NDLI: Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy

Content Provider	Springer Nature : BioMed Central
Author	Quesnel, Agathe Coles, Nathan Angione, Claudio Dey, Priyanka Polvikoski, Tuomo M. Outeiro, Tiago F. Islam, Meez Khundakar, Ahmad A. Filippou, Panagiota S.
Abstract	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.
Related Links	https://bmccancer.biomedcentral.com/counter/pdf/10.1186/s12885-023-10588-w.pdf
Ending Page	15
Page Count	15
Starting Page	1
File Format	HTM / HTML
ISSN	14712407
DOI	10.1186/s12885-023-10588-w
Journal	BMC Cancer
Issue Number	1
Volume Number	23
Language	English
Publisher	BioMed Central
Publisher Date	2023-02-21
Access Restriction	Open
Subject Keyword	Cancer Research Oncology Surgical Oncology Health Promotion and Disease Prevention Biomedicine Medicine Public Health Raman spectroscopy Gliomas Biomolecular signatures Diagnosis Glioblastoma Glycosylation Medicine/Public Health
Content Type	Text
Resource Type	Article
Subject	Cancer Research Oncology Genetics
Journal Impact Factor	3.4/2023
5-Year Journal Impact Factor	3.8/2023

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