The Hyaluronan Receptors CD44 and Rhamm (CD168) Form Complexes with ERK1,2 That Sustain High Basal Motility in Breast Cancer Cells
Bibliographic record
Abstract
CD44 is an integral hyaluronan receptor that can promote or inhibit motogenic signaling in tumor cells. Rhamm is a nonintegral cell surface hyaluronan receptor (CD168) and intracellular protein that promotes cell motility in culture. Here we describe an autocrine mechanism utilizing cell surface Rhamm-CD44 interactions to sustain rapid basal motility in invasive breast cancer cell lines that requires endogenous hyaluronan synthesis and the formation of Rhamm-CD44-ERK1,2 complexes. Motile/invasive MDA-MB-231 and Ras-MCF10A cells produce more endogenous hyaluronan, cell surface CD44 and Rhamm, an oncogenic Rhamm isoform, and exhibit more elevated basal activation of ERK1,2 than less invasive MCF7 and MCF10A breast cancer cells. Furthermore, CD44, Rhamm, and ERK1,2 uniquely co-immunoprecipitate and co-localize in MDA-MB-231 and Ras-MCF10A cells. Combinations of anti-CD44, anti-Rhamm antibodies, and a MEK1 inhibitor (PD098059) had less-than-additive blocking effects, suggesting the action of all three proteins on a common motogenic signaling pathway. Collectively, these results show that cell surface Rhamm and CD44 act together in a hyaluronan-dependent autocrine mechanism to coordinate sustained signaling through ERK1,2, leading to high basal motility of invasive breast cancer cells. Therefore, an effect of CD44 on tumor cell motility may depend in part on its ability to partner with additional proteins, such as cell surface Rhamm.
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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 | 0.001 |
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".