Increased wild‐type p53‐induced phosphatase 1 (Wip1 or PPM1D) expression correlated with downregulation of checkpoint kinase 2 in human gastric carcinoma
Bibliographic record
Abstract
Phosphorylation of checkpoint kinase 2 (Chk2) at Thr68 (pChk2) induced by DNA double-strand breaks is required for inhibition of cell cycle progression in the G(2) phase. The purpose of the present paper was to investigate the expression of wild-type p53-induced phosphatase 1 (Wip1 or PPM1D), a negative regulator of Chk2, to better understand its role in human gastric cancer. In non-neoplastic gastric mucosa, most epithelial cells exhibited Wip1-positive and pChk2-negative immunoreactivity, whereas an inverse pattern of protein expression was detected at the surface of the foveolar epithelium. In tumor tissues, 74% of 53 gastric cancers had intense Wip1 immunoreactivity and close correlation with both tumor size (P = 0.0497) and Chk2 dephosphorylation (P = 0.0213). In MKN-74 gastric cancer cells, ionizing radiation (IR)-induced Wip1 upregulation was detected at protein levels, but the Chk2-mediated cell cycle regulatory mechanism was disrupted. In addition, protease inhibitor Z-Leu-Leu-Leu (ZLLL) effectively upregulated Wip1 levels in the presence or absence of IR, suggesting that Wip1 expression can be modulated post-transcriptionally. Understanding the Wip1-mediated signaling pathway in gastric cancer may provide useful information for the development of new chemo- and radiotherapies.
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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".