Gene regulatory network topology governs resistance and treatment escape in glioma stem-like cells

Menée sur des cellules souches cancéreuses issues de glioblastomes de patients et menée à l'aide de simulations in silico, cette étude met en évidence le rôle de l'architecture et de la dynamique des réseaux de régulation transcriptionnelle dans la plasticité phénotypique et la résistance thérapeutique des cellules souches cancéreuses

Résumé en anglais

Poor prognosis and drug resistance in glioblastoma (GBM) can result from cellular heterogeneity and treatment-induced shifts in phenotypic states of tumor cells, including dedifferentiation into glioma stem-like cells (GSCs). This rare tumorigenic cell subpopulation resists temozolomide, undergoes proneural-to-mesenchymal transition (PMT) to evade therapy, and drives recurrence. Through inference of transcriptional regulatory networks (TRNs) of patient-derived GSCs (PD-GSCs) at single-cell resolution, we demonstrate how the topology of transcription factor interaction networks drives distinct trajectories of cell-state transitions in PD-GSCs resistant or susceptible to cytotoxic drug treatment. By experimentally testing predictions based on TRN simulations, we show that drug treatment drives surviving PD-GSCs along a trajectory of intermediate states, exposing vulnerability to potentiated killing by siRNA or a second drug targeting treatment-induced transcriptional programs governing nongenetic cell plasticity. Our findings demonstrate an approach to uncover TRN topology and use it to rationally predict combinatorial treatments that disrupt acquired resistance in GBM. Gene regulatory networks drive glioma stem-like cell drug response and drug-induced cell-state transitions leading to resistance.