Abstracts

Rationale: Tumor associated seizures (TAS) are common and cause significant morbidity. As advances in tumor treatments increase life expectancy, morbidity from TAS becomes increasingly burdensome. Underlying mechanisms of TAS, crucial in developing new therapies, is hindered by the multifactorial nature of TAS, as both imaging and genomic characteristics play key roles. Genomic imaging is an emerging field that capitalizes on both these individual factors and their interactions. We describe genomic imaging tools which allow mapping of brain regions where gene expression has significant influence on TAS.Methods: Patients underwent a volumetric contrast enhanced T1 weighted MRI scan. Tumors were manually segmented from MRI with margins delineated by the area of contrast enhancement. Images were transformed into a standardized coordinate space based on the Talairach atlas. A 9-set gene expression profile predicting long-term survivors was obtained from RNA derived from formalin-fixed paraffin embedded tissue. For each candidate gene, to assess the localizing value of the tumors causing seizures, a T- statistic map was calculated. For each patient, the entire tumor mask was assigned the gene expression value associated with that patient after normalizing the expression to a baseline of zero. At each voxel, the T-statistic of the gene expression difference between patients with and without TAS was calculated. Signal clusters were obtained through a 6-connectivity model. Significance of the clusters was obtained using the threshold-free cluster enhancement (TFCE) technique, then through a resampling method repeated 5000 times. Results: A total of 81 patients were studied, of whom 34 patients (42%) experienced preoperative TAS. Tumor volume was smaller (30.6 vs 60.1 cubic cm, p<0.001) and median survival higher in patients with TAS (49.0 vs 32.8 months, p < 0.05). Although the expression of only OLIG2 was significantly lower in patients with TAS in a groupwise analysis, genomic imaging analysis revealed regions with significantly higher regional expression of GPNMB and LGALS3, and with significantly lower expression of OLG2, RTN1, and IGFPB2 in patients with TAS. Conclusions: As tumor location has strong influence on epileptogenicity in only certain areas of the brain, the influence of gene expression is also likely to be regional. The regions where gene expression is of greatest interest are in areas where tumor location has minimal upon influence TAS. Not accounting for this regional variability will miss detection of genes with strong influence in a limited region of the brain. We have demonstrated this regional variability and possibility for enhanced power in this limited 9-gene set using genomic imaging techniques. Regional variability should be evaluated with any genomic or molecular markers of solid brain lesions.