Login / Signup

Autonomous rhythmic activity in glioma networks drives brain tumour growth.

David HausmannDirk C HoffmannVarun VenkataramaniErik JungSandra HorschitzSvenja K TetzlaffAmmar JabaliLing HaiTobias KesslerDaniel D AzoŕinSophie WeilAlexandros KourtesakisPhilipp SieversAntje HabelMichael O BreckwoldtMatthia A KarremanMiriam RatliffJulia M MessmerYvonne YangEkin ReyhanSusann WendlerCathrin LöbChanté MayerKatherine FigarellaMatthias OsswaldGergely SoleckiFelix SahmOlga GaraschukThomas KunerPhilipp KochMatthias SchlesnerWolfgang WickFrank Winkler
Published in: Nature (2022)
Diffuse gliomas, particularly glioblastomas, are incurable brain tumours 1 . They are characterized by networks of interconnected brain tumour cells that communicate via Ca 2+ transients 2-6 . However, the networks' architecture and communication strategy and how these influence tumour biology remain unknown. Here we describe how glioblastoma cell networks include a small, plastic population of highly active glioblastoma cells that display rhythmic Ca 2+ oscillations and are particularly connected to others. Their autonomous periodic Ca 2+ transients preceded Ca 2+ transients of other network-connected cells, activating the frequency-dependent MAPK and NF-κB pathways. Mathematical network analysis revealed that glioblastoma network topology follows scale-free and small-world properties, with periodic tumour cells frequently located in network hubs. This network design enabled resistance against random damage but was vulnerable to losing its key hubs. Targeting of autonomous rhythmic activity by selective physical ablation of periodic tumour cells or by genetic or pharmacological interference with the potassium channel KCa3.1 (also known as IK1, SK4 or KCNN4) strongly compromised global network communication. This led to a marked reduction of tumour cell viability within the entire network, reduced tumour growth in mice and extended animal survival. The dependency of glioblastoma networks on periodic Ca 2+ activity generates a vulnerability 7 that can be exploited for the development of novel therapies, such as with KCa3.1-inhibiting drugs.
Keyphrases