Abstract
BACKGROUND: A major barrier in our understanding of glioblastoma (GBM) is the difficulty in tracking tumour development 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 apply a phylogenetic approach to studying tumour development. METHODS: Patient derived glioma initiating cell lines were engineered with expressed DNA barcodes with CRISPR/Cas-9 targets and subsequently implanted to create an intracranial xenograft model. Tumors were sent for single cell RNA sequencing; clonal relationships were surmised through identification of expressed barcodes, and cells were characterized by their transcriptional profiles. Phylogenetic lineage trees were created utilizing 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 tumour engraftment and in vivo clonal advantage. Phylogenetic lineage trees allowed us to define gene signatures of both cell fitness and expansion, 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: cells with highly fitness appear to represent cells undergoing cell state transition. CONCLUSION: We successfully employed a novel lineage tracing technique in GBM, creating a powerful tool for real-time tracing of tumour growth through the analysis of a unique set of highly detailed transcriptional data with associated clonal and phylogenetic relationships.