Association between polymorphisms in TP53 and MDM2 genes and susceptibility to prostate cancer
Bibliographic record
Abstract
Tumor protein 53 (TP53), a tumor suppressor gene, is a vital cellular cancer suppressor in multicellular organisms. Murine double minute-2 (MDM2) is an oncoprotein that inhibits TP53 activity. A number of studies have examined the association of TP53 and MDM2 polymorphisms with the risk of common forms of cancer, but the findings remain inconclusive. The present study aimed to evaluate the impact of the 40‑bp insertion/deletion (I/D) polymorphism (rs3730485) in the MDM2 promoter region and the 16‑bp I/D polymorphism (rs17878362) in TP53 on the susceptibility of prostate cancer (PCa) in a sample of the Iranian population. This case‑control study included 103 patients with pathologically confirmed PCa and 142 patients with benign prostatic hyperplasia. The MDM2 40‑bp I/D and TP53 16‑bp I/D polymorphism was determined using polymerase chain reaction analysis. The results demonstrated that the MDM2 40‑bp I/D polymorphism increased the risk of PCa in a co‑dominant inheritance model [odds ratio (OR)=1.88; 95% confidence interval (CI)=1.11‑3.19; P=0.023, D/D vs. I/I], while this variant marginally increased the risk of PCa in a dominant model (OR=1.69; 95% CI=1.00‑2.83; P=0.051, I/D+D/D vs. I/I). No significant association was observed between the TP53 16-bp I/D polymorphism and PCa. In conclusion, the present study demonstrated that the 40‑bp I/D polymorphism in the MDM2 promoter increased the risk of PCa in an Iranian population. Further investigations with diverse ethnicities and larger sample sizes are required to verify these results.
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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".