Integration of Cell Attachment, Cytoskeletal Localization, and Signaling by Integrin-linked Kinase (ILK), CH-ILKBP, and the Tumor Suppressor PTEN
Bibliographic record
Abstract
Cell attachment and the assembly of cytoskeletal and signaling complexes downstream of integrins are intimately linked and coordinated. Although many intracellular proteins have been implicated in these processes, a new paradigm is emerging from biochemical and genetic studies that implicates integrin-linked kinase (ILK) and its interacting proteins, such as CH-ILKBP (alpha-parvin), paxillin, and PINCH in coupling integrins to the actin cytoskeleton and signaling complexes. Genetic studies in Drosophila, Caenorhabditis elegans, and mice point to an essential role of ILK as an adaptor protein in mediating integrin-dependent cell attachment and cytoskeletal organization. Here we demonstrate, using several different approaches, that inhibiting ILK kinase activity, or expression, results in the inhibition of cell attachment, cell migration, F-actin organization, and the specific cytoskeletal localization of CH-ILKBP and paxillin in human cells. We also demonstrate that the kinase activity of ILK is elevated in the cytoskeletal fraction and that the interaction of CH-ILKBP with ILK within the cytoskeleton stimulates ILK activity and downstream signaling to PKB/Akt and GSK-3. Interestingly, the interaction of CH-ILKBP with ILK is regulated by the Pi3 kinase pathway, because inhibition of Pi3 kinase activity by pharmacological inhibitors, or by the tumor suppressor PTEN, inhibits this interaction as well as cell attachment and signaling. These data demonstrate that the kinase and adaptor properties of ILK function together, in a Pi3 kinase-dependent manner, to regulate integrin-mediated cell attachment and signal transduction.
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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 | 0.000 |
| 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 | 0.001 |
| 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".