Vitamin D Receptor Expression in Normal, Premalignant, and Malignant Human Lung Tissue
Bibliographic record
Abstract
BACKGROUND: There is a strong interest in identifying chemopreventive agents that might help decrease the burden of lung cancer. The active metabolite of vitamin D, 1,25-dihydroxycholecalciferol (calcitriol), has been shown to have antiproliferative effects in several tumor types, mediated by the vitamin D receptor (VDR). This is the first comprehensive survey of VDR expression in a series of human lung tissues, including normal and premalignant central airway biopsies and lung tumors. METHODS: Immunohistochemical expression of nuclear and cytoplasmic VDR was examined in 180 premalignant or malignant bronchial biopsies from bronchoscopy of 78 high-risk individuals at the Roswell Park Cancer Institute and also in 63 tumor samples from 35 lung cancer patients from the University of Chicago Hospitals. Associations between clinicopathologic data and VDR expression were examined. RESULTS: VDR expression was present in many samples. In biopsies, VDR was commonly detected throughout the full epithelial layer. Most histologically normal (60%, 53 of 88) and metaplastic (61%, 39 of 64) samples had moderate to high nuclear intensity; dysplastic samples mostly had low nuclear intensity (10 of 18, 55%). In tumor samples, 62% (38 of 61) were lacking cytoplasmic VDR, with nuclear expression present in 79%(49 of 62). Analysis of all samples revealed a positive linear trend between proportion of samples with greater nuclear than cytoplasmic intensity and increasing histologic grade (P < 0.01). CONCLUSIONS: VDR expression spanned the lung carcinogenesis spectrum. Nuclear expression was similar across various histologies, whereas cytoplasmic expression decreased with increasing histologic grade. These results indicate that there is potential for the use of calcitriol as a chemopreventive agent against the development of lung cancer.
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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 | 0.000 |
| 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) | 0.001 | 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".