A co‐clustering model involving α5β1 integrin for the biological effects of GPI‐anchored human carcinoembryonic antigen (CEA)
Bibliographic record
Abstract
CEA functions as an intercellular adhesion molecule and is up-regulated in a wide variety of human cancers, including colon, breast and lung. Its over-expression inhibits cellular differentiation, blocks cell polarization, distorts tissue architecture, and inhibits anoikis of many different cell types. Here we report results concerning the molecular mechanism involved in these biological effects, where relatively rapid molecular changes not requiring alterations in gene expression were emphasized. Confocal microscopy experiments showed that antibody-mediated clustering of a deletion mutant of CEA (DeltaNCEA), normally incapable of self binding and clustering, led to the co-localization of integrin alpha5beta1 with patches of DeltaNCEA on the cell surface. Activation of alpha5, as defined by an anti-alpha5 mAb-sensitive increase in cell adhesion to immobilized fibronectin, and an increased binding of soluble fibronectin to cells, was also observed. This was accompanied by the recruitment of integrin-linked kinase (ILK), protein kinase B (PKB/Akt), and the mitogen-activated protein kinase (MAPK) to membrane microdomains and the phosphorylation of Akt and MAPK. Inhibition of PI3-K and ILK, but not MAPK, prevented the alpha5beta1 integrin activation. Conversely, anti-alpha5 antibody inhibited the PI3-K-mediated activation of Akt, implying the involvement of outside-in and inside-out signaling in integrin activation. Therefore we propose that CEA-mediated signaling involves clustering of CEA and co-clustering and activation of the alpha5beta1 and associated specific signaling elements on the internal surfaces of membrane microdomains. These changes may represent a molecular mechanism for the biological effects of CEA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".