Institute for Systems Biology, Seattle, WA, USA.
Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA, USA.
Sci Adv. 2024 Jun 7;10(23):eadj7706. doi: 10.1126/sciadv.adj7706.
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.
胶质母细胞瘤（GBM）的预后不良和耐药性可能源于细胞异质性和治疗诱导的肿瘤细胞表型状态变化，包括去分化为神经胶质瘤干细胞（GSCs）。这种罕见的肿瘤发生细胞亚群对替莫唑胺耐药，经历向神经前体细胞-间质转化（PMT）以逃避治疗，并驱动复发。通过在单细胞分辨率下推断患者来源的 GSCs（PD-GSCs）的转录调控网络（TRN），我们展示了转录因子相互作用网络的拓扑结构如何驱动对细胞状态转变具有不同轨迹的 PD-GSCs 对细胞毒性药物治疗的耐药或敏感。通过基于 TRN 模拟实验测试预测，我们表明药物治疗沿着中间状态的轨迹驱动存活的 PD-GSCs，从而使它们容易受到增强的 siRNA 或靶向治疗诱导的转录程序的第二种药物的杀伤，这些程序控制非遗传细胞可塑性。我们的研究结果表明了一种揭示 TRN 拓扑结构并利用它合理预测组合治疗以破坏 GBM 获得性耐药的方法。
