Pyruvate Kinase Inhibits Proliferation during Postnatal Cerebellar Neurogenesis and Suppresses Medulloblastoma Formation
Bibliographic record
Abstract
Abstract Aerobic glycolysis supports proliferation through unresolved mechanisms. We have previously shown that aerobic glycolysis is required for the regulated proliferation of cerebellar granule neuron progenitors (CGNP) and for the growth of CGNP-derived medulloblastoma. Blocking the initiation of glycolysis via deletion of hexokinase-2 (Hk2) disrupts CGNP proliferation and restricts medulloblastoma growth. Here, we assessed whether disrupting pyruvate kinase-M (Pkm), an enzyme that acts in the terminal steps of glycolysis, would alter CGNP metabolism, proliferation, and tumorigenesis. We observed a dichotomous pattern of PKM expression, in which postmitotic neurons throughout the brain expressed the constitutively active PKM1 isoform, while neural progenitors and medulloblastomas exclusively expressed the less active PKM2. Isoform-specific Pkm2 deletion in CGNPs blocked all Pkm expression. Pkm2-deleted CGNPs showed reduced lactate production and increased SHH-driven proliferation. 13C-flux analysis showed that Pkm2 deletion reduced the flow of glucose carbons into lactate and glutamate without markedly increasing glucose-to-ribose flux. Pkm2 deletion accelerated tumor formation in medulloblastoma-prone ND2:SmoA1 mice, indicating the disrupting PKM releases CGNPs from a tumor-suppressive effect. These findings show that distal and proximal disruptions of glycolysis have opposite effects on proliferation, and that efforts to block the oncogenic effect of aerobic glycolysis must target reactions upstream of PKM. Cancer Res; 77(12); 3217–30. ©2017 AACR.
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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 | 0.001 |
| 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".