Synergistic Role between p53 and JWA: Prognostic and Predictive Biomarkers in Gastric Cancer
Bibliographic record
Abstract
Expression of p53 appears to be correlated to prognosis in patients with malignancy, but its role in gastric carcinoma has remained controversial. Recently we reported that JWA, an ADP-ribosylation-like factor 6 interacting protein 5 (ARL6ip5), was both prognostic for overall survival and predictive for platinum-based treatment of gastric cancer. In this study, we aimed to investigate p53 expression as a prognostic and predictive marker in resectable gastric cancer, alone and in combination with JWA. Expression of p53 was examined in three large patient cohorts (total n=1155) of gastric cancer. High expression of p53 was significantly correlated with unfavorable clinicopathologic parameters and decreased overall patient survival. Furthermore, patients with high p53 expression in tumors acquired remarkable survival benefit from adjuvant first-line platinum-based-chemotherapy. The synergy between p53 and JWA in predicting patient outcome was demonstrated, while no significantly elevated predictive value concerning chemotherapy was observed. Thus, p53 expression is a potent prognostic and predictive factor for resectable gastric cancer with adjuvant platinum-based chemotherapy. A combined effect of p53 with JWA as efficient prognostic indicators was found for the first time.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".