Mammaglobin 1 promotes breast cancer malignancy and confers sensitivity to anticancer drugs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mammaglobin 1 (MGB1), a member of the secretoglobin family, is expressed in mammary epithelial tissues and is overexpressed in most mammary carcinomas. Despite the extensive research correlating MGB1 expression profiles to breast cancer pathogenesis and disease outcome, the biological significance of MGB1 in cancer processes is still unclear. We have thus set out to conduct a functional evaluation of the molecular and cellular roles of MGB1 in breast cancer processes leading to disease progression. Using a series of breast cancer cell models with conditional MGB1 expression, we demonstrate that MGB1 promotes cancer cell malignant features. More specifically, loss of MGB1 expression resulted in a decrease of cell proliferation, soft agar spheroid formation, migration, and invasion capacities of breast cancer cells. Concomitantly, we also observed that MGB1 expression activates signaling pathways mediated by MAPK members (p38, JNK, and ERK), the focal adhesion kinase (FAK), matrix metalloproteinases (MMPs) and NFκB. Moreover, MGB1 regulates epithelial to mesenchymal (EMT) features and modulates Snail, Twist and ZEB1 expression levels. Interestingly, we also observed that expression of MGB1 confers breast cancer cell sensitivity to anticancer drug-induced apoptosis. Together, our results support a role for MGB1 in tumor malignancy in exchange for chemosensitivity. These findings provide one of the first descriptive overview of the molecular and cellular roles of MGB1 in breast cancer processes and may offer new insight to the development of therapeutic and prognostic strategies in breast cancer patients. © 2015 Wiley Periodicals, Inc.
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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 it