Identification of poly(ADP-ribose)polymerase-1 and Ku70/Ku80 as transcriptional regulators of S100A9 gene expression
Bibliographic record
Abstract
BACKGROUND: S100 proteins, a multigenic family of non-ubiquitous cytoplasmic Ca2+-binding proteins, have been linked to human pathologies in recent years. Dysregulated expression of S100 proteins, including S100A9, has been reported in the epidermis as a response to stress and in association with neoplastic disorders. Recently, we characterized a regulatory element within the S100A9 promotor, referred to as MRE that drives the S100A9 gene expression in a cell type-specific, activation- and differentiation-dependent manner (Kerkhoff et al. (2002) J. Biol. Chem. 277, 41879-41887). RESULTS: In the present study, we investigated transcription factors that bind to MRE. Using the MRE motif for a pull-down assay, poly(ADP-ribose)polymerase-1 (PARP-1) and the heterodimeric complex Ku70/Ku80 were identified by mass spectrometry and confirmed by chromatin immunoprecipitation. Furthermore, TPA-induced S100A9 gene expression in HaCaT keratinocytes was blocked after the pharmacologic inhibition of PARP-1 with 1,5-isoquinolinediol (DiQ). CONCLUSION: The candidates, poly(ADP-ribose)polymerase-1 (PARP-1) and the heterodimeric complex Ku70/Ku80, are known to participate in inflammatory disorders as well as tumorgenesis. The latter may indicate a possible link between S100 and inflammation-associated 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) | 0.002 | 0.001 |
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".