Association of XRCC4 codon 247 polymorphism with oral cancer susceptibility in Taiwan.
Bibliographic record
Abstract
BACKGROUND: The DNA repair gene XRCC4, an important caretaker of overall genome stability, is thought to play a major role in the development of human carcinogenesis. However, the association of the polymorphic variants of XRCC4 with oral cancer susceptibility has never been reported. MATERIALS AND METHODS: In this hospital-based case-control study, the association of XRCC4 codon 247 (rs3734091), G-1394T (rs6869366), intron 7 (rs28360317) and intron 7 (rs1805377) polymorphisms with oral cancer risk in a Central Taiwanese population was investigated. In total, 318 patients with oral cancer and 318 age- and gender-matched healthy controls recruited from the China Medical Hospital in Central Taiwan were genotyped. RESULTS: A significantly different distribution was found in the frequency of the XRCC4 codon 247 genotype, but not the XRCC4 G-1394T or intron 7 genotypes, between the oral cancer and control groups. A/C heterozygosity at XRCC4 codon 247 conferred a significant (2.04-fold) increased risk of oral cancer. As for XRCC4 G-1394T and intron 7 polymorphisms, there was no difference in distribution between the oral cancer and control groups. Gene-environment interactions with smoking, but not with betel quid chewing or alcohol consumption, were significant for XRCC4 codon 247 polymorphism. The XRCC4 codon 247 A/C genotype in association with smoking conferred an increased risk of 3.44 (95% confidence interval = 1.24-9.60) for oral cancer. CONCLUSION: Our results provide the first evidence that the heterozygous A allele of the XRCC4 codon 247 may be associated with the development of oral cancer and may be a novel useful marker for primary prevention and anticancer intervention.
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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 | 0.001 | 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".