Targeting SNARE-Mediated Vesicle Transport to Block Invadopodium-Based Cancer Cell Invasion
Bibliographic record
Abstract
During metastasis, cancer cells can invade extracellular matrix (ECM) through a process mediated by matrix-degrading protrusions of the plasma membrane, termed invadopodia. Formation of invadopodia correlates with cells’ invasive and metastatic potential, and thus presents a potential target for therapeutic approaches to target metastatic progression. Invadopodia formation is dependent on the recruitment of proteins involved in intracellular signaling, actin cytoskeleton remodeling, and proteolytic matrix modification. The latter includes matrix degrading enzymes such as MT1-MMP, MMP2, and MMP9. These essential invadopodium-associated enzymes are required for localized matrix degradation, and their localization at invadopodia is central to invadopodium-based cancer cell invasion. Soluble N -ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) facilitate intracellular vesicle traffic, including that involved in the transport of invadopodium-associated proteins, and in so doing promote modification of ECM and modulation of signaling pathways involved in the movement of cancer cells. Specific SNARE complexes have been found to support invadopodia formation, and these complexes are, in turn, regulated by associated proteins that interact specifically with SNAREs. Targeting SNARE regulatory proteins thus provides a possible approach to disrupt SNARE-dependent delivery of invadopodial proteins, including MT1-MMP, to sites of ECM modification. Here, we review recent studies of SNARE regulators that hold potential as targets for the development of anti-metastatic therapies for patients burdened with invadopodia-forming cancer types.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".