Overexpression of TET dioxygenases in seminomas associates with low levels of DNA methylation and hydroxymethylation
Bibliographic record
Abstract
Germ cell tumors and particularly seminomas reflect the epigenomic features of their parental primordial germ cells (PGCs), including genomic DNA hypomethylation and expression of pluripotent cell markers. Because the DNA hypomethylation might be a result of TET dioxygenase activity, we examined expression of TET1-3 enzymes and the level of their product, 5-hydroxymethylcytosine (5hmC), in a panel of histologically characterized seminomas and non-seminomatous germ cell tumors. Expression of TET dioxygenase mRNAs was quantified by real-time PCR. TET1 expression and the level of 5hmC were examined immunohistochemically. Quantitative assessment of 5-methylcytosine (5mC) and 5hmC levels was done by the liquid chromatography-mass spectroscopy technique. We found highly increased expression of TET1 dioxygenase in most seminomas and strong TET1 staining in seminoma cells. Isocitrate dehydrogenase 1 and 2 mutations were not detected, suggesting the enzymatic activity of TET1. The levels of 5mC and 5hmC in seminomas were found decreased in comparison to non-seminomatous germ cell tumors and healthy testicular tissue. We propose that TET1 expression should be studied as a potential marker of seminomas and mixed germ cell tumors and we suggest that elevated expression of TET dioxygenase enzymes is associated with the maintenance of low DNA methylation levels in seminomas. This "anti-methylator" phenotype of seminomas is in contrast to the CpG island methylator phenotype (CIMP) observed in a fraction of tumors of various types.
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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".