Promoter SNPs in G1/S checkpoint regulators and their impact on the susceptibility to childhood leukemia
Bibliographic record
Abstract
Mutations leading to the alteration of cell-cycle checkpoint functions are a common feature of most cancers. Because of the highly regulated nature of the cell cycle, it seems likely that variation in gene dosage of key components due to functional regulatory polymorphisms could play an important role in cancer development. Here we provide evidence of the involvement of promoter single-nucleotide polymorphisms (pSNPs) in the cyclin-dependent-kinase inhibitor genes CDKN2A, CDKN2B, CDKN1A, and CDKN1B in the etiology of childhood pre-B acute lymphoblastic leukemia (ALL). A case-control study, conducted in 240 patients with pre-B ALL and 277 healthy controls, combined with a family-based analysis using 135 parental trios, all of French-Canadian origin, were used to evaluate single-site genotypic as well as multilocus haplotypic associations for a total of 10 pSNPs. Using both study designs, we showed evidence of association between variants CDKN2A -222A, CDKN2B -593A, and CDKN1B -1608A, and an increased risk of ALL. These findings suggest that variable expression levels of cell-cycle inhibitor genes CDKN2A, CDKN2B, and CDKN1B due to regulatory polymorphisms could indeed influence the risk of childhood pre-B ALL and contribute to carcinogenesis.
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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 | 0.000 |
| 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) | 0.002 | 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".