IκB Kinase-α Regulates Endothelial Cell Motility and Tumor Angiogenesis
Bibliographic record
Abstract
The transcription factor nuclear factor-kappaB (NF-kappaB) is constitutively activated in many types of cancers and has been implicated in gene expression important for angiogenesis, tumor growth, progression, and metastasis. Here, we show that the NF-kappaB activator, IkappaB kinase-alpha (IKKalpha), but not IKKbeta, promotes endothelial cell motility and tumor angiogenesis. IKKalpha is elevated in tumor vasculature compared with normal endothelium. Overexpression of IKKalpha in endothelial cells promoted cell motility and vascular tubule formation in a three-dimensional culture assay, and conversely, knockdown of IKKalpha in endothelial cells inhibited cell motility, compared with controls. Interestingly, blocking NF-kappaB activation totally abolished IKKalpha-induced angiogenic function. Furthermore, using a tumor and endothelial cell cotransplantation model, we show that overexpression of IKKalpha in endothelial cells significantly increased tumor vascular formation compared with controls, which contributed to increased tumor growth and tumor cell proliferation, and decreased tumor cell apoptosis. Collectively, these findings have identified a new function for IKKalpha through the canonical NF-kappaB pathway in tumor angiogenesis.
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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) | 0.001 | 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".