Over‐expression of IκB‐kinase‐ε (IKKε/IKKi) induces secretion of inflammatory cytokines in prostate cancer cell lines
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Elevated inflammatory cytokine levels in serum have been associated with advanced stage metastasis-related morbidity in prostate cancer. Several studies have shown that IL-6 and IL-8 can accelerate the growth of human prostate cancer cell lines. Previous studies, in murine embryonic fibroblasts, have shown that Ikappa-B kinase-epsilon (IKKepsilon/IKKi)-deficiency results in the reduction of lipopolysaccharide-mediated expression of IL-6. RESULTS: In this study, we report that over-expression of IKKepsilon in hormone-sensitive 22Rv1 and LNCaP prostate cancer cells induces the secretion of several inflammatory cytokines including IL-6 and IL-8. Both of these cytokines are secreted by hormone-refractory PC-3 prostate cancer cells and IKKepsilon knock-down in these cells correlates with a strong decrease in IL-6 secretion. Furthermore, we demonstrate that IKKepsilon over-expression does not induce the activation of the IKKepsilon classical targets NF-kappaB and IRF-3, two transcription factors involved in the regulation of several cytokines. Finally, we observe that high IKKepsilon expression results in its nuclear translocation, a phenomena that is TBK1-independent. CONCLUSIONS: This study identifies IKKepsilon as a potential prostate cancer gene that may favor chronic inflammation and create a tumor-supporting microenvironment that promotes prostate cancer progression, particularly by the induction of IL-6 secretion that may act as a positive growth factor in prostate cancer.
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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