AUTOANTIBODIES IN GLIOMA PATIENTS: IMMUNE BIOMARKERS FOR IDENTIFICATION OF LOW GRADE TUMOURS. Issue 11 (9th October 2013) - Coleman, James; Sedehizadeh, Saam; Chapman, Caroline; Shafei, Rachelle; Thorpe, Alison; Robertson, John; Maddison, Paul
Abstract : Gliomas comprise an aggressive group of heterogeneous tumours with poor 5–year survival: vague initial symptoms predispose to delayed diagnosis with subsequent poor prognosis. Invasive biopsy and current diagnostic challenges emphasise the need to identify novel, specific and non–invasive early–diagnostic biomarkers. The presence of tumour–associated antigens (TAAs) in patients' sera long before symptom onset suggests that detecting autoantibodies directed to these antigens may be useful in early tumour diagnosis. We developed high throughput antigen production techniques to produce a total of 22 recombinant TAAs. Sera from adult patients with glioma (n=60) and age, sex and smoking status matched normal controls were collected. AdditonalAdditional control patients with Multiple Sclerosis with or without intercurrent relapse were recruited (n=18). Analysis of sera by ELISA tested for the presence of IgG autoantibodies against all 22 TAAs. Autoantibody responses towards SOX11, SSX–2, HER–2–ICD and MMP–7 were significantly raised in glioma patients compared with matched controls. A six antigen diagnostic panel including the four significant antigens in addition to SOX9 and SOX13 elicited 31% sensitivity with 94% specificity (n=60). Additionally, a low–grade glioma (n=17) panel, comprising significantly raised antibodies to p53 and GFAP, demonstrated 29% sensitivity and 98% specificity: antibodies to these two TAA were not present in patients with high–grade glioma (n=43) (P<0.05). Autoantibodies to some TAAs are significantly raised in individuals with glioma compared with matched controls. Validation of these results in a larger prospective clinical cohort study will enable us to identify specific antibody profiles which will distinguish a low grade from high grade tumour, and predict the timescale of a patient's low grade glioma high grade transformation.