Effects of DNA Methylation on Galectin-3 Expression in Pituitary Tumors
Bibliographic record
Abstract
Galectin-3 (Gal-3), a beta-galactoside-binding protein is expressed in a specific cell-type manner in pituitary tumors. Here we questioned the mechanism of Gal-3 expression in pituitary tumors, by using methylation-specific PCR and DNA sequence analyses to analyze the methylation status of the promoter region of the LGALS3 gene. DNA analysis of a human pituitary tumor, breast carcinoma cell lines, and thyroid carcinoma cell lines showed that in cells expressing Gal-3 protein, the LGALS3 gene was unmethylated, whereas in Gal-3 null cells, the promoter of the LGALS3 gene was methylated. Treatment of cells with 30 mumol/L 5-aza-2'-deoxycytidine induced Gal-3 mRNA and protein expression. Among pituitary tumors, 30% (7/23), mainly in follicle-stimulating hormone/luteinizing hormone-producing (38%) and null cell (57%) adenomas, the promoter of the LGALS3 was found to be methylated and silenced, although prolactin- and adrenocorticotropic hormone-producing tumors, which were unmethylated, expressed the Gal-3 protein. These results show for the first time that Gal-3 expression is regulated in part by promoter methylation in pituitary as well as in other tumors. Because it is functionally involved in cancer progression and metastasis, Gal-3 may serve as a possible therapeutic target in the treatment of pituitary tumors.
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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 | 0.000 |
| 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".