p53-dependent integration of telomere and growth factor deprivation signals
Bibliographic record
Abstract
Ectopically expressed hTERT enables p16(INK4A)(-) human mammary epithelial cells to proliferate in the absence of growth factors, a finding that has led to the hypothesis that hTERT has growth regulatory properties independent of its role in telomere maintenance. We now show that telomerase can alter the growth properties of cells indirectly through its role in telomere maintenance, without altering growth stimulatory pathways. We find that telomere dysfunction, indicated by 53BP1/phosphorylated histone H2AX foci at chromosome ends, is present in robustly proliferating human mammary epithelial cells long before senescence. These foci correlate with increased levels of active p53. Ectopic expression of hTERT reduces the number of foci and the level of active p53, thereby decreasing sensitivity to growth factor depletion, which independently activates p53. The continuous presence of hTERT is not necessary for this effect, indicating that telomere maintenance, rather than the presence of the enzyme itself, is responsible for the increased ability to proliferate in the absence of growth factors. Our findings provide a previously unrecognized mechanistic explanation for the observation that ectopically expressed hTERT conveys growth advantages to cells, without having to postulate nontelomeric functions for the enzyme.
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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) | 0.002 | 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".