Deciphering the topological landscape of glioma using a network theory framework

Glioma stem cells have been recognized as key players in glioma recurrence and therapeutic resistance, presenting a promising target for novel treatments. However, the limited understanding of the role glioma stem cells play in the glioma hierarchy has drawn controversy and hindered research translation into therapies. Despite significant advances in our understanding of gene regulatory networks, the dynamics of these networks and their implications for glioma remain elusive. This study employs a systemic theoretical perspective to integrate experimental knowledge into a core endogenous network model for glioma, thereby elucidating its energy landscape through network dynamics computation. The model identifies two stable states corresponding to astrocytic-like and oligodendrocytic-like tumor cells, connected by a transition state with the feature of high stemness, which serves as one of the energy barriers between astrocytic-like and oligodendrocytic-like states, indicating the instability of glioma stem cells in vivo. We also obtained various stable states further supporting glioma's multicellular origins and uncovered a group of transition states that could potentially induce tumor heterogeneity and therapeutic resistance. This research proposes that the transition states linking both glioma stable states are central to glioma heterogeneity and therapy resistance. Our approach may contribute to the advancement of glioma therapy by offering a novel perspective on the complex landscape of glioma biology.