Claudin-18 as a Promising Surrogate Marker for Endocervical Gastric-type Carcinoma
Bibliographic record
Abstract
HIK1083 and trefoil factor 2 (TFF2) are known to be expressed in gastric-type carcinoma (GAS), but they do not reliably mark all GASs, and focal expression can be missed in biopsy specimens. We aimed to investigate whether claudin-18 and alpha-methylacyl-CoA racemase (AMACR) could be surrogate markers to separate GAS from other types of endocervical adenocarcinoma (ECA) and to compare their usefulness with that of HIK1083 and TFF2. Claudin-18 and AMACR immunohistochemistry was performed, and the results were compared with that of TFF2 and HIK1083, using whole sections of 75 ECAs (22 GASs and 53 non-GASs) and 179 ECAs with tissue microarrays (TMAs). TMAs were built to simulate the assessment of immunohistochemical stains in small biopsies. Any membranous (claudin-18) or cytoplasmic/membranous (AMACR, TFF2, HIK1083) staining of >5% of tumor cells was considered positive. Of 75 ECAs with whole sections, claudin-18 was significantly more frequently expressed in GASs (21/22) compared with non-GASs (8/53) (P<0.01). In ECAs with TMAs, claudin-18 expression was significantly frequent in GASs (15/23, 65.2%) than in non-GASs (3/152, 2.0%; all usual-type) (P<0.01). All claudin-18-positive GASs showed intense staining except 1 case. Claudin-18 shared the same degree of sensitivity and specificity with HIK1083 and TFF2. Three clear cell carcinomas were positive for claudin-18, but none showed intense staining. AMACR was expressed in a subset of ECAs and showed no impact in distinguishing between GAS and other ECAs. Our results suggest that claudin-18 is a promising surrogate marker to separate GAS from other types of ECA, including clear cell carcinoma.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".