Abstract IA20: Neuronal activity promotes proliferation of normal and neoplastic glial cells
Bibliographic record
Abstract
Abstract Neuronal activity regulates the proliferation and differentiation of oligodendrocyte precursor cells during development and in adulthood. In the healthy brain, this results in activity-regulated plasticity of myelination and subsequent modulation of neural circuit function evident in oligodendrogenesis-dependent behavioral changes. The robust mitogenic effect of neuronal activity on normal neural precursor and oligodendroglial precursor cells, a putative cellular origin of pediatric high-grade gliomas (HGG), suggests that dysregulated or “hijacked” mechanisms of myelin plasticity might similarly promote proliferation in this devastating group of childhood brain cancers. Using in vivo and in situ optogenetic techniques together with patient-derived high-grade glioma cell cultures and xenograft models, we have demonstrated that neuronal activity similarly promotes proliferation and growth of both pediatric and adult high-grade glioma subtypes. Crucial mechanisms mediating activity-regulated high-grade glioma growth include secretion of Brain Derived Neurotrophic Factor (BDNF) and the synaptic protein neuroligin-3 (NLGN3), which induces multiple oncogenic signaling pathways together with robust changes in synaptic gene expression in glioma cells. Nlgn3 is necessary for the growth of high-grade glioma xenografts in the mouse brain, and NLGN3 expression levels in human HGG negatively correlate with patient overall survival. Thus, neuronal activity not only modulates the structure and function of the brain’s myelinated infrastructure, but neurons also play an important role in the brain tumor microenvironment, with activity-regulated secretion of NLGN3 emerging as an unexpected and therapeutically targetable mechanism underlying axon-glioma interactions and promoting neuronal activity-regulated cancer growth. References: Gibson EM, Purger D, Mount CW, Goldstein AK, Lin GL, Inema I, Miller SE, Bieri G, Zuchero JB, Barres BA, Woo PJ, Vogel H, Monje M. Neuronal activity promotes adaptive oligodendrogenesis and myelination in the mammalian brain. Science 2014;344 (6183):487; 344:1252304. Venkatesh HS, Johung T, Caretti V, Noll A, Tang Y, Nagaraja S, Gibson EM, Mount CW, Pollepalli J, Mitra SS, Woo PJ, Malenka RM, Vogel H, Bredel M, Mallick P, Monje M. Neuronal activity promotes glioma growth through neuroligin-3 secretion, Cell 2015;161(4):803-16. Venkatesh HS, Tam LT, Woo PJ, Nagaraja S, Gillespe SM, Lennon J, Ni J, Duveau DY, Morris PJ, Zhao JJ, Thomas CJ, Monje M. Targeting neuronal activity-regulated neuroligin-3 dependency for high-grade glioma, Nature 2017;549:533-37. Citation Format: Michelle Monje. Neuronal activity promotes proliferation of normal and neoplastic glial cells [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr IA20.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".