LGG-05. SINGLE-CELL RNA SEQUENCING OF PEDIATRIC LOW-GRADE GLIOMAS REVEALS INTRATUMORAL HETEROGENEITY

Pediatric low-grade gliomas (PLGGs) are slow growing tumors that result in neurologic defects due to both disease burden and therapeutic complications. We have previously performed FFPE bulk expression profiling on more than 150 PLGGs that revealed substantial tumor heterogeneity on the level of gene expression. One limitation of bulk expression profiling is the presence of normal cells along with tumor cells that confound the overall expression signal in a tumor. We therefore analyzed gene expression profiles of individual cells from dissociated tumors obtained by flow cytometry. Single cells from freshly dissociated PLGGs were sorted by flow cytometry into distinct populations using the glial progenitor marker A2B5. Individual A2B5-negative and A2B5-positive cells were processed by ultra-low input RNA sequencing. We analyzed between 30–283 cells per tumor. RNA-sequencing of bulk sorted populations were processed in parallel as controls. We observed high correlations between the bulk control populations and the average of the single cell populations derived from the same tumor at the RNA expression level. In all tumors analyzed, consensus clustering distinguished two major sub-populations of single cells; one predominantly composed by A2B5 positive cells and the other exclusively by A2B5 negative cells. Principle component analyses also demonstrated distinct clustering between A2B5-positive and A2B5-negative cells. These data suggest that intratumoral heterogeneity observed at the population level can be reduced by analyzing individual cells. Importantly, we can identify specific gene expression signatures that distinguish these populations to enhance our understanding of PLGGs. Single cell transcriptome profiling of freshly dissociated PLGGs revealed unique subpopulations of cells within these tumors. A2B5 positive cells generally cluster separately from A2B5 negative cells, suggesting that key differences exist between cells within individual PLGGs. Further analysis may reveal biological pathways specifically operative in PLGG tumor cells or non-transformed cells that can inform our understanding of PLGGs.