Wide-ranging DNA methylation differences of primary trophoblast cell populations and derived cell lines: implications and opportunities for understanding trophoblast function†
Bibliographic record
Abstract
Difficulties associated with long-term culture of primary trophoblasts have proven to be a major hurdle in their functional characterization. In order to circumvent this issue, several model cell lines have been established over many years using a variety of different approaches. Due to their differing origins, gene expression profiles and behaviour in vitro, different model lines have been utilized to investigate specific aspects of trophoblast biology. However, generally speaking, the molecular mechanisms underlying functional differences remain unclear. In this study, we profiled genome-scale DNA methylation in primary first trimester trophoblast cells and seven commonly used trophoblast-derived cell lines in an attempt to identify functional pathways differentially regulated by epigenetic modification in these cells. We identified a general increase in DNA promoter methylation levels in four choriocarcinoma (CCA)-derived lines and transformed HTR-8/SVneo cells, including hypermethylation of several genes regularly seen in human cancers, while other differences in methylation were noted in genes linked to immune responsiveness, cell morphology, development and migration across the different cell populations. Interestingly, CCA-derived lines show an overall methylation profile more similar to unrelated solid cancers than to untransformed trophoblasts, highlighting the role of aberrant DNA methylation in CCA development and/or long-term culturing. Comparison of DNA methylation and gene expression in CCA lines and cytotrophoblasts revealed a significant contribution of DNA methylation to overall expression profile. These data highlight the variability in epigenetic state between primary trophoblasts and cell models in pathways underpinning a wide range of cell functions, providing valuable candidate pathways for future functional investigation in different cell populations. This study also confirms the need for caution in the interpretation of data generated from manipulation of such pathways in vitro.
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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".