Expression of DBC1 and SIRT1 Is Associated with Poor Prognosis of Gastric Carcinoma
Bibliographic record
Abstract
PURPOSE: SIRT1 (silent mating-type information regulation 2 homologue 1) expression has been reported to predict poor survival in some cancers. We therefore investigated the expression levels of SIRT1 and its negative regulator, DBC1 (deleted in breast cancer 1), in gastric cancer patients. EXPERIMENTAL DESIGN: We evaluated immunohistochemical expression of DBC1, SIRT1, and p53 using 3-mm tumor cores from 177 gastric cancer patients for tissue microarray. RESULTS: Positive expressions of DBC1 and SIRT1 were seen in 62% (109 of 177) and in 73% (130 of 177) of patients, respectively. Expression of DBC1 was significantly correlated with tumor stage (P = 0.007), lymph node metastasis (P < 0.001), tumor invasion (P = 0.001), venous invasion (P = 0.001), histologic types (P < 0.001), p53 expression (P < 0.001), and SIRT1 expression (P < 0.001). SIRT1 expression was also significantly correlated with tumor stage (P < 0.001), lymph node metastasis (P < 0.001), tumor invasion (P < 0.001), histologic types (P < 0.001), and p53 expression (P = 0.001). In addition, expression of DBC1 was significantly associated with shorter overall survival and relapse-free survival by univariate analysis (P < 0.001 and P < 0.001, respectively). SIRT1 expression was also significantly associated with shorter overall survival and relapse-free survival by univariate analysis (P = 0.001 and P = 0.001, respectively). Multivariate analysis showed that tumor stage and expression of DBC1 were independent prognostic factors significantly associated with overall survival and relapse-free survival. CONCLUSION: This study shows that expression of DBC1 and SIRT1 is a significant prognostic indicator for gastric carcinoma patients.
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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 | 0.000 |
| 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".