Reversible Dissociation of Mitochondrial Complex V Balances Anabolic and Energy-Generating Needs in Cancer
Bibliographic record
Abstract
Abstract Cancer cell metabolic re-programming provides the excess energy and anabolic precursors necessary to sustain uncontrolled growth. This is partly mediated by the Warburg effect, whereby glucose is converted into ATP and a subset of these anabolic substrates. Concurrently, mitochondrial mass and ATP production decline in most tumors. This raises the question of how increased supplies of glycolysis-derived anabolic substrates can be balanced with those generated by the TCA cycle. Using primary murine liver cancers and cell lines, we show that this can be explained by the dissociation of mitochondrial Complex V (CV or ATP synthase) into its component and functionally-independent F o and F 1 domains. This occurs as a result of marked reductions in MT-ATP6, a CV subunit that stabilizes the F o -F 1 association. Serving as a proton pore, F o maintains a normal mitochondrial membrane potential without generating ATP, thus allowing the TCA cycle, electron transport chain and anaplerotic reactions to function at high levels. Concurrently, free F 1 functions as an ATPase to prevent excessive ATP accumulation. The uncoupling of TCA cycle-derived anabolic substrate production from membrane hyperpolarization and ATP synthesis by a smaller population of more efficient mitochondria allows TCA cycle-generated anabolic precursors to match those generated via glycolysis.
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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".