Transendothelial Migration of Colon Carcinoma Cells Requires Expression of E-selectin by Endothelial Cells and Activation of Stress-activated Protein Kinase-2 (SAPK2/p38) in the Tumor Cells
Bibliographic record
Abstract
Adhesion and migration of tumor cells on and through the vascular endothelium are critical steps of the metastatic invasion. We investigated the roles of E-selectin and of stress-activated protein kinase-2 (SAPK2/p38) in modulating endothelial adhesion and transendothelial migration of HT-29 colon carcinoma cells. Tumor necrosis factor alpha (TNF alpha) strongly increased the expression of E-selectin in human umbilical vein endothelial cells (HUVEC). This effect was independent of the activation of SAPK2/p38 induced by TNF alpha. Adhesion of HT-29 cells on a monolayer of HUVEC pretreated with TNF alpha was dependent on E-selectin expression but was independent of SAPK2/p38 activity of both HUVEC and tumor cells. The adhesion of HT-29 cells to E-selectin-expressing HUVEC led to the activation of SAPK2/p38 in the tumor cells as reflected by the increased phosphorylation of the actin-polymerizing factor HSP27 by mitogen-activated protein kinase 2/3, a direct target of SAPK2/p38. Moreover, a recombinant E-selectin/Fc chimera quickly increased the activation of SAPK2/p38 in HT-29 cells. Blocking the increased activity of SAPK2/p38 of HT-29 cells by SB203580 or by expressing a dominant negative form of SAPK2/p38 inhibited their transendothelial migration. Similarly, HeLa cells stably expressing a kinase-inactive mutant of SAPK2/p38 showed a decreased capacity to cross a layer of HUVEC. Overall, our results suggest that the regulation of transendothelial migration of tumor cells involves two essential steps as follows: adhesion to the endothelium through adhesion molecules, such as E-selectin, and increased motogenic potential through adhesion-mediated activation of the SAPK2/p38 pathway.
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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 | 0.000 |
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 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".