Neuroendocrine Markers Insulinoma-Associated Protein 1, Chromogranin, Synaptophysin, and CD56 Show Rare Positivity in Adenocarcinoma Ex-Goblet Cell Carcinoids
Bibliographic record
Abstract
BACKGROUND: Adenocarcinoma ex-goblet cell carcinoid (AdexGCC) was considered a neuroendocrine adenocarcinoma, despite majority of tumor cells being negative for conventional neuroendocrine markers such as chromogranin and synaptophysin. Recently, insulinoma-associated protein 1 (INSM1) has been identified as a novel neuroendocrine marker that is more sensitive than chromogranin, synaptophysin, and CD56 in pulmonary neuroendocrine tumors. METHODS: We studied this marker in conjunction with chromogranin, synaptophysin, and CD56 in 36 appendiceal AdexGCCs (21 primaries, 15 metastatic). RESULTS: Primary AdexGCCs showed staining for INSM1, chromogranin, synaptophysin, and CD56 in 13/21 (62%), 18/21 (86%), 18/21 (86%), and 9/19 (47%) cases, respectively. However, the mean proportion of tumor cells stained for INSM1, chromogranin, synaptophysin, and CD56 was only 8.0% (median 1%, range 0-70%), 15.7% (median 2%, range 0-70%), 19.9% (median 5%, range 0-90%), and 5.6% (median 0%, range 0-50%), respectively. Metastatic AdexGCCs showed staining for INSM1, chromogranin, synaptophysin, and CD56 in 8/15 (53%), 11/15 (73%), 12/15 (80%), and 3/14 (21%) cases. The mean proportion of tumor cells stained for INSM1, chromogranin, synaptophysin, and CD56 in metastatic tumors was 1% (median 1%, range 0-3%), 12% (median 1%, range 0-85%), 17% (median 5%, range 0-85%), and 2% (median 0%, range 0-20%), respectively. CONCLUSIONS: Primary and metastatic AdexGCCs showed no difference in INSM1, chromogranin, synaptophysin, or CD56 staining. INSM1 exhibits low expression in AdexGCCs and is expressed by a lower proportion of tumor cells compared to chromogranin and synaptophysin.
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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".