NI-82 * DIFFUSION AND CONVENTIONAL MR IMAGING GENOMIC BIOMARKER SIGNATURE FOR EGFR MUTATION IDENTIFICATION IN GLIOBLASTOMA

Abstract

PURPOSE: To create a diffusion and conventional MR imaging biomarker signature in order to identify those Glioblastoma (GBM) patients with EGFR mutation status. EGFR is the cell-surface receptor for members of the epidermal growth factor family(EGF-family)of extracellular protein ligands,a subfamily of receptor tyrosine kinases. EGFR gene expression is present in 40% of GBM patients.Identification of EGFR as an oncogene has led to the development of anticancer therapeutics directed against EGFR.Thus,a non-invasive imaging surrogate that predicts EGFR mutation status will help stratify patients into therapy and clinical trials. MATERIALS AND METHODS: We identified 80 treatment-naive patients from TCGA who had both gene and microRNA expression profiles including the EGFR mutation status and pretreatment MRI from The Cancer Imaging Archive (TCIA). Qualitative VASARI imaging features for these 80 patients were assessed by 3 independent neuroradiologists and consensus was reached. Quantitative volumetric analysis was done in the 3D Slicer software 3.6 using segmentation module.Fluid Attenuated Inversion Recovery (FLAIR)was used for segmentation of the edema and post-contrast T1 weighted imaging(T1W1)for segmentation of enhancement and necrosis.Diffusion was analyzed in Olea Sphere 2.3 and Conventional FLAIR/post- contrast T1WI was registered to DWI/ADC maps. ADC, FLAIR, T1 Gadolinium enhancement values were measured using the ROI based method, in the perilesional edema/non-enhancing tumor and the enhancing tumor zones, dividing the perilesional edema/non-enhancing tumor into 3 zones each of 1 cm width, 3 ROI measurements were taken from each zone. Each quantitative feature was correlated to EGFR mutation status to create the imaging biomarker signature predictive of EGFR mutation status. Survival analysis was done in all cases. RESULTS: A diffusion and conventional MR imaging biomarker signature was created that predicted EGFR mutation status. CONCLUSIONS: EGFR mutation status plays an important role in predictive and prognostic stratification of patients with GBM. The identification of a non-invasive biomarker signature as a surrogate for EGFR mutation can help stratify patients in specific therapy and predict response to therapy.