Post-Transcriptional Regulation of Connexin43 in H-Ras-Transformed Cells
Bibliographic record
Abstract
Connexin43 (Cx43) expression is lost in cancer cells and many studies have reported that Cx43 is a tumor suppressor gene. Paradoxically, in a cellular NIH3T3 model, we have previously shown that Ha-Ras-mediated oncogenic transformation results in increased Cx43 expression. Although the examination of transcriptional regulation revealed essential regulatory elements, it could not solve this paradox. Here we studied post-transcriptional regulation of Cx43 expression in cancer using the same model in search of novel gene regulatory elements. Upon Ras transformation, both Cx43 mRNA stability and translation efficiency were increased. We investigated the role of Cx43 mRNA 3' and 5'Untranslated regions (UTRs) and found an opposing effect; a 5'UTR-driven positive regulation is observed in Ras-transformed cells (NIH-3T3(Ras)), while the 3'UTR is active only in normal NIH-3T3(Neo) cells and completely silenced in NIH-3T3(Ras) cells. Most importantly, we identified a previously unknown regulatory element within the 3'UTR, named S1516, which accounts for this 3'UTR-mediated regulation. We also examined the effect of other oncogenes and found that Ras- and Src-transformed cells show a different Cx43 UTRs post-transcriptional regulation than ErbB2-transformed cells, suggesting distinct regulatory pathways. Next, we detected different patterns of S1516 RNA-protein complexes in NIH-3T3(Neo) compared to NIH-3T3(Ras) cells. A proteomic approach identified most of the S1516-binding proteins as factors involved in post-transcriptional regulation. Building on our new findings, we propose a model to explain the discrepancy between the Cx43 expression in Ras-transformed NIH3T3 cells and the data in clinical specimens.
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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 | 0.001 |
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".