p75 Neurotrophin Receptor Cleavage by α- and γ-Secretases Is Required for Neurotrophin-mediated Proliferation of Brain Tumor-initiating Cells
Bibliographic record
Abstract
Malignant gliomas are highly invasive, proliferative, and resistant to treatment. Previously, we have shown that p75 neurotrophin receptor (p75NTR) is a novel mediator of invasion of human glioma cells. However, the role of p75NTR in glioma proliferation is unknown. Here we used brain tumor-initiating cells (BTICs) and show that BTICs express neurotrophin receptors (p75NTR, TrkA, TrkB, and TrkC) and their ligands (NGF, brain-derived neurotrophic factor, and neurotrophin 3) and secrete NGF. Down-regulation of p75NTR significantly decreased proliferation of BTICs. Conversely, exogenouous NGF stimulated BTIC proliferation through α- and γ-secretase-mediated p75NTR cleavage and release of its intracellular domain (ICD). In contrast, overexpression of the p75NTR ICD induced proliferation. Interestingly, inhibition of Trk signaling blocked NGF-stimulated BTIC proliferation and p75NTR cleavage, indicating a role of Trk in p75NTR signaling. Further, blocking p75NTR cleavage attenuated Akt activation in BTICs, suggesting role of Akt in p75NTR-mediated proliferation. We also found that p75NTR, α-secretases, and the four subunits of the γ-secretase enzyme were elevated in glioblastoma multiformes patients. Importantly, the ICD of p75NTR was commonly found in malignant glioma patient specimens, suggesting that the receptor is activated and cleaved in patient tumors. These results suggest that p75NTR proteolysis is required for BTIC proliferation and is a novel potential clinical target.
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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) | 0.001 | 0.000 |
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".