Lipid Raft Association Restricts CD44-Ezrin Interaction and Promotion of Breast Cancer Cell Migration
Bibliographic record
Abstract
Cancer cell migration is an early event in metastasis, the main cause of breast cancer-related deaths. Cholesterol-enriched membrane domains called lipid rafts influence the function of many molecules, including the raft-associated protein CD44. We describe a novel mechanism whereby rafts regulate interactions between CD44 and its binding partner ezrin in migrating breast cancer cells. Specifically, in nonmigrating cells, CD44 and ezrin localized to different membranous compartments: CD44 predominantly in rafts, and ezrin in nonraft compartments. After the induction of migration (either nonspecific or CD44-driven), CD44 affiliation with lipid rafts was decreased. This was accompanied by increased coprecipitation of CD44 and active (threonine-phosphorylated) ezrin-radixin-moesin (ERM) proteins in nonraft compartments and increased colocalization of CD44 with the nonraft protein, transferrin receptor. Pharmacological raft disruption using methyl-β-cyclodextrin also increased CD44-ezrin coprecipitation and colocalization, further suggesting that CD44 interacts with ezrin outside rafts during migration. Conversely, promoting CD44 retention inside lipid rafts by pharmacological inhibition of depalmitoylation virtually abolished CD44-ezrin interactions. However, transient single or double knockdown of flotillin-1 or caveolin-1 was not sufficient to increase cell migration over a short time course, suggesting complex crosstalk mechanisms. We propose a new model for CD44-dependent breast cancer cell migration, where CD44 must relocalize outside lipid rafts to drive cell migration. This could have implications for rafts as pharmacological targets to down-regulate cancer cell migration.
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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".