AhR controls redox homeostasis and shapes the tumor microenvironment in BRCA1-associated breast cancer
Bibliographic record
Abstract
Cancer cells have higher reactive oxygen species (ROS) than normal cells, due to genetic and metabolic alterations. An emerging scenario is that cancer cells increase ROS to activate protumorigenic signaling while activating antioxidant pathways to maintain redox homeostasis. Here we show that, in basal-like and BRCA1-related breast cancer (BC), ROS levels correlate with the expression and activity of the transcription factor aryl hydrocarbon receptor (AhR). Mechanistically, ROS triggers AhR nuclear accumulation and activation to promote the transcription of both antioxidant enzymes and the epidermal growth factor receptor (EGFR) ligand, amphiregulin (AREG). In a mouse model of BRCA1-related BC, cancer-associated AhR and AREG control tumor growth and production of chemokines to attract monocytes and activate proangiogenic function of macrophages in the tumor microenvironment. Interestingly, the expression of these chemokines as well as infiltration of monocyte-lineage cells (monocyte and macrophages) positively correlated with ROS levels in basal-like BC. These data support the existence of a coordinated link between cancer-intrinsic ROS regulation and the features of tumor microenvironment. Therapeutically, chemical inhibition of AhR activity sensitizes human BC models to Erlotinib, a selective EGFR tyrosine kinase inhibitor, suggesting a promising combinatorial anticancer effect of AhR and EGFR pathway inhibition. Thus, AhR represents an attractive target to inhibit redox homeostasis and modulate the tumor promoting microenvironment of basal-like and BRCA1-associated BC.
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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) | 0.001 | 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".