Gene Regulatory Network topology governs resistance and treatment escape in glioma stem-like cells
Poor prognosis and drug resistance in glioblastoma (GBM) manifests from heterogeneity and treatment-induced shifts in phenotypic states of tumor cells, including dedifferentiation to glioma stem-like cells (GSCs). This rare tumorigenic cell subpopulation is inherently resistant to temozolomide, undergoes proneural-to-mesenchymal transition (PMT) to evade therapy, and thereby drives recurrence. Through inference of transcriptional regulatory networks (TRNs) of patient-derived GSCs (PD-GSCs) at single-cell resolution, we demonstrate how topology of transcription factor interactions drives distinct trajectories of cell state transitions of susceptible and resistant PD-GSCs in response to cytotoxic drug treatment. By experimentally testing TRN simulation-based predictions, we show that drug treatment drives surviving cells of a PD-GSC along a trajectory of intermediate states, akin to a bottleneck in gene expression space, exposing vulnerability to potentiated killing by sequential addition of siRNA or a second drug targeting transcriptional programs governing non-genetic plasticity of a PD-GSC. Thus, our findings demonstrate an approach to uncover and use TRN topology of a PD-GSC to rationally predict combinatorial and sequential treatments that block treatment escape and acquired resistance in GBM.