The inhibitor of kappa B kinase-epsilon regulates MMP-3 expression levels and can promote lung metastasis
Bibliographic record
Abstract
The factors that determine the ability of metastatic tumor cells to expand and grow in specific secondary site(s) are not yet fully understood. Matrix metalloproteinases (MMP) were identified as potential regulators of the site-specificity of metastasis. We found that lung carcinoma cells ectopically expressing high levels of the receptor for the type I insulin like growth factor receptor (M27(R) cells) had a significant reduction in MMP-3 expression levels and this coincided with reduced metastasis to the lung. We used these cells to further investigate signaling pathways regulating MMP-3 expression and the role that MMP-3 plays in lung metastasis. We show that ectopic IκB kinase ɛ (IKKɛ) expression in these cells partly restored MMP-3 expression levels and also sensitized MMP-3 transcription to induction by phorbol 12-myristate 13-acetate (PMA). This increase in MMP-3 production was due to increased activation of several signal transduction mediators, including protein kinase C alpha, ERK2, Akt and the transcription factor p65. Furthermore, reconstitution of MMP-3 expression in M27(R) cells restored their ability to colonize the lung whereas silencing of MMP-3 in M27 cells reduced metastases. Collectively, our results implicate IKKɛ as a central regulator of PMA-induced cell signaling and MMP-3 expression and identify MMP-3 as an enabler of tumor cell expansion in the lung.Oncogenesis (2014) 3, e116; doi:10.1038/oncsis.2014.28; published online 18 August 2014.
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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) | 0.002 | 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".