DEVELOPING A MODEL OF GLIOBLASTOMA MULTIFORME WITH VASCULARIZED CEREBRAL ORGANOIDS
Bibliographic record
Abstract
Glioblastoma Multiforme (GBM) is the most aggressive neurological malignancy with unpreventable recurrence. This cancer is heterogeneous in its cellular composition and genetic profile making it highly adaptable to treatment. A treatment-evading glioblastoma stem cell (GSC) is suspected to regrow the tumour and lead to recurrence. Cerebral organoid (CO) GBM models have been used to study tumour initiation, formation, and invasion. Given the vast differences between primate and non-primate brains, COs offer a 3D human-specific microenvironment to model GBM. Results from a treatment dosage response on patient-derived GBM cell lines suggest that conventional orbital culture COs are unable to withstand the level of radiation and chemotherapy required to achieve the level of cancer cell elimination similar to which is seen in patients. Conventional COs also lack stromal components of GBM recurrence such as vasculature and immune component. Our group has developed a vascularized cerebral organoid (vCO) model for recurrent GBM. vCOs display an expanded glial population, which is suggestive of an accelerated developmental trajectory. Co-culturing GBM with vCOs exhibited significant hydrogel peeling which is aligned with fibrin degradation and ECM remodelling properties associated with GBM.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".