EPCO-27. GLIOMA SINGLE CELL MULTI-OMIC ANALYSES REVEALS REGULATORS OF PLASTICITY AND ADAPTIVE STRESS RESPONSE
Bibliographic record
Abstract
Abstract Extensive intra- and intertumoral heterogeneity in glioma contributes to therapeutic resistance and poor patient outcomes. Alterations to DNA methylation (DNAme) modulate epigenetic homeostasis, allowing tumor cells to sample alternative cell states to promote tumorigenesis. However, the epigenetic mechanisms that promote cellular plasticity and regulate cell states are still poorly understood. To characterize the epigenetic mechanisms underlying glioma heterogeneity we profiled 914 single-cell methylomes, 55,284 single-cell transcriptomes, and bulk whole genomes across 11 patient samples spanning initial and recurrent time points and 3 molecular subtypes delineated by IDH mutation status. Local DNAme disorder, defined as epimutation burden, was increased in tumor cells relative to nontumor cells, higher in IDH wild-type than in IDH mutant glioma and was positively associated with copy number alteration (CNA). Epimutation was positively associated with transcriptional variability and enriched at genes involved in cellular differentiation. Epimutation was also increased in the binding sites of transcription factors (TFs) associated with response to extracellular stimuli, suggesting that stochastic DNAme alterations enable cellular plasticity and diverse responses to microenvironmental stressors. Integrative clustering of DNAme and scRNAseq profiles defined stem-like and differentiated-like cell states which exhibited differences in TF activity. Stem-like cells were enriched for differentially methylated binding sites of TFs associated with hypoxia response. scDNAme and scRNAseq-derived copy number profiles were compared with bulk copy number profiles and inferred tumor phylogenies to assess how the timing of CNAs impact epigenetic instability, with results suggesting that early CNA events propagate both genetic and epigenetic heterogeneity. Bulk longitudinal data was used to validate the relationship of epigenetic instability with CNA burden as well as differentially methylated binding sites of cell stress response TFs. Our work suggests that local DNAme disorder promotes cellular plasticity and enables adaptive response to cellular stress such as hypoxia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".