TMET-46. Investigating metabolic dependencies during the evolution of glioblastoma
Bibliographic record
Abstract
Abstract Glioblastoma (GBM) is the most common and aggressive form of brain cancer in adults, with a five-year survival rate of less than 7%. GBMs are difficult to treat and often recur within a year of diagnosis. Despite many attempts, treatment options have remained stagnant for decades. Clinical trials have yet to reveal an effective therapy for GBMs. This stems, in part, from an incomplete understanding of tumour biology and a lack of appropriate preclinical models to capture patient-specific tumour heterogeneity. Patient-derived organoids (PDOs) have emerged as powerful models that preserve the genetic and phenotypic features of the original tumours, making them valuable for studying disease progression and testing personalized therapies. In this study, we developed and characterized matched sets (n=4) of PDOs from newly diagnosed GBM (ndGBM) and recurrent GBM (rGBM), with a particular focus on investigating the phenotypic, growth, and metabolic changes found upon recurrence. We observed that nd-rGBM PDOs retained key features of the original tumours, including expression of cycling (Ki-67), stem (NES, SOX2), oligodendrocytic (OLIG2), and astrocytic (GFAP) cell markers. Additionally, GBMs exhibited distinct, patient-specific changes in growth phenotype upon recurrence. By assessing mitochondrial and metabolic profiles alongside proliferation, we linked phenotypic growth dynamics with underlying bioenergetics. We found that slow-proliferating GBM samples consistently exhibited characteristics associated with higher oxidative phosphorylation (OxPhos) activity, such as increased membrane polarization and dense cristae, while faster-proliferating tumours relied on glycolysis. These findings suggest that metabolic reprogramming occurs in a patient-specific manner upon recurrence and may drive differential tumor growth. Given the critical role of metabolism in tumour progression and its correlation with prognosis, investigating the metabolic adaptations of nd-rGBM is essential for identifying tumour-specific vulnerabilities. Ultimately, our work may provide insights into GBM tumour evolution, identifying new prognostic markers, and guiding personalized treatment strategies for 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 | 0.000 | 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".