Spatially Resolved Whole Transcriptome Analysis of Histologically-Characterized Tissue Microarray of Patient-Matched Primary and Recurrent Glioblastomas to Identify Underlying Mechanisms of Treatment Resistance

Abstract

Glioblastoma multiforme (GBM) is a lethal CNS malignancy. Radiation therapy increases overall survival, but tumors often recur in high-radiation dose regions. Additionally, recent investigations have underscored the importance of intra-tumoral heterogeneity as a driver of GBM biology. The purpose of this investigation is to characterize transcriptome differences in primary and recurrent GBM patient clinical samples using a digital spatial profiling approach to better appreciate treatment resistance mechanisms. To address the lack of understanding of molecular mechanisms of resistance in GBM, patient-matched primary and recurrent GBM pathological specimens were identified within the brain tissue biorepository and tissue cores were selected for generation of a tissue microarray (TMA). Hematoxylin and eosin staining with histomorphological (cellular tumor, pseudopalisading necrosis, invasive edge, and perivascular inflammation) scoring were performed in a blinded fashion for every core. This array was then molecularly characterized using digital spatial profiling of the transcriptome. Quality assurance including filtering of lowly expressed genes followed by downstream analyses of the data were performed using the manufacturer's recommended methods within their Bioconductor library. Gene Set Enrichment Analysis (GSEA) was then performed on the ranked gene lists. After recommended filtering, 6171 genes and 248 regions of interest remained for downstream analysis representing 22 unique patients across four different tumor histomorphological types. Significance testing revealed 679 genes that were differentially expressed between primary and recurrent tumor samples (at FDR<1%). On GSEA analysis, the chromosomal positional locus that contains genes most strongly up-regulated is 12q14, a locus that was previously identified as genomically amplified in multiple patient-derived xenograft lines after radiation selection. Additionally, recurrent tumors display a transcriptional profile more similar to the mesenchymal subtype, whereas primary tumors have a more classical transcriptional phenotype. The epithelial-to-mesenchymal transition pathway is particularly strongly up-regulated in recurrent tumors. Recurrent selection at previously identified genomic loci and molecular pathways underscores a possible conserved set of pathways for treatment resistance. This analysis has yielded a set of gene and molecular pathways that will guide future work in our lab targeting treatment resistance using novel therapeutics and radiation techniques in GBM. Future directions include assessing the feasibility of mapping these clinical samples onto our previously generated panel of comprehensively characterized patient-derived xenograft lines.