Efficacy of GATA3 Versus BRST2 for the Identification of Metastatic Breast Carcinoma in the Upper GI Tract: Which Performs Better?
Bibliographic record
Abstract
Distinguishing primary diffuse-type gastric carcinoma (PDGC) versus gastric involvement by metastatic breast carcinoma (mBC), particularly the lobular subtype, is difficult on histology alone. Both can appear morphologically similar. GATA3, a novel transcription factor, is used in certain scenarios as an immunohistochemical marker of breast origin. Our objective was to investigate the efficacy of GATA3 in differentiating PDGC and mBC and how it compares to another breast marker, BRST2. We retrospectively stained 40 cases of PDGC and 10 control cases of mBC from upper gastrointestinal tract specimens for antibodies: GATA3, BRST2, CDX2, and estrogen receptor. Staining of tumor cells was semiquantified with a modified Allred score. GATA3 and BRST2 were positive in 17.5% and 12.5% of PDGC cases, respectively, and in 100% of mBC cases. Allred scores for GATA3 were significantly greater in mBC cases compared with PDGC (P=0.001). Allred scores were not significantly different for BRST2 due to low levels of staining in mBC cases. Although sensitivity and specificity were similar, differences in staining between PDGC and mBC were more decisive for GATA3 versus BRST2 and thus easier to interpret. In addition, 50% of PDGC cases were positive for CDX2 and none for estrogen receptor. Overall, our results show that GATA3 can reliably and correctly identify cases of mBC to the upper gastrointestinal tract. However, because a minority of PDGC were positive for GATA3, it should still be used within an antibody panel to resolve this diagnostic dilemma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".