TET2 repression by androgen hormone regulates global hydroxymethylation status and prostate cancer progression
Bibliographic record
Abstract
Modulation of epigenetic patterns has promising efficacy for treating cancer. 5-Hydroxymethylated cytosine (5-hmC) is an epigenetic mark potentially important in cancer. Here we report that 5-hmC is an epigenetic hallmark of prostate cancer (PCa) progression. A member of the ten–eleven translocation (TET) proteins, which catalyse the oxidation of methylated cytosine (5-mC) to 5-hmC, TET2, is repressed by androgens in PCa. Androgen receptor (AR)-mediated induction of the miR-29 family, which targets TET2, are markedly enhanced in hormone refractory PCa (HRPC) and its high expression predicts poor outcome of PCa patients. Furthermore, decreased expression of miR-29b results in reduced tumour growth and increased TET2 expression in an animal model of HRPC. Interestingly, global 5-hmC modification regulated by miR-29b represses FOXA1 activity. A reduction in 5-hmC activates PCa-related key pathways such as mTOR and AR. Thus, DNA modification directly links the TET2-dependent epigenetic pathway regulated by AR to 5-hmC-mediated tumour progression. The epigenetic mark 5-hmC alters gene expression and is known to be regulated by TET proteins. Here, the authors show that 5-hmC and TET2 are reduced in prostate cancer via androgen receptor-dependent miRNA expression and are inversely correlated with prognosis.
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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) | 0.002 | 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".