Functional promoter SNPs in cell cycle checkpoint genes
Bibliographic record
Abstract
A substantial number of genes mutated in human cancers encode components of the cell cycle processes. As the G1/S transition in the cell cycle is a finely regulated biological process, we hypothesized that sequence variations in the promoter region of the related genes might indeed lead to abnormal expression, thus predisposing the individuals carrying these genetic variants to cancer. In this report, we screened the promoter regions of 16 cell cycle checkpoint genes for DNA variants and assessed the functional impact of these promoter region single nucleotide polymorphisms (pSNPs) by combining in silico analysis and in vitro functional assays. We identified 127 pSNPs including 90 with predicted impact on putative binding sites of known transcription factors. Eleven pSNPs were selected for electrophoresis mobility shift assays because of their association with predicted gains of binding sites, and nine pSNPs showed differential allelic shifts in at least one cell line tested. Following the subcloning of the promoter regions into a gene reporter system, we found that at least four promoter haplotypes associated with CCND1, E2F1, HDAC1 and RB1 significantly influenced transcriptional activity in an allele-specific manner. Although the biological significance of these observations still remains to be demonstrated, the expected variability of expression levels in key cell cycle components might influence individual's risk of cancer.
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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) | 0.000 | 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".