NIMG-44. NON-INVASIVE ADVANCED IMAGING METRICS PROVIDE POTENTIAL BIOMARKERS FOR GBM BIOLOGICAL HETEROGENEITY AND IMMUNE LANDSCAPE VARIANCE. (11th November 2019)

• Record Type: Journal Article
• Authors: Kersch, Cymon; Muldoon, Leslie; Fu, Rochelle; Claunch, Cheryl; Neuwelt, Edward; Barajas, Ramon
• Is Part Of: Neuro-oncology. Volume 21(2019)Supplement 6
• Page Start: vi171
• Page End: vi171
• Publication Date: 2019-11-11
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noz175.714
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: BACKGROUND: Treatment of glioblastoma multiforme (GBM) is complicated by extensive tumor heterogeneity. We hypothesize that transcriptomic analysis of brain tumor regions with different magnetic resonance imaging (MRI) characteristics will define specific biological processes, providing a non-invasive method for tumor characterization and stratification. METHODS: Previously at the University of California San Francisco, treatment naïve GBM tissue from gadolinium contrast enhancing lesion (CEL) and non-enhancing lesion (NCEL) regions were stereotactically sampled; prior to resection, relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) were determined. The tissue samples were characterized by immunohistochemistry and assessed for gene expression by microarray analysis. We correlated gene expression patterns in the CEL, NCEL, and non-tumor gliotic brain samples with multimodal physiological imaging metrics and immunohistochemical phenotypes. Gene expression networks were probed using Gene Set Enrichment Analysis. Key immunologic genes were examined individually. RESULTS: Samples with differing MRI and histological phenotypes demonstrated transcriptomic variance reflecting distinct biological networks. We found significant differences in immune pathways, with immune gene signature prominent in CEL areas, moderate in NCEL and low in gliotic non-tumor brain. Within homogenously enhancing areas of CEL and NCEL there was underlying heterogeneity detectable by variable rCBV, ADC and histological phenotypes, which correlate with differing gene expression profiles indicative of biological and immunological tumor microenvironments. Increasing rCBV was correlated with an anti-inflammatory immune response in the CEL and a pro-inflammatory immune response in the NCEL. ADC was negatively correlated with cell cycle and immune networks in CEL, while NCEL ADC was positively correlated with immune processes. GBM samples with the mesenchymal molecular subtype had the greatest immune response. CONCLUSIONS: Multimodal MRI features identify regionally diverse transcriptomic-based biological and immunological phenotypes in GBM. We propose that imaging genomics provides a technique for localizing biological processes and tumor immune microenvironments across space and time in GBM.