2072 Background: Human glioma stem cells and xenograft lines are common translational models in neuro-oncology but it has not been established if they are genetically and phenotypically comparable. This study aimed to determine if human glioma xenografts and stem cell-derived tumors had similar genotypes. Methods: Matched glioma stem cell cultures and subcutaneous xenograft lines were generated from four human glioblastoma specimens (BT114, BT116, BT120, BT132). Comparison was made between subcutaneous stem cell-derived tumors (flank) and xenografts established in nude mice. Copy number variation (CNV) and gene expression microarray studies were performed. Results: Various differences in copy number and gene expression were seen. Observed CNVs included regions within EGFR, myc, and p16 (INK). For example, EGFR copy number was two fold higher in xenografts vs. stem cell-derived tumor in one line (BT114). This difference was corroborated by western blot. Other differences included a heat shock protein homolog (DNAJA4), tetraspanin 13, and a p53 family target gene (ISG20L1). Two lines (BT114, BT116) had a greater than two fold increase in DNAJA4 expression in xenografts vs. stem cell-derived tumors (p = 0.04, 0.01). Two cell lines (BT116, BT120) had a two to eight fold increase in tetraspanin 13 expression in xenografts (p = 0.02, 0.05). However, neither copy number nor gene expression variations were consistent across all cell lines. Conclusions: Xenografts and glioma stem cell-derived tumors established from the same patient specimens have distinct genotypes. Further work is needed to establish if these differences are random or represent characteristic changes selected by different in vitro or in vivo pressures. However, these variations raise questions regarding which model is ideal for studying glioma biology, and which ones best replicate glioma characteristics in human patients.
OPTC-2. Identification of enriched genes and pathways associated to hypoxia induced migration in patient-derived glioma stem cell lines by RNAseq