Distribution of GPR30, a Seven Membrane–Spanning Estrogen Receptor, in Primary Breast Cancer and its Association with Clinicopathologic Determinants of Tumor Progression
Bibliographic record
Abstract
PURPOSE: The seven transmembrane receptor, GPR30, is linked to estrogen binding and heparan-bound epidermal growth factor release. Here, the significance of GPR30 in human breast cancer was evaluated by comparing its relationship to steroid hormone receptor expression and tumor progression variables. EXPERIMENTAL DESIGN: Immunohistochemical analysis of a National Cancer Institute-sponsored tumor collection comprised of 361 breast carcinomas obtained at first diagnosis (321 invasive and 40 intraductal tumors). Biopsies from 12 reduction mammoplasties served as controls. The distribution pattern of GPR30, estrogen receptor (ER), and progesterone receptor (PR) was correlated with clinicopathologic variables obtained at diagnosis. RESULTS: GPR30, ER, and PR were positive in all 12 normal controls. In contrast, GPR30 expression varied in breast tumors, in which 62% (199 of 321) of invasive tumors and 42% (17 of 40) of intraductal tumors were positive. Codistribution of ER and GPR30 was measured in 43% (139 of 321) of invasive breast tumors, whereas both receptors were lacking (ER-GPR30-) in 19% (61 of 321) of the tumors analyzed, indicating a significant association between ER and GPR30 (P<0.05). The coexpression of PR and ER did not influence GPR30 expression, yet coexpression of GPR30 and ER was linked to PR positivity. Unlike ER, which varied inversely with HER-2/neu and tumor size, GPR30 positively associated with HER-2/neu and tumor size. In addition, GPR30 showed a positive association with metastasis (P=0.014; odds ratio, 1.9). CONCLUSIONS: GPR30 and ER exhibited distinct patterns of association with breast tumor progression variables, including HER-2/neu, tumor size, and metastatic disease. Thus, these results support the hypothesis that GPR30 and ER have an independent influence on estrogen responsiveness in breast carcinoma.
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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 | 0.000 | 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 | 0.000 | 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".