High concentration calcitriol induces endoplasmic reticulum stress related gene profile in breast cancer cells
Bibliographic record
Abstract
Calcitriol, the active form of vitamin D, is known for its anticancer properties including induction of apoptosis as well as the inhibition of angiogenesis and metastasis. Understanding the mechanisms of action for calcitriol will help with the development of novel treatment strategies. Since vitamin D exerts its cellular actions via binding to its receptor and by altering expressions of a set of genes, we aimed to evaluate the effect of calcitriol on transcriptomic profile of breast cancer cells. We previously demonstrated that calcitriol alters endoplasmic reticulum (ER) stress markers, therefore in this study we have focused on ER-stress-related genes to reveal calcitriols action on these genes in particular. We have treated breast cancer cell lines MCF-7 and MDA-MB-231 with previously determined IC50 concentrations of calcitriol and evaluated the transcriptomic alterations via microarray. During analysis, only genes altered by at least 2-fold with a P value < 0.05 were taken into consideration. Our findings revealed an ER-stress-associated transcriptomic profile induced by calcitriol. Induced genes include genes with a pro-survival function (NUPR1, DNAJB9, HMOX1, LCN2, and LAMP3) and with a pro-death function (CHOP (DDIT3), DDIT4, NDGR1, NOXA, and CLGN). These results suggest that calcitriol induces an ER-stress-like response inducing both pro-survival and pro-death transcripts in the process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".