CRB3A Controls the Morphology and Cohesion of Cancer Cells through Ehm2/p114RhoGEF-Dependent Signaling
Bibliographic record
Abstract
The transmembrane protein CRB3A controls epithelial cell polarization. Elucidating the molecular mechanisms of CRB3A function is essential as this protein prevents the epithelial-to-mesenchymal transition (EMT), which contributes to tumor progression. To investigate the functional impact of altered CRB3A expression in cancer cells, we expressed CRB3A in HeLa cells, which are devoid of endogenous CRB3A. While control HeLa cells display a patchy F-actin distribution, CRB3A-expressing cells form a circumferential actomyosin belt. This reorganization of the cytoskeleton is accompanied by a transition from an ameboid cell shape to an epithelial-cell-like morphology. In addition, CRB3A increases the cohesion of HeLa cells. To perform these functions, CRB3A recruits p114RhoGEF and its activator Ehm2 to the cell periphery using both functional motifs of its cytoplasmic tail and increases RhoA activation levels. ROCK1 and ROCK2 (ROCK1/2), which are critical effectors of RhoA, are also essential to modulate the cytoskeleton and cell shape downstream of CRB3A. Overall, our study highlights novel roles for CRB3A and deciphers the signaling pathway conferring to CRB3A the ability to fulfill these functions. Thereby, our data will facilitate further investigation of CRB3A functions and increase our understanding of the cellular defects associated with the loss of CRB3A expression in cancer cells.
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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 | 0.001 |
| 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".