FAK modulates glioblastoma stem cell energetics via regulation of glycolysis and glutamine oxidation
Bibliographic record
Abstract
Glycolysis and the tricarboxylic acid cycle (TCA) cycle are reprogrammed in cancer cells to meet bioenergetic and biosynthetic demands, including by engagement with the extracellular matrix (ECM). However, the mechanisms by which the ECM engagement reprograms core energy metabolism is still unknown. We showed that the canonical cell-ECM adhesion protein focal adhesion kinase (FAK, also known as PTK2) and, specifically, its kinase activity, is driving cellular energetics. Using a mouse stem cell model of glioblastoma, we showed that deletion of the FAK gene simultaneously inhibits glycolysis and glutamine oxidation, increases mitochondrial fragmentation, elevates phosphorylation of the mitochondrial protein MTFR1L at serine residue 235 (S235) and triggers a mesenchymal-to-epithelial transition. These metabolic and structural changes arise through altered contractility of actomyosin, as shown by myosin light chain type II (MYL2, also known as MLC2) phosphorylated (p) at S19. This process can be reversed by Rho-kinase (ROCK) inhibitors revealing mechanotransduction pathway control of both mitochondrial dynamics and glutamine oxidation. FAK-dependent metabolic programming is associated with regulation of cell migration, invasive capacity and tumour growth in vivo. Our work describes a previously unrecognised FAK-ROCK axis that couples mechanical cues to the rewiring of energy metabolism, linking cell shape, mitochondrial function and malignant behaviour.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".