Progressive neuronal network reorganisation in glioblastoma drives pathological activity in vitro

Glioblastoma (GBM) is the most aggressive primary brain tumour and is frequently accompanied by severe neurological symptoms, including epilepsy and cognitive impairment. Neurological symptoms often persist after surgical resection, indicating that GBM induces durable and self-sustaining changes in the surrounding neuronal networks. However, the mechanisms by which GBM reshapes network structure and function in the tumour periphery remain poorly understood. We present a compartmentalised in vitro platform enabling long-term coculture of iPSC-derived neurons and primary GBM cells to investigate these changes. Placed on high-density microelectrode arrays, the platform permits longitudinal electrophysiological recordings at single-neuron resolution. Using effective network inference, we find that GBM drives a reproducible structural progression: first toward a hyperconnected, hub-dominated architecture, then a collapse of community structure accompanied by a widespread neuron loss. This evolving structure shapes population dynamics, constraining features such as network burst rate and instantaneous synchrony. The reorganisation also carries computational consequences: signal propagation becomes progressively redundant and synergistic rather than unique. As a result, neurons lose the capacity to encode distinct input combinations independently, and the repertoire of accessible network states contracts. Together, these findings reframe GBM as a driver of neuronal network reorganisation rather than uniform hyperexcitability, and establish a compartmentalised, single-neuron-resolution platform for the longitudinal observation, dissection, and ultimately targeting of the network processes that underlie disease progression.