Chromosome Arm-Specific Long Telomeres: A New Clonal Event in Primary Chronic Myelogenous Leukemia Cells
Bibliographic record
Abstract
Previous studies demonstrated that critically shortened telomere lengths correlate with the chromosome instability in carcinogenesis. However, little has been noticed regarding the correlation of long telomeres at specific chromosomes with malignant disorders. We studied relative telomere lengths (RTLs) for individual chromosomes using the quantitative fluorescence in situ hybridization technique in a cohort of 32 patients with chronic myeloid leukemia (CML) and 32 normal samples. We found that telomeres at some specific chromosome arms remain well maintained or even lengthened in a high frequency (27/32) of leukemia cases. In particular, 10 chromosome arms, 4q, 5p, 7q, 11p, 13p, 13q, 14p, 15p, 18p, and Xp, with long telomeres were consistently identified in different samples, and six of them (4q, 5p, 13p, 13q, 14p, and Xp) with relatively long telomeres were also observed in normal samples, but they appeared in lower occurrence rate and shorter RTL than in CML samples. Our results strongly indicate the presence of a special leukemia cell population, or a clone, originated from a common progenitor that is characterized with chromosome arm-specific long telomeres. We suggest that relatively long telomeres located at key chromosomes could be preferentially maintained or further elongated during the early stage of malignant transformation.
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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 | 0.001 | 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".