Evaluation of breast cancer susceptibility loci on 2q35, 3p24, 17q23 and FGFR2 genes in Taiwanese women with breast cancer.
Bibliographic record
Abstract
AIM: Breast cancer is the most common cancer in women. In recent years, mounting evidence has identified the possibility that 2q35, 3p24, 17q23 and fibroblast growth factor receptor 2 (FGFR2) may be genetic susceptibility loci for breast cancer. This study aimed to evaluate the association of four polymorphic genotypes in these loci with breast cancer in Taiwanese women. PATIENTS AND METHODS: Eighty-eight patients with breast cancer and 70 controls without breast cancer were selected. Polymorphic variants of 2q35-rs13387042, 3p24-rs4973768, 17q23-rs650490 and FGFR2-rs2981578 were analyzed to test for their association with breast cancer susceptibility. The 2q35, 17q23 and FGFR2 polymorphisms were detected using polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) and the 3p24 polymorphism was detected using an amplification-created restriction site method. RESULTS: The distribution of genotypes of 2q35 were significantly different between the breast cancer group and the control group (p=0.035), while the distributions for 3p24, 17q23, and FGFR2 did not produce statistically significant differences (p>0.05). In addition, allele A of 2q35 conferred a higher risk for breast cancer risk than allele G (odds ratio, OR=2.95, 95% confidence interval, CI=1.29-6.71, p=0.008). Furthermore, the genotypic distribution of 2q35 was not significantly different among patients with different tumor stages, or from different specimen type. CONCLUSION: The 2q35 allele A may be a potential biomarker for breast cancer risk, but further confirmation is required to determine its role in breast carcinogenesis. Blood samples can be used for determining the genotypes for 2q35-rs13387042 in patients for risk of breast cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".