Cdx2 Polymorphism Affects the Activities of Vitamin D Receptor in Human Breast Cancer Cell Lines and Human Breast Carcinomas
Bibliographic record
Abstract
Vitamin D plays a role in cancer development and acts through the vitamin D receptor (VDR). It regulates the action of hormone responsive genes and is involved in cell cycle regulation, differentiation and apoptosis. VDR is a critical component of the vitamin D pathway and different common single nucleotide polymorphisms have been identified. Cdx2 VDR polymorphism can play an important role in breast cancer, modulating the activity of VDR. The objective of this study is to assess the relationship between the Cdx2 VDR polymorphism and the activities of VDR in human breast cancer cell lines and carcinomas breast patients. Cdx2 VDR polymorphism and antiproliferative effects of vitamin D treatment were investigated in a panel of estrogen receptor-positive (MCF7 and T-47D) and estrogen receptor-negative (MDA-MB-231, SUM 159PT, SK-BR-3, BT549, MDA-MB-468, HCC1143, BT20 and HCC1954) human breast cancer cell lines. Furthermore, the potential relationship among Cdx2 VDR polymorphism and a number of biomarkers used in clinical management of breast cancer was assessed in an ad hoc set of breast cancer cases. Vitamin D treatment efficacy was found to be strongly dependent on the Cdx2 VDR status in ER-negative breast cancer cell lines tested. In our series of breast cancer cases, the results indicated that patients with variant homozygote AA were associated with bio-pathological characteristics typical of more aggressive tumours, such as ER negative, HER2 positive and G3. Our results may suggest a potential effect of Cdx2 VDR polymorphism on the efficacy of vitamin D treatment in aggressive breast cancer cells (estrogen receptor negative). These results suggest that Cdx2 polymorphism may be a potential biomarker for vitamin D treatment in breast cancer, independently of the VDR receptor expression.
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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".