Overexpression of AKR1B10 Predicts Poor Prognosis in Gastric Cancer Patients Undergoing Surgical Resection
Bibliographic record
Abstract
Aldo-keto reductase family 1 member B10 (AKR1B10) is associated with several cancers, but the prognostic role in gastric cancer (GC) remains unclear. We enrolled 359 GC patients who underwent a gastrectomy with D2 lymph node dissection. AKR1B10 expression was scored using an immunoreactive scoring system based on immunohistochemistry. Adjuvant chemotherapy with S-1 or oxaliplatin plus capecitabine was administered to pathological stage II or III disease patients. There were 117 (32.6%) and 242 (67.4%) patients with AKR1B10 overexpression and low expression, respectively. Patients overexpressing AKR1B10 had worse 5-year disease-free survival (DFS) and overall survival (OS) rates than those with low expression of AKR1B10. Pathological T3-T4 stage, pathological stage III, lymph node ratio ≥25%, and AKR1B10 overexpression were independent prognostic factors for worse DFS and OS in univariate and multivariate analyses. For 162 stage II or III patients who received adjuvant chemotherapy after surgical resection and 59 patients with signet ring cell carcinoma histology, AKR1B10 overexpression was also associated with inferior DFS and OS. AKR1B10 was not associated with clinical survival in stage I GC patients. In conclusion, AKR1B10 overexpression may be an independent prognostic factor for worse survival in GC patients who underwent gastrectomy with D2 lymph node dissection.
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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 | 0.000 | 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".