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Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy

Lookup NU author(s): Dr Tuomo Polvikoski, Professor Tiago OuteiroORCiD, Dr Ahmad Khundakar



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2023, Crown.Background: Gliomas are the most common brain tumours with the high-grade glioblastoma representing the most aggressive and lethal form. Currently, there is a lack of specific glioma biomarkers that would aid tumour subtyping and minimally invasive early diagnosis. Aberrant glycosylation is an important post-translational modification in cancer and is implicated in glioma progression. Raman spectroscopy (RS), a vibrational spectroscopic label-free technique, has already shown promise in cancer diagnostics. Methods: RS was combined with machine learning to discriminate glioma grades. Raman spectral signatures of glycosylation patterns were used in serum samples and fixed tissue biopsy samples, as well as in single cells and spheroids. Results: Glioma grades in fixed tissue patient samples and serum were discriminated with high accuracy. Discrimination between higher malignant glioma grades (III and IV) was achieved with high accuracy in tissue, serum, and cellular models using single cells and spheroids. Biomolecular changes were assigned to alterations in glycosylation corroborated by analysing glycan standards and other changes such as carotenoid antioxidant content. Conclusion: RS combined with machine learning could pave the way for more objective and less invasive grading of glioma patients, serving as a useful tool to facilitate glioma diagnosis and delineate biomolecular glioma progression changes.

Publication metadata

Author(s): Quesnel A, Coles N, Angione C, Dey P, Polvikoski TM, Outeiro TF, Islam M, Khundakar AA, Filippou PS

Publication type: Article

Publication status: Published

Journal: BMC Cancer

Year: 2023

Volume: 23

Issue: 1

Online publication date: 21/02/2023

Acceptance date: 27/01/2023

Date deposited: 10/03/2023

ISSN (electronic): 1471-2407

Publisher: BioMed Central Ltd


DOI: 10.1186/s12885-023-10588-w

PubMed id: 36809974


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