Preferential Dependence of Breast Cancer Cells versus Normal Cells on Integrin-Linked Kinase for Protein Kinase B/Akt Activation and Cell Survival
Bibliographic record
Abstract
The emerging paradigm of "oncogene addiction" has been called an Achilles' heel of cancer that can be exploited therapeutically. Here, we show that integrin-linked kinase (ILK), which is either activated or overexpressed in many types of cancers, is a critical regulator of breast cancer cell survival through the protein kinase B (PKB)/Akt pathway but is largely dispensable for the survival of normal breast epithelial cells and mesenchymal cells. We show that inhibition of ILK activity with a pharmacologic ILK inhibitor, QLT-0267, results in the inhibition of PKB/Akt Ser473 phosphorylation, stimulation of apoptosis, and a decrease in mammalian target of rapamycin (mTOR) expression in human breast cancer cells. In contrast, QLT-0267 treatment has no effect on PKB/Akt Ser473 phosphorylation or apoptosis in normal human breast epithelial, mouse fibroblast, or vascular smooth muscle cells. The inhibition of PKB/Akt Ser473 phosphorylation by QLT-0267 in breast cancer cells was rescued by a kinase-active ILK mutant but not by a kinase-dead ILK mutant. Furthermore, a dominant-negative ILK mutant increased apoptosis in the MDA-MB-231 breast cancer cell line but not in normal human breast epithelial cells. The inhibitor was active against ILK isolated from all cell types but did not have any effect on cell attachment and spreading. Our data point to an "ILK addiction" of breast cancer cells whereby they become dependent on ILK for cell survival through the mTOR-PKB/Akt signaling pathway and show that ILK is a promising target for the treatment of breast cancer.
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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".