Telomerase Contributes to Fludarabine Resistance in Primary Human Leukemic Lymphocytes
Bibliographic record
Abstract
We report that Imetelstat, a telomerase inhibitor that binds to the RNA component of telomerase (hTR), can sensitize primary CLL lymphocytes to fludarabine in vitro. This effect was observed in lymphocytes from clinically resistant cases and with cytogenetic abnormalities associated with bad prognosis. Imetelstat mediated-sensitization to fludarabine was not associated with telomerase activity, but with the basal expression of Ku80. Since both Imetelstat and Ku80 bind hTR, we assessed 1) if Ku80 and Imetelstat alter each other's binding to hTR in vitro and 2) the effect of an oligonucleotide complementary to the Ku binding site in hTR (Ku oligo) on the survival of primary CLL lymphocytes exposed to fludarabine. We show that Imetelstat interferes with the binding of Ku70/80 (Ku) to hTR and that the Ku oligo can sensitize CLL lymphocytes to FLU. Our results suggest that Ku binding to hTR may contribute to fludarabine resistance in CLL lmphocytes. This is the first report highlighting the potentially broad effectiveness of Imetelstat in CLL, and the potential biological and clinical implications of a functional interaction between Ku and hTR in primary human cancer cells.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".