Activation of endocrine-related gene expression in placental choriocarcinoma cell lines following DNA methylation knock-down
Bibliographic record
Abstract
Increasingly, placental DNA methylation is assessed as a factor in pregnancy-related complications, yet the transcriptional impact of such findings is not always clear. Using a proliferative in vitro placental model, the effect of DNA methylation loss on gene activation was evaluated at a number of genes selected for being differentially methylated in pre-eclampsia-associated placentae in vivo. We aimed to determine whether reduced DNA methylation at specific loci was associated with transcriptional changes at the corresponding gene, thus providing mechanistic underpinnings for previous clinical findings and to assess the degree of transcriptional response amongst our candidate genes. BeWo and JEG3 choriocarcinoma cells were exposed to 1 μM 5-Aza-2'-deoxycytidine (5-Aza-CdR) or vehicle control for 48 h, and re-plated and cultured for a further 72 h in normal media before cells were harvested for RNA and DNA. Bisulphite pyrosequencing confirmed that DNA methylation was reduced by ∼30-50% points at the selected loci studied in both cell lines. Gene activation, measured by qRT-PCR, was highly variable and transcript specific, indicating differential sensitivity to DNA methylation. Most notably, loss of DNA methylation at the leptin (LEP) promoter corresponded to a 200-fold and 40-fold increase in LEP expression in BeWo and JEG3 cells, respectively (P < 0.01). Transcripts of steroidogenic pathway enzymes CYP11A1 and HSD3B1 were up-regulated ∼40-fold in response to 5-Aza-CdR exposure in BeWo cells (P < 0.01). Other transcripts, including aromatase (CYP19), HSD11B2, inhibin (INHBA) and glucocorticoid receptor (NR3C1) were more moderately, although significantly, affected by loss of associated DNA methylation. These data present a mixed effect of DNA methylation changes at selected loci supporting cautionary interpretation of DNA methylation results in the absence of functional data.
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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 | 0.001 |
| 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".