TMIC-12. RAB27 REGULATION OF VASCULAR WALL INTEGRITY MEDIATES T-CELL INFILTERATION IN GLIOBLASTOMA
Bibliographic record
Abstract
Abstract Endothelial secretome exerts a potent influence on the phenotype of cancer cells and immune microenvironment. Recently, we have reported that glioblastoma stem cells acquire a more aggressive mesenchymal state under influence of vascular endothelial cell derived extracellular vesicles (EVs). Since Rab27, GTPases involved in multiple aspects of EV (exosome) biogenesis, has been implicated in control of angiogenic pathways through regulation of VEGFR1 turnover and possibly other mechanisms, we interrogated the role of Rab27 in the function of normal and glioblastoma associated brain microvasculature. Using mice with disrupted Rab27a and Rab27b isoforms, we documented that these proteins control development and stability of the brain vasculature including pathological angiogenesis in glioblastoma. Thus, relative to wild-type C57bl/6 (WT) and double heterozygous Rab27a+/-;Rab27b+/- (dHET) mice, animals with Rab27a/b double knock-out (Rab27a/b-dKO) exhibit reduced microvascular density in brain cortices. When neoangiogensis was induced following orthotopic inoculation of mouse glioma cells (GL261), multiple morphological anomalies were observed in the tumour vasculature relative to tumours established in control mice. Moreover, vascular permeability of tumours in Rab27a/b-dKO mice markedly exceeded that of similar tumours in wild type or heterozygous controls resulting in augmented T-cell infiltration into the otherwise ‘cold’ brain tumor microenvironment. Our results suggest that key switches in the cellular secretome, such as Rab27a and Rab27b, may impact endothelial membrane dynamic and intercellular interactions capabilities, whereby they may play a critical role in ensuring the stability and sustained cellular barrier function of the vasculature during brain tumour progression. Therapeutic implications of these findings are being explored.
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 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) | 0.002 | 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".