Telomere length and its correlation with gene mutations in chronic lymphocytic leukemia in a Korean population
Bibliographic record
Abstract
Telomere length (TL) is a prognostic indicator in Caucasian chronic lymphocytic leukemia (CLL), but its significance in Asian CLL remains unknown. To investigate the prognostic significance of TL and its correlation with cytogenetic aberrations and somatic mutations, we analyzed TL measurements at the cellular level by interphase fluorescence in situ hybridization in patients with CLL in Korea. The present study enrolled 110 patients (41 females and 69 males) diagnosed with CLL according to the World Health Organization criteria (2001-2017). TLs of bone marrow nucleated cells at the single-cell level were measured by quantitative fluorescence in situ hybridization (Q-FISH) in 71 patients. The correlations of TL with clinical characteristics, cytogenetic aberrations, genetic mutations, and overall survival were assessed. The median value of mean TL in CLL patients (T/C ratio 7.46 (range 1.19-18.14) was significantly shorter than that in the normal controls (T/C ratio 15.28 (range 8.59-24.93) (p < 0.001). Shorter TLs were associated with complex karyotypes (p = 0.030), del(11q22) (p = 0.023), presence of deletion and/or mutation in ATM and/or TP53 (p = 0.019), and SH2B3 mutation (p = 0.015). A shorter TL was correlated with lower hemoglobin levels and adverse survival (mean TL < 9.35, p = 0.021). When the proportion of cells with extremely short TLs (< 7.61) was greater than 90%, CLL patients showed poor survival (p = 0.002). Complex karyotypes, TP53 mutation, and the number of mutated genes were determined to be significant adverse variables by multivariable Cox analysis (p = 0.011, p = 0.002, and p = 0.002, respectively). TL was attrited in CLL, and attrited telomeres were correlated with adverse survival and other well-known adverse prognostic factors. We infer that TL is an independent adverse prognostic predictor in Korean CLL.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".