Overexpression of Phosphorylated Mammalian Target of Rapamycin Predicts Lymph Node Metastasis and Prognosis of Chinese Patients with Gastric Cancer
Bibliographic record
Abstract
PURPOSE: We determined the expression of mammalian target of rapamycin (mTOR) and its activated form, p-mTOR, in Chinese patients with gastric cancer and its clinical effects and underlying mechanisms. EXPERIMENTAL DESIGN: Tissue microarray blocks containing gastric cancer tissue and matched noncancer gastric tissue specimens obtained from 1,072 patients were constructed. Expression of total mTOR and p-mTOR in these specimens was analyzed using immunohistochemical studies and confirmed by Western blotting. RESULTS: The overall rates of total mTOR and p-mTOR overexpression were 50.8% (545 of 1,072) and 46.5% (499 of 1,072), respectively. The p-mTOR overexpression was significantly correlated with total mTOR overexpression. Overexpression of total mTOR protein was significantly correlated with tumor differentiation, T1/T2 tumors, and stage I/II/III disease, whereas p-mTOR overexpression was significantly correlated with lymph node metastasis and all stage disease. The Cox proportional hazards model revealed that the overexpression of p-mTOR, but not total mTOR, was an independent prognostic factor for gastric cancer. The overexpression of p-mTOR also predicted the angiogenic phenotype of human gastric cancer and regulated angiogenesis of gastric cancer cells. CONCLUSIONS: Increased activation of mTOR is frequent in human gastric cancer and overexpression of p-mTOR is an independent prognostic factor, suggesting that mTOR pathway could be a potential target for therapy of this malignancy.
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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 | 0.001 |
| 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".