The role of phosphatidylcholine and choline metabolites to cell proliferation and survival
Bibliographic record
Abstract
The reorganization of metabolic pathways in cancer facilitates the flux of carbon and reducing equivalents into anabolic pathways at the expense of oxidative phosphorylation. This provides rapidly dividing cells with the necessary precursors for membrane, protein and nucleic acid synthesis. A fundamental metabolic perturbation in cancer is the enhanced synthesis of fatty acids by channeling glucose and/or glutamine into cytosolic acetyl-CoA and upregulation of key biosynthetic genes. This lipogenic phenotype also extends to the production of complex lipids involved in membrane synthesis and lipid-based signaling. Cancer cells display sensitivity to ablation of fatty acid synthesis possibly as a result of diminished capacity to synthesize complex lipids involved in signaling or growth pathways. Evidence has accrued that phosphatidylcholine, the major phospholipid component of eukaryotic membranes, as well as choline metabolites derived from its synthesis and catabolism, contribute to both proliferative growth and programmed cell death. This review will detail our current understanding of how coordinated changes in substrate availability, gene expression and enzyme activity lead to altered phosphatidylcholine synthesis in cancer, and how these changes contribute directly or indirectly to malignant growth. Conversely, apoptosis targets key steps in phosphatidylcholine synthesis and degradation that are linked to disruption of cell cycle regulation, reinforcing the central role that phosphatidylcholine and its metabolites in determining cell fate.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".