9 D-SERINE FACILITATES AGGRESSIVE MIGRATION AND STEMNESS OF RECURRENT GLIOBLASTOMA CELLS BY INTERACTING WITH HOST ENDOTHELIAL CELLS
Bibliographic record
Abstract
Abstract Sponsored by BC Cancer Foundation Introduction: Glioblastoma (GBM) cells infiltrate deep brain structures by exploiting perivascular pathways, utilizing stem-like properties and malignant traits to access nutrient-rich environments that support tumor expansion. Our findings suggest that N-methyl-D-aspartate receptors (NMDARs) in brain endothelial cells play a key role in transducing signals initiated by parenchymal cells, facilitating recurrent GBM progression. Hypothesis: D-serine enhances GBM migration and stemness by interacting with host endothelial cells, thereby promoting recurrent tumor aggressiveness. Methods: Patient-derived recurrent GBM cells and human cerebral microvascular endothelial cells (hCMECs/D3) were co-cultured in a transwell system to assess the role of endogenous D-serine in GBM migration and stemness. Pharmacological inhibitors, CRISPR/Cas9-mediated gene silencing, and enzymatic modulation of D-serine metabolism were employed to determine the contribution of GBM-derived D-serine and endothelial NMDARs to these processes. Further, in vivo xenograft experiments employed gene silencing or pharmacological inhibitors of Serine Racemase (SRR) to test the effects of recurrent tumorigenesis. Results: Endothelial cells significantly potentiated GBM migration and stemness in co-culture. D-serine release from GBM cells was confirmed using D-amino acid oxidase, SRR inhibition with phenazine methosulfate (PMS), and CRISPR-mediated SRR silencing, significantly reducing migration and stemness markers. Pharmacological NMDAR antagonism and endothelial GluN1 silencing further mitigated these effects. In vivo, SRR silencing, or inhibition, reduced tumor burden at 4 weeks post-injection and extended survival in GBM-bearing mice. Conclusion: Our findings demonstrate that brain endothelial cells enhance GBM malignancy through D-serine- mediated activation of endothelial NMDARs. This pathway supports GBM migration and stemness, presenting a novel therapeutic target for recurrent GBM treatment.
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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) | 0.002 | 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".