TMOD-26. ESTABLISHING A PATIENT-DERIVED, IN-VITRO ORGANOTYPIC SLICE CULTURE MODEL OF GBM
Bibliographic record
Abstract
Abstract Glioblastoma Multiforme (GBM) is the most common primary malignant brain tumour. This tumour is universally fatal with a median survival of 15 months. Driving this pathology is an extremely heterogeneic tumour and complex tumour microenvironment. GBM research is primarily conducted using immortalized or primary cell lines due to their practicality and reproducibility. However, these cell lines do not effectively recapitulate the tumour microenvironment. Mouse models address these shortcomings but are laborious and expensive. We propose to utilize a patient derived organotypic culture model of GBM as an intermediary. We have utilized this model to test genetic manipulation via lentiviral transduction and the feasibility of utilizing this model to understand patient derived extracellular vesicles (EVs). We have sectioned and cultured patient derived organotypic models for 14 days without loss of viability. To determine if these organotypic cultures are amenable to lentiviral manipulation, tissue sections were transduced with far-red fluorescent lentivirus and efficiency determined by confocal laser scanning microscopy (CLSM) and flow cytometry (FC). To determine feasibility as a model for EVs, media obtained from patient-derived organotypic cultures was analyzed by western blot, nanoparticle tracking analysis (NTA), and nanoFlow Cytometry (nFC). In the future these EVs will be compared to those found in patient serum. The model of GBM has been lentivirally transduced to express a far-red fluorescent vector in approximately 15% of the slice, quantified by CLSM and FC. EV-sized particles positive for canonical EV markers have been identified in the media by NTA, nFC and western blot. Using lentiviral-mediated genetic engineering and emerging EV science, this organotypic slice culture models yields exciting utility in GBM research. The established organotypic slice culture model will likely be a valuable tool in the study of GBM biology and EV dynamics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".