Association of <i>p53 Arg72Pro</i> polymorphism and HPV status with the initiation, progression, and development of cervical cancer (CC): A meta-analysis.
Bibliographic record
Abstract
1597 Background: CC develops through progression from normal cervical epithelium through squamous intra-epithelial lesions (SILs) to cancer. CC is classically associated with oncogenic human papillomavirus (HPV). Yet, not all CC patients demonstrate HPV infection at diagnosis. HPV+ and HPV– subsets of CC patients may thus represent distinct entities. HPV binds to P53, promoting its degradation; the Arg variant of p53 Arg72Pro binds more ardently to HPV than the Pro variant. Although there have been meta-analyses of Arg72Pro in CC risk, none has evaluated the relationship between Arg72Pro and HPV status together. We hypothesize that p53 Arg72Pro modifies aspects of the carcinogenic process in HPV+ (but not HPV-) subsets of CC. Methods: Pubmed/Embase databases identified 1494 potential studies; 51 were eligible and included. Separate analyses were performed to evaluate CC risk (CC vs normal), initiation of cancer (SIL vs normal), and progression towards cancer (CC vs SIL), by HPV status. Pooled odds ratios (pOR) were generated using RevMan 5.1 software. Results: p53 Arg72Pro was not associated with CC risk in either HPV+ or HPV- patient subsets (pORs 0.92; 95%CI, 0.6-1.3 and pORs 1.07; 95%CI, 0.7-1.7, respectively). Similarly, there was no association with the initiation of disease (SIL vs normal): pORs 0.96; 95%CI, 0.7-1.3 (HPV+ subset); 1.11; 95%CI, 0.9-1.4 (HPV- subset). There was no association with disease progression from SIL to CC in the HPV- subset (pOR, 0.98; 95%CI, 0.7-1.4). However, in the HPV+ subset, comparing the progression from SIL through to CC, there was strong and significant association: pOR, 1.37; 95%CI, 1.2-1.6 (p=4.0x10E-4), with no evidence of heterogeneity (I2 = 0%) or bias (by funnel plot). Sensitivity analyses demonstrated similarly significant results, even after taking into account differing quality of methodological designs and type of biological sample analyzed (tumour vs. blood) of the underlying studies. Associations were mainly restricted to Caucasian studies. Conclusions: In this meta-analysis, the Arg variant of p53 Arg72Pro was associated with progression of SIL to CC only in HPV+ subsets, but not to disease initiation or risk of CC.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.026 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".