Trefoil Factor 2 (TFF2) as a Surrogate Marker for Endocervical Gastric-type Carcinoma
Bibliographic record
Abstract
Gastric-type carcinoma (GAS) is the most common human papilloma virus-independent endocervical adenocarcinoma (ECA), characterized by an aggressive behavior. Trefoil factor 2 (TFF2) is a mucin-associated peptide expressed in normal gastric but not endocervical glands. This study was carried out to investigate whether TFF2 could be a surrogate marker to separate GAS from other types of ECA. ECAs from 9 international institutions were reviewed for consensus histotype. Of them, expression of TFF2 was immunohistochemically examined compared with that of HIK1083, using whole sections of 50 ECAs (10 GASs and 40 non-GASs) and 179 ECAs (24 GASs and 155 non-GASs) with tissue microarrays (TMAs). TMAs were assessed to simulate assessment of immunohistochemical stains in small biopsies. Both markers were similarly scored, and any cytoplasmic/membranous staining of >5% of tumor cells was considered positive. Of 50 ECAs with whole sections, TFF2 was significantly more frequently expressed in GASs (8/10) compared with non-GASs (5/40) (P<0.01). In 179 ECAs with TMAs, TFF2 was also significantly more frequently expressed in GASs (7/24) compared with non-GASs (4/155) (P<0.01). There was no significant difference in specificity among the 2 markers. Double positivity for TFF2 and HIK1083 in ECAs was highly specific in separating GASs from non-GAS (P<0.01). A significantly smaller percentage of GASs were TFF2 positive in TMAs than in whole sections (P<0.01). Our results suggest that TFF2 is a promising marker, along with HIK1083, to confirm a diagnosis of GAS. This marker may be negative in small biopsies, indicating the necessity of using other exclusionary markers in combination with rigorous morphologic review and extensive sampling in resection specimens.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".