Glypican-3 and Cytokeratin-19 Expression in Pancreatic Cancer in a Canadian Population
Bibliographic record
Abstract
Background/Objectives: One study of pancreatic ductal adenocarcinoma has found expression of glypican-3 (GPC3) and cytokeratin-19 (CK19) determined by immunohistochemistry to be associated with higher stage and grade disease, with a more adverse prognosis. The reported 44% rate of GPC3 expression in pancreatic cancer raises the important possibility that targeted immunotherapies currently in development for hepatocellular carcinoma may also prove useful for GPC3-expressing pancreatic cancers. The present study aims to determine if a similar expression pattern of these markers and stage/grade/prognostic associations is present in our Canadian patient population. Methods: Patients with a pancreatic surgical resection for adenocarcinoma or neuroendocrine tumor (NET) were identified from pathology records over a 5-year period. Immunohistochemistry for GPC3 and CK19 was performed on archived tumor tissue and the proportion of positive cells and intensity of staining were recorded. Grade, stage, and overall survival were compared in patients with NETs that were CK19-positive versus -negative. Results: All 72 pancreatic adenocarcinomas and 20 NETs tested were negative for GPC3, apart from a single case of pancreatic adenocarcinoma. All 72 adenocarcinomas were positive for CK19 expression. Half of the NETs were positive for CK19. There was no correlation between CK19 expression in NETs and tumor grade, lymph node metastasis, distant metastasis, or overall survival. Conclusions: We are skeptical of the reported prognostic value of GPC3 and CK19 in pancreatic adenocarcinomas. CK19 as a prognostic marker in NETs has potential for further study. The results with our protocol for GPC3 immunohistochemistry suggest that pancreatic cancer may be a less promising target for GPC3-targeted immunotherapies than previously thought.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".