Resident, PhD Candidate University of Toronto / University of Manitoba
Introduction: Glioblastoma (GBM) is the most common and fatal form of primary brain malignancy in adults. A major barrier in our understanding of this disease is the difficulty in tracking the tumour development, treatment and inevitable recurrence in real-time. We adopted a novel approach that combines the principles of classic cellular barcoding with CRISPR/Cas-9 technology and single-cell RNA sequencing known as continuous lineage tracing to address this problem.
Methods: Patient derived glioma initiating cell lines were engineered with expressed DNA barcodes with CRISPR/Cas-9 targets. An intracranial xenograph model was then created through injection into NOD scid-mice. Following successful engraftment of lineage-engineered lines, tumours are harvested and sent for single cell RNA sequencing. Clonal and relationships are surmised through identification of expressed barcodes, and cells were characterized by their transcriptional profiles. Phylogenetic lineage trees are created using lineage reconstructive algorithms to define cell fitness and expansion.
Results: Our work has revealed a significant amount of intra-clonal cell state heterogeneity, suggesting that tumour cells engage in phenotype switching prior to therapeutic intervention. We defined a consistent transcriptional pattern for tumor engraftment and in vivo clonal advantage associated with FOXO signalling. Phylogenetic lineage trees allowed us to define a gene signature of cell fitness, which correlate strongly with published neural-mesenchymal and developmental-injury response phenotypes. GBMs exist along a transcriptional gradient between undifferentiated but “high-fit” cells and terminally differentiated, “low-fit” cells, lending further evidence that these tumors consist of pools of cells that are capable of recapitulating the tumour microenvironment after treatment due to their ability to undergo cell state transition
Conclusion : We have successfully engineered a set of glioma initiating tumours with a novel lineage tracing technique, creating a powerful tool for real-time tracing of tumour growth through the analysis of a unique set of highly detailed singe-cell RNA sequencing data with associated clonal and phylogenetic relationships. Arresting cell state transition through the targeting of genes associated with evolutionary fitness may on day provide tools that will allow us to halt tumor progression and recurrence.
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