Normalization of Previously Shortened Telomere Length under Treatment with Imatinib Argues against a Preexisting Telomere Length Deficit in Normal Hematopoietic Stem Cells from Patients with Chronic Myeloid Leukemia
Bibliographic record
Abstract
Telomeres are composed of TTAGGG repeats and associated proteins. In somatic cells, telomere repeats are lost with each cell division, eventually leading to genetic instability and cellular senescence. In previous studies, we described substantial and disease stage-specific telomere shortening in peripheral blood (PB) leukocytes from patients with chronic myeloid leukemia (CML). Here, we sought to determine whether age-adjusted telomere length in PB granulocytes (deltaTEL(gran)) is associated with response to treatment with the selective tyrosine kinase inhibitor imatinib. A total of 517 samples from 206 patients in chronic phase (CP), accelerated phase (AP), and blast crisis (BC) before and up to 706 days after initiation of imatinib therapy (median: 144 days) were analyzed by quantitative fluorescence in situ hybridization of interphase cells in suspension (Flow-FISH); telomere fluorescence was expressed in molecular equivalents of soluble fluorochrome units (MESF). Telomere length in samples from start of treatment up to day 144 was significantly shorter (mean +/- SE; -1.5 +/- 0.3 kMESF) compared to samples from patients treated for more than 144 days (-0.8 +/- 0.3 kMESF, p = 0.035). In patients with repeated measurements, a significant increase in telomere length under treatment was observed. Median telomere length in major remission was found to be significantly longer compared to patients without response to treatment measured either by cytogenetics (n = 246, p < 0.05), interphase FISH (n = 204, p = 0.002), or quantitative RT-PCR (n = 371, p < 0.05). In conclusion, the increase in telomere length under treatment with imatinib reflects a shift from Ph+ to Ph- cells in the PB of patients with CML.
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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) | 0.001 | 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".