Deciphering the Finger Prints of Brain Cancer Glioblastoma Multiforme from Four Different Patients by Using Near Infrared Raman Spectroscopy

Hn, Banerjee; Banerji, A. K.; Banerjee, AN; Riddick, Eilena; Petis, J; Evans, Shavonda; Patel, Manishkumar; Parson, Carl; Smith, Stacy; Gwebu, Ephraim T.; Voisin, Sarah

doi:10.4172/1948-5956.1000323

Cited by 11 publications

(3 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to collagen rearrangement, a switch in the level of the different collagen types, has also been shown to occur during glioma progression [ 29 , 42 – 44 ]. Overall, our study confirmed that Raman peaks that increase during glioma progression, could be assigned to an increase in collagen, proteins, lipids, haemoglobin, and DNA levels [ 12 , 32 , 45 ]. In addition, there was a decrease in antioxidant carotenoids in grade IV compared to III, a common feature in RS cancer research studies [ 12 , 46 , 47 ].…”

Section: Discussionsupporting

confidence: 79%

Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy

et al. 2023

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionsupporting

confidence: 79%

Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Decreased lipid signals, particularly at 1450 cm −1 were found in glioma U251 cell culture and human GBM [37,100,101]. However, high lipid signals were detected in astrocytoma grade IV, recurrent glioma and after temozolomide treatment [102][103][104]. Uckermann et al also provided similar result where elevated lipid signals were detected by FTIR spectroscopy [105].…”

Section: Lipids Signal Intensities In Gliomamentioning

confidence: 75%

Lipid Alterations in Glioma: A Systematic Review

et al. 2022

View full text Add to dashboard Cite

Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients’ survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.

show abstract

“…The average survival rate from the time of diagnosis is less than twelve months, and even in the least aggressive forms, GBM causes most patients to die within two year time frame 1 , 2 . Numerous studies have focused on gaining a better understanding of different molecular mechanisms exploited by invading GBM tumour cells 3 – 5 and in recent years there has been much interest in the use of optical tools for cancer diagnostics because of their ability to detect biochemical changes occurring at the early stages of tumorigenesis 6 . Aside from being one of the most invasive and deadly human malignancies, GBM is a example model of a heterogeneous cancer 7 , 8 .…”

Section: Introductionmentioning

confidence: 99%

Glioblastoma single-cell microRaman analysis under stress treatments

Ricci

Ragonese

Gironi

et al. 2018

Sci Rep

View full text Add to dashboard Cite

Glioblastoma multiforme (GBM) is the most frequent malignant brain tumor characterized by highly heterogeneous subpopulations. In order to reveal the heterogeneous cell response, single cell analysis is an essential requirement. In this study, optical microscopy and Raman microspectroscopy were used to follow the stress response of U251 single cells adherent on a silicon substrate. Cultured cells on silicon substrate were treated with hydrogen peroxide to promote apoptosis. Under these conditions expected changes occurred after a few hours and were revealed by the reduction of cytochrome c, lipid, nucleic acid and protein Raman signals: this ensured the possibility to analyse U251 cell line as grown on Si substrate, and to monitor the response of single cells to stress conditions. As a consequence, we used microRaman to monitor the effects induced by nutrient depletion: a fast change of Raman spectra showed two different sub-populations of sensible and resistant U251 cells. Furthermore, spectral variations after DMSO addition were associated to volume changes and confirmed by morphological analysis. Thus, our results highlight the sensitivity of Raman microspectroscopy to detect rapid variations of macromolecule concentration due to oxidative stress and/or cell volume changes at the single cell level.

show abstract

Deciphering the Finger Prints of Brain Cancer Glioblastoma Multiforme from Four Different Patients by Using Near Infrared Raman Spectroscopy

Cited by 11 publications

References 19 publications

Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy

Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy

Lipid Alterations in Glioma: A Systematic Review

Glioblastoma single-cell microRaman analysis under stress treatments

Contact Info

Product

Resources

About