Transient Telomerase Inhibition with Imetelstat Impacts DNA Damage Signals and Cell-Cycle Kinetics
Bibliographic record
Abstract
Abstract Telomerase is the ribonucleoprotein reverse transcriptase that catalyzes the synthesis of telomeres at the ends of linear 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, it is discovered that telomerase activity is critical for efficient cell-cycle progression using transient chemical inhibition by the telomerase inhibitor, imetelstat. Telomerase inhibition changed 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, it was 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. Also, imetelstat potentiation of etoposide, a DNA-damaging drug that acts preferentially during S–G2 phases of the cell cycle, depends on functional ATM signaling. Thus, telomerase inhibition delays the removal of ATM-dependent DNA damage signals from telomeres in telomerase-positive cancer cells and interferes with cell cycle progression through G2. Implications: This study demonstrates that telomerase activity directly facilitates the progression of the cell cycle through modulation of transient telomere dysfunction signals. Mol Cancer Res; 16(8); 1215–25. ©2018 AACR.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".