Modulation of the oncogenic potential of β‐catenin by the subcellular distribution of plakoglobin
Bibliographic record
Abstract
Plakoglobin (Pg) and beta-catenin are homologous proteins that function in cell-cell adhesion and signaling. The cadherin-associated form of these proteins mediates adhesion, whereas the cytosolic/nuclear form has a signaling role. Despite their interactions with common cellular partners, beta-catenin has a well-documented oncogenic potential while Pg has a less characterized tumor suppressor activity. We showed previously that Pg overexpression in Pg-deficient SCC9 cells (SCC9-Pg-WT) induced Bcl-2 expression and inhibited apoptosis. To assess the exact role of Pg in Bcl-2 expression, we generated and characterized SCC9 transfectants expressing Pg with a restricted cytoplasmic (Pg-NES) or nuclear (Pg-NLS) distribution. We show that Bcl-2 was expressed regardless of Pg localization, although its level was substantially lower in SCC9-Pg-NLS cells. Bcl-2 expression coincided with increased nuclear beta-catenin levels (Pg-NES) or a decrease in the level of total and nuclear beta-catenin associated with N-cadherin and alpha-catenin (Pg-WT and -NLS) cells. Bcl-2 expression also was induced in SCC9 cells overexpressing beta-catenin. In contrast, SCC9 cells expressing mutant Pg proteins, unable to interact with N-cadherin and alpha-catenin, had noticeably lower Bcl-2 levels. Our data suggest that Bcl-2 expression is induced by beta-catenin and modulated by Pg. We show that the inhibition of beta-catenin-dependent TCF transactivation had no effect on Bcl-2 levels, suggesting that induction of Bcl-2 expression by beta-catenin and its modulation by Pg may involve factors other than, or in addition, to, TCF. These results provide a possible mechanism for the tumor suppressor activity of Pg via its role as a regulator of the oncogenic potential beta-catenin.
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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".