Prostate-Derived Ets Transcription Factor Overexpression is Associated with Nodal Metastasis, Hormone Receptor Positivity in Invasive Breast Cancer
Bibliographic record
Abstract
Prostate-derived Ets transcription factor (PDEF) has recently been associated with invasive breast cancer, but no expression profile has been defined in clinical specimens. We undertook a comprehensive PDEF transcriptional expression study of 86 breast cancer clinical specimens, several cell lines, and normal tissues. PDEF expression profile was analyzed according to standard clinicopathologic parameters and compared with hormonal receptor and HER-2/neu status and to the expression of the new tumor biomarker Dikkopf-1 (DKK1). Wide ranging PDEF overexpression was observed in 74% of tested tumors, at higher levels than the average expression found in normal breasts. High PDEF expression was associated with hormone receptor positivity (P < .001), moderate to good differentiation (less than grade III, P = .01), and dissemination to axillary lymph nodes (P = .002). PDEF was an independent risk factor for nodal involvement (multivariate analysis, odds ratio 1.250, P = .002). It was expressed in a different subgroup compared to DKK1-expressing tumors (P < .001). Our data imply that PDEF mRNA expression could be useful in breast cancer molecular staging. Further insights into PDEF functions at the protein level, and possible links with hormone receptors biology, bear great potential for new therapeutic avenues.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".