Abstract A81: Relationships between expression of TGF-β factors and breast tumor characteristics in a population-based study from Poland
Bibliographic record
Abstract
Transforming growth factor-beta (TGF-β signaling has been implicated in breast development and carcinogenesis. However, the associations between expression of individual members of the TGF-β superfamily and breast cancer characteristics remains undefined. To address this gap, we evaluated the relationship of expression of TGF-β signaling factors to clinically important tumor characteristics among 842 invasive breast carcinomas identified in a population-based case-control study conducted in Poland. We evaluated immunohistochemical stains performed on tissue microarrays for six components of the TGF-β signaling pathway, including four TGF-β ligands [intracellular TGF-β1, extracellular TGF-β1, TGF-β2, and TGF-β3], the TGF-β type II receptor (TGF-βR2), and the downstream transcriptional modulator, phosphorylated-SMAD2 (p-SMAD2). Three pathologists independently read two of the six stains and scored the staining as negative, equivocal, weakly positive, or strongly positive, depending on the stain. Re-examination of 40 randomly selected spots demonstrated satisfactory intra-observer agreement for all stains (weighted kappa ≥75%). Most tumors were positive for extracellular TGF-β1 (77%), TGF-β2 (89%), TGF-β3 (92%), and TGF-βR2 (71%), whereas expression of intracellular TGF-β1 was detected in 32% and p-SMAD2 in 59% of cases. Lobular histology was associated with expression of extracellular TGF-β1 (χ2 p=
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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) | 0.000 | 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".