Heterozygote deficiency in thymidylate synthase enhancer region polymorphism genotype distribution in Hungarian colorectal cancer patients
Bibliographic record
Abstract
Thymidylate synthase (TS) gene polymorphisms are important as prognostic factors in cancer chemotherapy, but recent results describe that the TS enhancer region (TSER) polymorphic genotypes may also modulate risk for malignancies. Two functionally important and ethnically diverse polymorphisms are present on the TS transcript, TSER, a repeat polymorphism (2 or 3 repeats; 2R, 3R) affecting TS expression, and a 6 bp ins/del polymorphism on the 3' UTR (position TS1494, del6 or ins6), which may influence mRNA stability. Hungarian population has one of the highest colorectal cancer (CRC) mortality rates in Europe, and several elevated dietary risk factors affect a large part of the population. In our study (99 primary CRC cases), population analysis of the patient group genotype frequencies revealed a departure from the Hardy-Weinberg equilibrium and significant heterozygote deficiency (p < 0.05) at the TSER locus. Despite the strong linkage between the 2 polymorphic loci, case TS1494del genotype frequencies were normally distributed, as well as the genotype frequencies of the healthy control population (n = 102), at both loci. Case-control comparison demonstrated a lower relative risk of TSER heterozygotes (OR = 0.47; CI = 0.27-0.83; p = 0.008) and a possible higher prevalence of the 3R3R&ins6/del6 in the CRC group. The observation that heterozygotes are those less susceptible for CRC in the Hungarian population may support the possibility of 2 different pathways in which TS may play a role in colorectal carcinogenesis, probably nutrient (or folate)-dependently. The lack of similar genotype effect seen with TS1494del polymorphism and the increased presence of one genotype combination (3R3R&ins6/del6) in the patient group suggest a possible TS haplotype effect influencing CRC risk.
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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) | 0.002 | 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".