and transcriptomic profiles of glioblastoma can be computationally connected and thus interpreted. We find that the dimensions of high‐dimensional RS and transcriptomes can be reduced and connected linearly through a shared low‐dimensional subspace. Accordingly, we were able to predict global gene expression profiles by applying the calculated transformation matrix to Raman spectra and vice versa. From these analyses, we extract a minimal gene expression signature associated with specific RS profiles and predictive of disease outcome.