BRCA1 interacts with Nrf2 to regulate antioxidant signaling and cell survival
Bibliographic record
Abstract
Oxidative stress plays an important role in cancer development and treatment. Recent data implicate the tumor suppressor BRCA1 in regulating oxidative stress, but the molecular mechanism and the impact in BRCA1-associated tumorigenesis remain unclear. Here, we show that BRCA1 regulates Nrf2-dependent antioxidant signaling by physically interacting with Nrf2 and promoting its stability and activation. BRCA1-deficient mouse primary mammary epithelial cells show low expression of Nrf2-regulated antioxidant enzymes and accumulate reactive oxygen species (ROS) that impair survival in vivo. Increased Nrf2 activation rescues survival and ROS levels in BRCA1-null cells. Interestingly, 53BP1 inactivation, which has been shown to alleviate several defects associated with BRCA1 loss, rescues survival of BRCA1-null cells without restoring ROS levels. We demonstrate that estrogen treatment partially restores Nrf2 levels in the absence of BRCA1. Our data suggest that Nrf2-regulated antioxidant response plays a crucial role in controlling survival downstream of BRCA1 loss. The ability of estrogen to induce Nrf2 posits an involvement of an estrogen-Nrf2 connection in BRCA1 tumor suppression. Lastly, BRCA1-mutated tumors retain a defective antioxidant response that increases the sensitivity to oxidative stress. In conclusion, the role of BRCA1 in regulating Nrf2 activity suggests important implications for both the etiology and treatment of BRCA1-related cancers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".