Nucleolin promotes angiogenesis and endothelial metabolism along the oncofetal axis in the human brain vasculature
Bibliographic record
Abstract
Glioblastomas are among the deadliest human cancers and are highly vascularized. Angiogenesis is dynamic during brain development, almost quiescent in the adult brain but reactivated in vascular-dependent CNS pathologies, including brain tumors. The oncofetal axis describes the reactivation of fetal programs in tumors, but its relevance in endothelial and perivascular cells of the human brain vasculature in glial brain tumors is unexplored. Nucleolin is a regulator of cell proliferation and angiogenesis, but its roles in the brain vasculature remain unknown. Here, we studied the expression of Nucleolin in the neurovascular unit in human fetal brains, adult brains, and human gliomas in vivo as well as its effects on sprouting angiogenesis and endothelial metabolism in vitro. Nucleolin is highly expressed in endothelial and perivascular cells during brain development, downregulated in the adult brain, and upregulated in glioma. Moreover, Nucleolin expression correlated with glioma malignancy in vivo. In culture, siRNA-mediated Nucleolin knockdown reduced human brain endothelial cell (HCMEC) and HUVEC sprouting angiogenesis, proliferation, filopodia extension, and glucose metabolism. Furthermore, inhibition of Nucleolin with the aptamer AS1411 decreased brain endothelial cell proliferation in vitro. Mechanistically, Nucleolin knockdown in HCMECs and HUVECs uncovered regulation of angiogenesis involving VEGFR2 and of endothelial glycolysis. These findings identify Nucleolin as a neurodevelopmental factor reactivated in glioma that promotes sprouting angiogenesis and endothelial metabolism, characterizing Nucleolin as an oncofetal protein. Our findings have potential implications in the therapeutic targeting of glioma.
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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".