Transient telomerase inhibition alters cell cycle kinetics
Bibliographic record
Abstract
ABSTRACT Telomerase is the ribonucleoprotein reverse transcriptase that catalyzes the synthesis of telomeres at the ends of linear human chromosomes and contributes to proper telomere-loop (T-loop) formation. Formation of the T-loop, an obligate step before cell division can proceed, requires the generation of a 3’-overhang on the G-rich strand of telomeric DNA via telomerase or C-strand specific nucleases. Here, we discover telomerase activity is critical for efficient cell cycle progression using transient chemical inhibition by the telomerase inhibitor imetelstat. Telomerase inhibition caused changes in cell cycle kinetics and increased the proportion of cells in G2 phase, suggesting delayed clearance through this checkpoint. Investigating the possible contribution of unstructured telomere ends to these cell cycle distribution changes, we observed that imetelstat treatment induced γH2AX DNA damage foci in a subset of telomerase-positive cells but not telomerase-negative primary human fibroblasts. Chromatin-immunoprecipitation with γH2AX antibodies demonstrated imetelstat treatment-dependent enrichment of this DNA damage marker at telomeres. Notably, the effects of telomerase inhibition on cell cycle profile alterations were abrogated by pharmacological inhibition of the DNA-damage-repair transducer ATM. Additionally, imetelstat potentiation of etoposide, a DNA-damaging drug that acts preferentially during S/G2 phases of the cell cycle, also depended on functional ATM signaling. Our results suggest that telomerase inhibition delays the removal of ATM-dependent DNA damage signals from telomeres in telomerase-positive cancer cells. This demonstrates for the first time that telomerase activity directly facilitates the progression of the cell cycle through modulation of transient telomere dysfunction signals.
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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".