Fazzari, E.; Azizad, D. J.; Li, M. X.; Ge, W.; Baisiwala, S.; Cadet, D.; Nano, P. R.; Kan, R. L.; Perryman, T.; Tum, H. A.; Tse, C.; Wick, B.; Arguelles, C. V.; Patel, K. S.; Liau, L. M.; Prins, R. M.; Nathanson, D. A.; Bhaduri, A.

Extensive molecular profiling has revealed profound heterogeneity in glioblastoma (GBM), yet how cellular lineages organize over time to govern tumor propagation and therapeutic response remains poorly understood. Existing single-cell approaches define transcriptional states but provide limited insight into how clonal dynamics shape functional tumor behavior. Here, we integrate high-complexity combinatorial DNA barcoding with single-cell transcriptomics in direct-from-patient IDH1-wild-type GBM, enabling lineage-resolved mapping of progenitor organization in a human microenvironmental context. Across 235,155 malignant cells from nine tumors, clonal relationships form reproducible lineage tracks in which distinct progenitor populations give rise to specific differentiated cell types, revealing that tumor growth is sustained by multiple non-redundant progenitors rather than a single dominant population. These progenitors exhibit distinct propensities for self-renewal, fate restriction, and cross-compartment interactions, collectively accounting for the full spectrum of tumor states. Using this lineage-resolved framework, we identify complementary drug targets in distinct progenitor compartments and demonstrate that hierarchy-informed combination therapies disrupt progenitor-progenitor interactions and reshape lineage output. These findings move beyond descriptive heterogeneity to define functional logic underlying GBM propagation and establish a generalizable framework for rational, cell type-specific combinatorial therapies.