Lack of Association Between BsmI and FokI Polymorphisms of the VDR Gene and Sporadic Colorectal Cancer in a Romanian Cohort—A Preliminary Study
Bibliographic record
Abstract
Colorectal cancer (CRC) is a major public health problem worldwide, currently ranking third in cancer incidence and second in mortality. Multiple genes and environmental factors have been involved in the complex and multifactorial process of CRC carcinogenesis. VDR is an intracellular hormone receptor expressed in both normal epithelial and cancer colon cells at various levels. Several VDR gene polymorphisms, including FokI and BsmI, have been evaluated for their possible association with CRC susceptibility. The aim of our study was to investigate these two SNPs for the first time in Romanian CRC patients. FokI (rs228570 C>T) and BsmI (rs1544410 A>G) were genotyped by real-time polymerase chain reaction (RT-PCR) in 384-well plates using specific TaqMan predesigned probes on a ViiA™ 7 RT-PCR System. A total of 441 subjects (166 CRC patients and 275 healthy controls) were included. No statistically significant difference was observed between CRC patients and controls when we compared the wild-type genotype with heterozygous and mutant genotypes for both FokI (OR 0.85, 95% CI: 0.56-1.28; OR 0.95, 95% CI: 0.51-1.79, respectively) and BsmI (OR 0.97, 95% CI: 0.63-1.49; OR 1.10, 95% CI: 0.65-1.87, respectively) or in the dominant and recessive models. Also, we compared allele frequencies, and no correlation was found. Moreover, the association between these SNPs and the tumor site, TNM stage, and histological type was examined separately, and there was no statistically significant difference. In conclusion, our study did not show any association between FokI and BsmI SNPs and CRC susceptibility in a Romanian population. Further studies including a larger number of samples are needed to improve our knowledge regarding the influence of VDR polymorphism on CRC susceptibility.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".