<i>On-chip</i> perivascular niche with patient-derived glioma cells
Bibliographic record
Abstract
Abstract Glioblastoma multiforme (GBM), is the most common and the most aggressive type of primary brain malignancy. Glioblastoma stem- like cells (GSCs) are able to migrate in vascular niches within or away from the tumour mass, increasing tumour resistance to patient treatments and contributing to relapses. To study individual GSCs migration and their interactions with the microenvironment in the vasculature, there is a need to develop a model of human blood vessels in vitro . Herein, we report a systematic study on the interaction between patient-derived glioma stem- like cell lines with different organotypic perivascular niche models. A microfluidic chip integrated with an extracellular matrix was fabricated to support the culture of rounded microvessels, formed with endothelial cells from three different organs, (1) human brain microvascular endothelial cells (hCMEC/D3), (2) human umbilical vein endothelial cells (HUVECs) and, (3) human lung microvascular endothelial cells (HMVEC-L). Three-dimensional (3D) cell culture retains selected adherent and tight junction markers of the endothelial cells, and the stemness-related genes of GSCs. We optimized the experimental protocol to perform qPCR, and western blot on the co-cultured GSCs with endothelial cells forming microvessels. Endpoint biological assays showed upregulation of neovascularization-related genes in endothelial cells (e.g., angiopoietins, vascular endothelial growth factor receptors) resulted after their co-culture with GBM cells. Moreover, we measured cancer cell speed and polarization during migration towards the endothelial cell formed vessel by live-cell imaging showing that organotypic (brain cancer cells – brain endothelial microvessel) interactions differ from those within non-tissue specific vascular niches. The development and optimization of this 3D microfluidic device could provide the next level of complexity of an in vitro system to study the influence of glioma cells on normal brain endothelium. More importantly, it enables the possibility to conduct comparative studies to dissect the influence of 3D culture, microvessel architecture and organotypic vessel types on glioma cells’ stemness and migration.
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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 | 0.001 |
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".