Genomic characterization of chronic lymphocytic leukemia (CLL) in radiation-exposed Chornobyl cleanup workers
Bibliographic record
Abstract
BACKGROUND: Chronic lymphocytic leukemia (CLL) was the predominant leukemia in a recent study of Chornobyl cleanup workers from Ukraine exposed to radiation (UR-CLL). Radiation risks of CLL significantly increased with increasing bone marrow radiation doses. Current analysis aimed to clarify whether the increased risks were due to radiation or to genetic mutations in the Ukrainian population. METHODS: A detailed characterization of the genomic landscape was performed in a unique sample of 16 UR-CLL patients and age- and sex-matched unexposed general population Ukrainian-CLL (UN-CLL) and Western-CLL (W-CLL) patients (n = 28 and 100, respectively). RESULTS: Mutations in telomere-maintenance pathway genes POT1 and ATM were more frequent in UR-CLL compared to UN-CLL and W-CLL (both p < 0.05). No significant enrichment in copy-number abnormalities at del13q14, del11q, del17p or trisomy12 was identified in UR-CLL compared to other groups. Type of work performed in the Chornobyl zone, age at exposure and at diagnosis, calendar time, and Rai stage were significant predictors of total genetic lesions (all p < 0.05). Tumor telomere length was significantly longer in UR-CLL than in UN-CLL (p = 0.009) and was associated with the POT1 mutation and survival. CONCLUSIONS: No significant enrichment in copy-number abnormalities at CLL-associated genes was identified in UR-CLL compared to other groups. The novel associations between radiation exposure, telomere maintenance and CLL prognosis identified in this unique case series provide suggestive, though limited data and merit further investigation.
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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 | 0.000 | 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 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".