Tuberous Sclerosis Complex Suppression in Cerebellar Development and Medulloblastoma: Separate Regulation of Mammalian Target of Rapamycin Activity and p27Kip1 Localization
Bibliographic record
Abstract
During development, proliferation of cerebellar granule neuron precursors (CGNP), candidate cells-of-origin for the pediatric brain tumor medulloblastoma, requires signaling by Sonic hedgehog (Shh) and insulin-like growth factor (IGF), the pathways of which are also implicated in medulloblastoma. One of the consequences of IGF signaling is inactivation of the mammalian target of rapamycin (mTOR)-suppressing tuberous sclerosis complex (TSC), comprised of TSC1 and TSC2, leading to increased mRNA translation. We show that mice, in which TSC function is impaired, display increased mTOR pathway activation, enhanced CGNP proliferation, glycogen synthase kinase-3 alpha/beta (GSK-3 alpha/beta) inactivation, and cytoplasmic localization of the cyclin-dependent kinase inhibitor p27(Kip1), which has been proposed to cause its inactivation or gain of oncogenic functions. We observed the same characteristics in wild-type primary cultures of CGNPs in which TSC1 and/or TSC2 were knocked down, and in mouse medulloblastomas induced by ectopic Shh pathway activation. Moreover, Shh-induced mouse medulloblastomas manifested Akt-mediated TSC2 inactivation, and the mutant TSC2 allele synergized with aberrant Shh signaling to increase medulloblastoma incidence in mice. Driving exogenous TSC2 expression in Shh-induced medulloblastoma cells corrected p27(Kip1) localization and reduced proliferation. GSK-3 alpha/beta inactivation in the tumors in vivo and in primary CGNP cultures was mTOR-dependent, whereas p27(Kip1) cytoplasmic localization was regulated upstream of mTOR by TSC2. These results indicate that a balance between Shh mitogenic signaling and TSC function regulating new protein synthesis and cyclin-dependent kinase inhibition is essential for the normal development and prevention of tumor formation or expansion.
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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 | 0.001 | 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".