Role of epigenetics and STAT5 in breast cancer resistance protein (BCRP/ABCG2) expression in the lactating mammary gland (1141.3)
Bibliographic record
Abstract
The multidrug transporter breast cancer resistance protein (ABCG2) is upregulated in the mammary gland during lactation. We have shown that prolactin induces ABCG2 in human breast cancer cells via the recruitment of Signal Transducer and Activator of Transcription‐5 (STAT5) to the human ABCG2 gene. It is unclear if a similar mechanism regulates ABCG2 in vivo. Here we investigated epigenetic and transcriptional mechanisms that may control Abcg2 expression in the lactating mouse mammary gland. Expression profiling of three different Abcg2 mRNA isoforms (E1a, E1b, and E1c) revealed that the E1b isoform is predominately expressed and induced in the lactating mammary gland. Despite this significant induction during lactation, the E1b promoter region in the virgin gland is already hypomethylated and enriched with the open chromatin histone mark H3K4me2. Next we used a forced‐weaning model to stop lactation and to rapidly turn off Stat5 activity in the mammary gland. Within 48h after forced weaning, there was a significant reduction in Abcg2 mRNA expression with a corresponding reduction in Stat5 occupancy at the mouse Abcg2 gene. Taken together, our results suggest that the Abcg2 gene is already poised for expression in the virgin mammary gland and that the binding of Stat5 plays an important role in the regulation of Abcg2 during lactation. Grant Funding Source : Supported by CIHR.
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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".