Insights into cAMP‐dependent molecular mechanisms regulating expression and function of <i>LGALS16</i> gene in choriocarcinoma JEG‐3 cells
Bibliographic record
Abstract
The human choriocarcinoma cell line JEG-3 offers a valuable model to study galectin-16 gene (LGALS16) expression and functions in the context of placental cell differentiation and cancer cell biology. Recent evidence indicates that cAMP-mediated signaling pathways might be responsible for the upregulation of LGALS16; however, the underlying mechanisms are unknown. Here, we employed biochemical inhibitors of the cAMP cascade and CRISPR/Cas9 engineered cells to assess regulatory patterns and associations between cAMP-induced trophoblast differentiation and LGALS16 expression in JEG-3 cells. The expression of LGALS16 was significantly upregulated in parallel with human chorionic gonadotropin beta (CGB), a biomarker of syncytiotrophoblast differentiation, in response to 8-Br-cAMP. Inhibition of p38 MAPK and EPAC significantly altered LGALS16 expression during differentiation, while PKA inhibition failed to change LGALS16 and CGB3/5 expression in our cell model. The CRISPR/Cas9 LGALS16 knockout cell pool expressed a significantly lower amount of CGB3/5, a reduced level of CGB protein, and an unaltered cell growth rate in response to 8-Br-cAMP in comparison with wild-type JEG-3 cells. Collectively, these findings suggest that LGALS16 is required for the trophoblast-like differentiation of JEG-3 cells, and its expression is mediated through p38 MAPK and EPAC signaling pathway branches.
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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) | 0.001 | 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".