Activated mitogen-activated protein kinase expression during human breast tumorigenesis and breast cancer progression.
Bibliographic record
Abstract
PURPOSE: The purpose of this study is to address the hypothesis that activatedmitogen-activated protein kinase (MAPK; extracellular signal-regulated kinases 1 and 2) has a role in breast tumorigenesis, breast cancer progression, and the development of tamoxifen resistance. EXPERIMENTAL DESIGN: H-score analysis and a specific antibody for the immunohistochemical detection of activated MAPK in formalin-fixed, paraffin-embedded tissue sections were used to compare expression in: (a) human breast tumors and their matched adjacent normal breast tissue; (b) primary human breast tumors and their matched lymph node metastases; and (c) primary breast tumors from patients who later proved to be sensitive or resistant to tamoxifen treatment. RESULTS: Active MAPK expression was detected in 48% of primary human breast tumors and was significantly increased in tumors compared with adjacent normal breast (Wilcoxon test, P = 0.027). A significant positive association (chi(2), P = 0.02; n = 55) was obtained between active MAPK and the presence of lymph node metastases. Moreover, increased active MAPK (Wilcoxon test, P = 0.0098) was found in concurrent lymph node metastases compared with primary breast tumors. No significant difference in active MAPK was found in primary tumors of patients who later responded to tamoxifen or did not respond to tamoxifen. CONCLUSIONS: These data suggest that active MAPK is a marker of breast cancer metastasis and has a role in the metastatic process. However, active MAPK is unlikely to be a marker of endocrine sensitivity or involved in de novo tamoxifen resistance.
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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 | 0.000 |
| 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) | 0.002 | 0.001 |
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".