<scp>MDM</scp>2 is a useful prognostic biomarker for resectable gastric cancer
Bibliographic record
Abstract
Expression of MDM2 protein appears to be increased in malignancy and correlated to prognosis of tumors, but its role in gastric cancer remains controversial. Our recent investigations indicated that JWA was a novel candidate biomarker for gastric cancer. To evaluate the impact of MDM2 protein expression alone, and in combination with JWA, on the prognostic and predictive of patients with resectable gastric cancer, expression of MDM2 and JWA were examined by immunohistochemistry in three large cohorts (total n = 1131) of patient with gastric cancer. We found that MDM2 protein levels were significantly upregulated in gastric cancer (70.4%, 57 of 81) compared with adjacent non-cancerous tissues. High tumoral MDM2 expression significantly correlated with clinicopathologic characteristics, as well as with shorter overall survival (OS; P < 0.001 for all cohorts) in patients without adjuvant treatment. The effect of adjuvant fluorouracil-leucovorin-oxaliplatin (FLO) in improving OS compared with surgery alone was evident only in the high MDM2 group (hazard ratio = 0.57; 95% confidence interval, 0.37-0.89; P = 0.013). Furthermore, knockdown of MDM2 and overexpression of JWA had a synergistic effect on suppression of gastric cancer cell proliferation and migration. Patients with low MDM2 and high JWA expression had a better outcome of survival compared with the other groups (P < 0.001 for all cohorts). For the first time, our data suggest that MDM2 is a potent prognostic and predictive factor for benefit from adjuvant fluorouracil-leucovorin-oxaliplatin chemotherapy in resectable gastric cancer. The combination of MDM2 expression and JWA could serve as a more effective candidate prognostic biomarker for gastric cancer.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".