Characterisation of cytokine secretion in malignant gliomas

Abel, Peter orcid iconORCID: 0000-0002-5221-7653 (2017) Characterisation of cytokine secretion in malignant gliomas. Doctoral thesis, University of Central Lancashire.

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Abstract

Cytokines are proteins produced by cells of the immune system. The working hypothesis of the thesis is to show that the lymphocytes and glial cells in Glioblastoma Multiformae patients have an altered pattern of secretion of cytokines compared with low-grade and non-cancerous patients. Lymphocyte subset analysis was performed using flow cytometry. Serum specimens taken from both high and low grade glioma patients were analysed with samples taken from control patients with no history of cancer. Cerebro-spinal fluid was analysed from high-grade glioma patients. Comparisons of high grade pre-surgery serum samples, high grade post-surgery samples, control pre-surgery samples and control post-surgery samples were included. The analysis was completed utilising a luminex immunoassay. This technology is able to measure 34 cancer-associated analytes simultaneously. Immunohistochemistry of candidate biomarkers was done using primary tumour tissue. The results show that there were significant differences in several analytes in the sera and CSF of the different groups. These were follistatin, fibroblast growth factor (FGF), granulocyte – colony stimulating factor (G-CSF), soluble human epidermal growth factor receptor 2 neural (sHER2neu), soluble interleukin-6 receptor alpha (sIL-6R alpha), platelet-derived growth factor - AABB (PDGF-AABB), platelet and endothelial cell adhesion molecule (PECAM-1), stem cell factor (SCF), prolactin, soluble vascular endothelial growth factor receptor 1 (sVEGFR-1) and urokinase plasminogen activator (uPA). The data also show that tumour tissue revealed increased expression of follistatin and G-CSF with little expression of prolactin. In conclusion, these results suggest that potential candidate biomarkers can be used to enable diagnosis of glioma and moreso to distinguish between different grades of glioma using a panel of biomarkers.


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