PARP7 and Mono-ADP-Ribosylation Negatively Regulate Estrogen Receptor α Signaling in Human Breast Cancer Cells
Bibliographic record
Abstract
ADP-ribosylation is a post-translational protein modification catalyzed by a family of proteins known as poly-ADP-ribose polymerases. PARP7 (TIPARP; ARTD14) is a mono-ADP-ribosyltransferase involved in several cellular processes, including responses to hypoxia, innate immunity and regulation of nuclear receptors. Since previous studies suggested that PARP7 was regulated by 17β-estradiol, we investigated whether PARP7 regulates estrogen receptor α signaling. We confirmed the 17β-estradiol-dependent increases of PARP7 mRNA and protein levels in MCF-7 cells, and observed recruitment of estrogen receptor α to the promoter of PARP7. Overexpression of PARP7 decreased ligand-dependent estrogen receptor α signaling, while treatment of PARP7 knockout MCF-7 cells with 17β-estradiol resulted in increased expression of and recruitment to estrogen receptor α target genes, in addition to increased proliferation. Co-immunoprecipitation assays revealed that PARP7 mono-ADP-ribosylated estrogen receptor α, and mass spectrometry mapped the modified peptides to the receptor's ligand-independent transactivation domain. Co-immunoprecipitation with truncated estrogen receptor α variants identified that the hinge region of the receptor is required for PARP7-dependent mono-ADP-ribosylation. These results imply that PARP7-mediated mono-ADP-ribosylation may play an important role in estrogen receptor positive breast cancer.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".