Matrix Metalloproteinase-2 and -9 Secreted by Leukemic Cells Increase the Permeability of Blood-Brain Barrier by Disrupting Tight Junction Proteins
Bibliographic record
Abstract
Central nervous system (CNS) involvement remains an important cause of morbidity and mortality in acute leukemia, the mechanisms of leukemic cell infiltration into the CNS have not yet been elucidated. The blood-brain barrier (BBB) makes CNS become a refugee to leukemic cells and serves as a resource of cells that seed extraneural sites. How can the leukemic cells disrupt this barrier and invasive the CNS, even if many of the currently available chemotherapies can not cross the BBB? Tight junction in endothelial cells occupies a central role in the function of the BBB. Except the well known role of degrading extracellular matrix in metastasis of cancer cells, here we show matrix metalloproteinase (MMP)-2 and -9, secreted by leukemic cells, mediate the BBB opening by disrupting tight junction proteins in the CNS leukemia. We demonstrated that leukemic cells impaired tight junction proteins ZO-1, claudin-5 and occludin resulting in increased permeability of the BBB. However, these alterations reduced when MMP-2 and -9 activities were inhibited by RNA interference strategy or by MMP inhibitor GM6001 in an in vitro BBB model. We also found that the disruption of the BBB in company with the down-regulation of ZO-1, claudin-5 and occludin and the up-regulation of MMP-2 and -9 in mouse brain tissues with leukemic cell infiltration by confocal imaging and the assay of in situ gelatin zymography. Besides, GM6001 protected all mice against CNS leukemia. Our findings suggest that the degradation of tight junction proteins ZO-1, claudin-5 and occludin by MMP-2 and -9 secreted by leukemic cells constitutes an important mechanism in the BBB breakdown which contributes to the invasion of leukemic cells to the CNS in acute leukemia.
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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 | 0.000 |
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".