GATA-3 Expression in Breast Cancer Has a Strong Association with Estrogen Receptor but Lacks Independent Prognostic Value
Bibliographic record
Abstract
BACKGROUND: GATA-3 is a transcription factor involved in human growth and differentiation. Gene expression profiling has shown that GATA-3 is highly expressed in the Luminal A subtype of breast cancer. A recent study found GATA-3 to be associated with favorable breast cancer pathologic features, including negative lymph node and positive estrogen receptor (ER) status. GATA-3 levels were also found to be an independent prognostic marker, with low expression predicting for breast cancer recurrence. MATERIALS AND METHODS: Our case series consists of 3,119 cases of invasive breast cancer in which GATA-3 expression was assessed by immunohistochemistry on tissue microarrays. We considered >5% nuclear staining to be a positive result for GATA-3. RESULTS: Thirty-two percent of cases were GATA-3 positive. GATA-3 is almost exclusively expressed in ER+ patients and is also associated with lower tumor grade, older age at diagnosis, and the absence of Her2 overexpression. In univariate analysis, the presence of GATA-3 is a marker of good prognosis and predicted for superior breast cancer-specific survival, relapse-free survival, and overall survival. However, in multivariate models including patient age, tumor size, histologic grade, nodal status, ER status, and Her2 status, GATA-3 was not independently prognostic for these same outcomes. In the subgroups of ER+ patients treated with or without tamoxifen, GATA-3 was again nonprognostic for all outcomes. DISCUSSION: GATA-3 is a molecular marker that is highly associated with ER expression, but it does not seem to have prognostic value independent of ER, nor does it predict for response to tamoxifen among ER-positive patients.
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".