Cul3 overexpression depletes Nrf2 in breast cancer and is associated with sensitivity to carcinogens, to oxidative stress, and to chemotherapy
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
Nrf2 is the key transcription factor for cytoprotective gene programs. Nrf2 is normally maintained at very low concentrations by proteasomal degradation, through its interaction with the adapter protein Keap1 and the Cul3 E3 ligase. Increased Nrf2 concentration resulting from loss of function Keap1 mutations has been described in chemoresistant non-small cell lung cancer. Previous studies in breast cancer showed low levels of some Nrf2-regulated detoxification genes, but the mechanism has not been systematically examined. We found that half of the breast cancer cell lines examined have decreased concentration of Nrf2 compared with normal mammary epithelial cell lines, associated with variable but detectable levels in Keap1 levels, and consistently increased Cul3 mRNA and protein. Immunochemistry showed that 7 of 10 breast cancer specimens examined also have low Nrf2 levels and increased Cul3. Keap1 protein levels are variable. We found no C23Y mutation in Keap1 of any of the cell lines. Using siRNA, we silenced Cul3 in MCF-7 breast cancer cells, and microarray analysis reveals the induction of GCL, NQO1, AKR1C1, UGDH, and TXN by at least 2-fold. The Nrf2-regulated ABCC1 drug transporter was also found to be increased. These Cul3-silenced MCF7 cells are highly resistant to oxidative stress induced by H(2)O(2,) to the carcinogen benzo(a)pyrene, and to both Doxorubicin and Paclitaxel. This high Cul3/low Nrf2 signature may be key to cellular sensitivity to both chemical carcinogeneic stimuli as well as to cytotoxicity of commonly used chemotherapeutic drugs in established breast 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.
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