Interaction of Munc18c and syntaxin4 facilitates invadopodium formation and extracellular matrix invasion of tumor cells
Bibliographic record
Abstract
Tumor cell invasion involves targeted localization of proteins required for interactions with the extracellular matrix and for proteolysis. The localization of many proteins during these cell–extracellular matrix interactions relies on membrane trafficking mediated in part by SNAREs. The SNARE protein syntaxin4 (Stx4) is involved in the formation of invasive structures called invadopodia; however, it is unclear how Stx4 function is regulated during tumor cell invasion. Munc18c is known to regulate Stx4 activity, and here we show that Munc18c is required for Stx4-mediated invadopodium formation and cell invasion. Biochemical and microscopic analyses revealed a physical association between Munc18c and Stx4, which was enhanced during invadopodium formation, and that a reduction in Munc18c expression decreases invadopodium formation. We also found that an N-terminal Stx4-derived peptide associates with Munc18c and inhibits endogenous interactions of Stx4 with synaptosome-associated protein 23 (SNAP23) and vesicle-associated membrane protein 2 (VAMP2). Furthermore, expression of the Stx4 N-terminal peptide decreased invadopodium formation and cell invasion in vitro . Of note, cells expressing the Stx4 N-terminal peptide exhibited impaired trafficking of membrane type 1 matrix metalloproteinase (MT1-MMP) and EGF receptor (EGFR) to the cell surface during invadopodium formation. Our findings implicate Munc18c as a regulator of Stx4-mediated trafficking of MT1-MMP and EGFR, advancing our understanding of the role of SNARE function in the localization of proteins that drive tumor cell invasion.
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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".