Plakoglobin restores tumor suppressor activity of p53<sup>R175H</sup> mutant by sequestering the oncogenic potential of β‐catenin
Bibliographic record
Abstract
Tumor suppressor/transcription factor p53 is mutated in over 50% of all cancers. Some mutant p53 proteins have not only lost tumor suppressor activities but they also gain oncogenic functions ( GOF ). One of the most frequently expressed GOF p53 mutants is Arg175His (p53 R175H ) with well‐documented roles in cancer development and progression. Plakoglobin is a cell adhesion and signaling protein and a paralog of β‐catenin. Unlike β‐catenin that has oncogenic function through its role in the Wnt pathway, plakoglobin generally acts as a tumor/metastasis suppressor. We have shown that plakoglobin interacted with wild type and a number of p53 mutants in various carcinoma cell lines. Plakoglobin and mutant p53 interacted with the promoter and regulated the expression of several p53 target genes. Furthermore, plakoglobin interactions with p53 mutants restored their tumor suppressor/metastasis activities in vitro. GOF p53 mutants induce accumulation and oncogenic activation of β‐catenin. Previously, we showed that one mechanism by which plakoglobin may suppress tumorigenesis is by sequestering β‐catenin's oncogenic activity. Here, we examined the effects of p53 R175H expression on β‐catenin accumulation and transcriptional activation and their modifications by plakoglobin coexpression. We showed that p53 R175H expression in plakoglobin null cells increased total and nuclear levels of β‐catenin and its transcriptional activity. Coexpression of plakoglobin in these cells promoted β‐catenin's proteasomal degradation, and decreased its nuclear levels and transactivation. Wnt/β‐catenin targets, c‐ MYC and S100A4 were upregulated in p53 R175H cells and were downregulated when plakoglobin was coexpressed. Plakoglobin‐p53 R175H cells also showed significant reduction in their migration and invasion 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 | 0.001 |
| 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".