Selective Association of Peroxiredoxin 1 with Genomic DNA and <i>COX-2</i> Upstream Promoter Elements in Estrogen Receptor Negative Breast Cancer Cells
Bibliographic record
Abstract
In a search for proteins differentially cross-linked to DNA by cisplatin or formaldehyde in normal breast epithelial and breast cancer cell lines, we identified peroxiredoxin 1 (PRDX1) as a protein preferentially cross-linked to DNA in estrogen receptor negative (ER-) MDA-MB-231 but not in estrogen receptor positive (ER+) MCF7 breast cancer cells. Indirect immunofluorescence microscopic analyses showed that PRDX1 was located in the cytoplasm and nucleus of normal and breast cancer cells, with nuclear PRDX1 associated with promyelocytic leukemia protein bodies. We demonstrated that PRDX1 association with the transcription factor nuclear factor-kappaB (NF-kappaB) in MDA-MB-231 but not in MCF7 cells contributed to PRDX1-selective recruitment to MDA-MB-231 genomic DNA. Furthermore, PRDX1 was associated with the cyclooxygenase (COX)-2 upstream promoter region at sites occupied by NF-kappaB in ER- but not in ER+ breast cancer cells. PRDX1 knockdown attenuated COX-2 expression by reducing NF-kappaB occupancy at its upstream promoter element in MDA-MB-231 but not in MCF7 cells. A phosphorylated form of PRDX1 was only present in ER- breast cancer cells. Because PRDX1 phosphorylation is known to inhibit its peroxidase activity and to promote PRDX1 oligomerization, we propose that PRDX1 acts as a chaperone to enhance the transactivation potential of NF-kappaB in ER- breast cancer cells.
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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".