Evidence of MTCBP‐1 interaction with the cytoplasmic domain of MT1‐MMP: Implications in the autophagy cell index of high‐grade glioblastoma
Bibliographic record
Abstract
Progression of astrocytic tumors is, in part, related to their dysregulated autophagy capacity. Recent evidence indicates that upstream autophagy signaling events can be triggered by MT1-MMP, a membrane-bound matrix metalloproteinase that contributes to the invasive phenotype of brain cancer cells. The signaling functions of MT1-MMP require its intracellular domain, and recent identification of MTCBP-1, a cytoplasmic 19 kDa protein involved in the inhibition of MT1-MMP-mediated cell migration, suggests that modulation of MT1-MMP cytoplasmic domain-mediated signaling may affect other carcinogenic processes. Using qPCR and screening of cDNA generated from brain tumor tissues of grades I, II, III, and IV, MT1-MMP gene expression was found to correlate with increased grade of tumors. Inversely, MTCBP-1 expression decreased with increasing grade of brain tumor. Confocal microscopy and fluorescence resonance energy transfer (FRET) analysis revealed that overexpressing a cytoplasmic-deleted MT1-MMP recombinant protein mutant prevented MTCBP-1 recruitment to the intracellular leaf of plasma membrane in U87 glioblastoma cells. The interaction between MTCBP-1 and the 20 amino acids peptide representing the MT1-MMP cytoplasmic domain was confirmed by surface plasmon resonance. Overexpression of a full-length Wt-MT1-MMP triggered acidic autophagy vesicle formation and autophagic puncta formation for green fluorescent microtubule-associated protein 1 light chain 3 (GFP-LC3). Autophagic vesicles and GFP-LC3 puncta formation were abrogated in the presence of MTCBP-1. Our data elucidate a new role for MTCBP-1 regulating the intracellular function of MT1-MMP-mediated autophagy. The inverse correlation between MTCBP-1 and MT1-MMP expression with brain tumor grades could also contribute to the decreased autophagic index observed in high-grade tumors.
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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".