Decreased Expression of Gastrokine 1 and the Trefoil Factor Interacting Protein TFIZ1/GKN2 in Gastric Cancer: Influence of Tumor Histology and Relationship to Prognosis
Bibliographic record
Abstract
PURPOSE: Transcriptional profiling showed decreased expression of gastrokine 1 (GKN1) and the related trefoil factor interacting protein (TFIZ1/GKN2) in Helicobacter pylori infection. Decreased GKN1 and GKN2 mRNA expression has been reported in gastric adenocarcinoma. We have examined GKN1 and GKN2 protein expression in a large gastric cancer series, correlated expression with tumor subtype, and evaluated their utility as prognostic biomarkers. EXPERIMENTAL DESIGN: GKN1, GKN2, and the trefoil factors TFF1 and TFF3 were examined in tissue microarrays from 155 distal gastric adenocarcinomas. Immunohistochemical expression was correlated with clinical outcome. GKN1 and GKN2 expression was measured by real-time PCR and Western analysis in samples of gastric cancer and adjacent nonneoplastic mucosa. RESULTS: GKN1 was lost in 78% of diffuse and 42% of intestinal cancers (P < 0.0001, diffuse versus intestinal). GKN2 expression was lost in 85% of diffuse and 54% of intestinal type cancers (P < 0.002). GKN1 and GKN2 down-regulation were confirmed by Western and real-time PCR analysis. Loss of either protein was associated with significantly worse outcome in intestinal-type tumors by univariate analysis; and GKN2 loss remained a predictor of poor outcome in multivariate analysis (P < 0.033). TFF1 was lost in >70%, and TFF3 was expressed in approximately 50% of gastric cancers. CONCLUSIONS: Loss of GKN1 and GKN2 expression occurs frequently in gastric adenocarcinomas, especially in the diffuse subtype. GKN1 and GKN2 loss are associated with shorter overall survival in the intestinal subtype.
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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 | 0.000 |
| 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".