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Helen S. Bell, Stephen B. Wharton, H. Anne Leaver and Ian R. Whittle

Object. Intracranial infusions of gamma-linolenic acid (GLA), an essential fatty acid, have been used as an adjuvant therapy following malignant glioma resection; however, little is known about the dose response of glioma cells to this therapy. In this in vitro study the authors address this important pharmacological question.

Methods. Glioma spheroids derived from U87, U373, MOG-G-CCM, and C6 cell lines were grown in collagen gel and exposed to a range of GLA concentrations (0–1 mM) for 5 days. The diameter of glioma spheroids was measured, the apoptotic index was assessed using both the terminal deoxynucleotidyl transferase—mediated deoxyuridine triphosphate nick-end labeling technique and cell morphological testing, and the levels of proliferating cell nuclear antigen were also measured.

Conclusions. The dose—response patterns were similar for all four glioma spheroids. Low concentrations of GLA (< 100 µM) increased both apoptosis and proliferation with a net increase in tumor growth and invasion, whereas high-dose GLA (> 100 µM) significantly impaired spheroid cell growth. The proliferative effects of low-dose GLA could be a hazard in the clinical treatment of malignant glioma; however, because of the low toxicity of GLA against normal cells, local delivery of millimolar doses of GLA could significantly reduce tumor size.

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Laurent J. Livermore, Martin Isabelle, Ian M. Bell, Oliver Edgar, Natalie L. Voets, Richard Stacey, Olaf Ansorge, Claire Vallance and Puneet Plaha


Raman spectroscopy is a biophotonic tool that can be used to differentiate between different tissue types. It is nondestructive and no sample preparation is required. The aim of this study was to evaluate the ability of Raman spectroscopy to differentiate between glioma and normal brain when using fresh biopsy samples and, in the case of glioblastomas, to compare the performance of Raman spectroscopy to predict the presence or absence of tumor with that of 5-aminolevulinic acid (5-ALA)–induced fluorescence.


A principal component analysis (PCA)–fed linear discriminant analysis (LDA) machine learning predictive model was built using Raman spectra, acquired ex vivo, from fresh tissue samples of 62 patients with glioma and 11 glioma-free brain samples from individuals undergoing temporal lobectomy for epilepsy. This model was then used to classify Raman spectra from fresh biopsies from resection cavities after functional guided, supramaximal glioma resection. In cases of glioblastoma, 5-ALA–induced fluorescence at the resection cavity biopsy site was recorded, and this was compared with the Raman spectral model prediction for the presence of tumor.


The PCA-LDA predictive model demonstrated 0.96 sensitivity, 0.99 specificity, and 0.99 accuracy for differentiating tumor from normal brain. Twenty-three resection cavity biopsies were taken from 8 patients after supramaximal resection (6 glioblastomas, 2 oligodendrogliomas). Raman spectroscopy showed 1.00 sensitivity, 1.00 specificity, and 1.00 accuracy for predicting tumor versus normal brain in these samples. In the glioblastoma cases, where 5-ALA–induced fluorescence was used, the performance of Raman spectroscopy was significantly better than the predictive value of 5-ALA–induced fluorescence, which showed 0.07 sensitivity, 1.00 specificity, and 0.24 accuracy (p = 0.0009).


Raman spectroscopy can accurately classify fresh tissue samples into tumor versus normal brain and is superior to 5-ALA–induced fluorescence. Raman spectroscopy could become an important intraoperative tool used in conjunction with 5-ALA–induced fluorescence to guide extent of resection in glioma surgery.

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Oral Presentations

2010 AANS Annual Meeting Philadelphia, Pennsylvania May 1–5, 2010