DNA Repair Gene Polymorphisms and Susceptibility to Urothelial Carcinoma in a Southeastern European Population
Bibliographic record
Abstract
Single nucleotide polymorphisms (SNPs) in DNA repair genes may predispose to urothelial carcinoma of the bladder (UCB). This study focused on three specific SNPs in a population with high exposure to environmental carcinogens including tobacco and alcohol. A case-control study design was used to assess for presence of XPC PAT +/−, XRCC3 Thr241Met, and ERCC2 Lys751Gln DNA repair gene SNPs in peripheral blood from patients with UCB and healthy individuals. One hundred patients and equal number of healthy subjects were enrolled. The XPC PAT +/+ genotype was associated with a 2-fold increased risk of UCB (OR = 2.16; 95%CI: 1.14–4; p = 0.01). The −/+ and +/+ XPC PAT genotypes were more frequently present in patients with multiple versus single tumors (p = 0.01). No association was detected between ERCC2 Lys751Gln genotypes/alleles, and risk for developing UCB. Presence of the XRCC3 TT genotype (OR = 0.14; 95%CI:0.07–0.25; p < 0.01) and of the T allele overall (OR = 0.26; 95%CI:0.16–0.41; p < 0.01) conferred a protective effect against developing UCB. The XPC PAT −/+ and XRCC3 Thr241Met SNPs are associated with predisposition to UCB. The XPC PAT −/+ SNP is also an indicator of bladder tumor multiplicity, which might require a more individualized surveillance and treatment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".