TMOD-24. PATIENT-DERIVED BRAIN TUMOUR IPSCS: MODELS FOR INVESTIGATING GLIOMA STEMNESS AND DRUG DISCOVERY
Bibliographic record
Abstract
Dysregulated, stem cell-like self-renewal has been implicated in glioma treatment resistance and tumour recurrence. Drugs that eliminate tumour cells possessing this malignant characteristic are urgently needed. It remains, however, an experimental challenge to link heterogeneous glioma genotypes to drug response at scale. To this end, we successfully derived patient-specific induced pluripotent stem cell (iPSC) models from both low- (LGG) and high-grade gliomas (HGG) and developed an initial drug discovery application. Brain tumour tissue, acquired at surgery, was reprogrammed. Derived iPSC models were characterised using pluripotency markers, tri-germinal layer differentiation, gene expression, karyology and deep whole genome sequencing (WGS, iPSC versus parental tumour). Glioma iPSC differentiation in 2-dimensional (adherent, optically clear 96-well imaging plates) and 3-dimensional (organoid) culture was carried out. Gene expression of neural induction and neuronal differentiation was analysed using mRNA-seq. Neural cancer stem cells from each glioma iPSC line were orthotopically implanted in vivo. Reprogrammed cells were confirmed as fully-reprogramed/stable iPSCs, with mutational variants (SNPs, CNVs) preserved as compared to the parental tumours. Glioma iPSC maturation and quantification of TUJ-1 expression indicated a ‘differentiation block’ in the HGG iPSC models. This phenotype was concordant in HGG iPSC-derived tumour organoids which displayed SOX2/MKI67-positive neural rosettes. Consistently, mice developed xenograft tumours with GBM histopathological characteristics. Expression profiling during neuronal differentiation (from iPSC to neural stem cells to neurons) has revealed candidate genes that may be responsible for the phenotypic differences between HGG and control/LGG iPSC models. Our adherent, organoid and in vivo iPSC models may uncover genetic mutations and regulatory networks underlying glioma stem cell self-renewal capability, and provide a basis for industrial-scale drug discovery. Here we have successfully implemented the first stages towards this development (in a 96-well assay format). Ultimately, our patient-derived iPSC-based approach may enable personalised precision medicine strategies against glioma.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".