ANGI-10GLIOMA-ASSOCIATED MACROPHAGES PROMOTE ENDOTHELIAL CELL DYSFUNCTION
Bibliographic record
Abstract
One of the most prominent features of glioblastoma (GBM) is hyper-vascularization, characterized by abnormal hyper-dilated, distorted, leaky vessels and increased thrombosis. Bone marrow-derived microglia/macrophages are an important host cell population that are actively recruited to the tumour, associate closely with blood vessels, and are thought to provide a supportive role in tumour neo-vascularization. The aim of this study was to investigate the unknown molecular mechanisms of how glioma-associated microglia/macrophages affect endothelial cells to promote neovascularization. Here we examined the effect of conditioned-medium (CM) from M1 (classically activated), M2 (alternatively activated), or glioma neurosphere-associated macrophages (co-cultured) on the expression of angiogenesis genes in human umbilical vein endothelial cells (HUVECs). Strikingly, CM from glioma-associated macrophages produced a substantial upregulation of genes involved in endothelial activation including VCAM-1, ICAM-1, CXCL5, CXCL10, HGF, VEGFC, and SERPINE1 (some up to several thousand-fold increase in expression) in comparison to CM from M1 or M2-polarized macrophages. Gene ontology analysis indicated the possibility of regulation by TNF-α and we therefore examined and confirmed that glioma-associated macrophages show increased secretion of this cytokine. Interestingly, CM from glioma-associated macrophages also led to a downregulation of NOS3 in HUVEC cells, which is known to promote endothelial dysfunction in activated endothelial cells. These findings suggest that glioma-associated macrophages secrete TNF-α, which acts on nearby endothelial cells to promote endothelial activation/ dysfunction. We propose that the pro-inflammatory state of dysfunctional glioma-associated endothelial cells may further increase the recruitment of macrophages through upregulation of adhesion molecules, and promote pro-thrombic properties and vascular leakage that characterize and promote GBM neo-vascularization.
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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".