Alpha-Fetoprotein-Producing Early Gastric Cancer with Intramucosal Hepatoid and Fetal Enteric Differentiation
Bibliographic record
Abstract
Alpha-fetoprotein (AFP)-producing gastric carcinomas (AFPGCs) are relatively rare tumors known to have a poor prognosis and commonly found as advanced lesions. Histologically, AFPGCs have been described as having hepatoid and fetal enteric (enteroblastic) morphology and are associated with conventional adenocarcinomas. Prior studies reported a hepatoid component present only in invasive areas and hypothesized that AFPGCs may develop hepatoid features during the process of tumor invasion. We report three cases of AFP-producing early gastric cancer which had an intramucosal hepatoid component. Immunohistochemistry showed that the hepatoid component was diffusely immunoreactive for SALL4, AFP, arginase-1, and HepPar1, and focally for CDX2 and PDX1. An intramucosal transition between the hepatoid component and conventional intramucosal adenocarcinoma was identified. Two patients also had a coexistent fetal enteric component, which was admixed with a hepatoid component. Although at an early stage one patient subsequently developed liver metastasis and a second patient was suspected of having liver metastasis, these were not biopsy-proven. The latter patient had a previous history of hepatocellular carcinoma (HCC) and SALL4 was used on the HCC to distinguish metastatic/further HCC from a gastric metastatic primary with hepatoid differentiation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".