Protein Kinase C-ζ Regulates Transcription of the Matrix Metalloproteinase-9 Gene Induced by IL-1 and TNF-α in Glioma Cells via NF-κB
Why this work is in the frame
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Bibliographic record
Abstract
The regulation of matrix metalloproteinase-9 (MMP-9) expression in glioma cells is one of the key processes in tumor invasion through the brain extracellular matrix. Although some studies have demonstrated the implication of classic protein kinase C (PKC) isoforms in the regulation of MMP-9 production by phorbol esters or lipopolysaccharide, the involvement of specific PKC isoforms in the signaling pathways leading to MMP-9 expression by inflammatory cytokines remains unclear. Here we report that the atypical PKC-zeta isoform participates in the induction of MMP-9 expression by interleukin-1 (IL-1) and tumor necrosis factor-alpha (TNF-alpha) in rat C6 glioma cells. Indeed, zymography and semi-quantitative reverse transcriptase-PCR analysis showed that pretreatment of C6 cells with PKC-zeta pseudosubstrate abolished MMP-9 activity and gene expression induced by IL-1 or TNF-alpha. Accordingly, IL-1 and TNF-alpha were able to induce PKC-zeta activity, as demonstrated by in vitro kinase assay using immunoprecipitated PKC-zeta. Furthermore, stable C6 clones overexpressing PKC-zeta, but not PKC-epsilon, displayed an up-regulation of MMP-9 constitutive expression as well as an increase of mmp-9 promoter activity. These processes were inhibited by an NF-kappaB-blocking peptide and completely prevented by NF-kappaB-binding site mutation in the mmp-9 promoter. Taken together, these results indicate that PKC-zeta plays a key role in the regulation of MMP-9 expression in C6 glioma cells through NF-kappaB.
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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