TMIC-15. Reactive Oligodendrocytes Promote Glioblastoma Progression via CCL5/CCR5-Mediated Glioma Stem Cell Maintenance
Bibliographic record
Abstract
Abstract BACKGROUND Glioblastoma (GBM) progression is tightly linked to microenvironmental interactions that remain poorly defined. Oligodendrocyte-lineage cells (OLs), traditionally viewed as passive bystanders, are increasingly recognized in the GBM niche, yet their functional role remains unexplored. METHODS Using integrated single-cell RNA sequencing, spatial transcriptomics, cytokine profiling, and functional assays across primary (newly diagnosed) and recurrent GBM samples, we investigated OL-GBM interactions. An OL meta-atlas encompassing 336,000 OL cells from 226 patients was constructed to contextualize OL phenotypes across CNS pathologies. RESULTS We found OLs are selectively recruited to the GBM tumor border via tumor-secreted CX3CL1 and infiltrate the tumor core at recurrence. Tumor-associated OLs adopt an interferon-driven reactive state, distinct from their healthy counterparts. These reactive OLs secrete pro-tumorigenic cytokines, including CCL5. We show that CCL5 supports GBM cell proliferation, particularly in recurrent GBM. Its receptor, CCR5, was selectively expressed in glioma stem-like cells (GSCs) and correlated with poor prognosis. Genetic and pharmacologic CCR5 inhibition impaired GSC viability, reduced tumor burden, and extended survival in orthotopic xenografts. CONCLUSIONS Our study identifies a previously unrecognized paracrine axis between reactive OLs and GSCs mediated by CCL5/CCR5 signalling. This axis is amplified in recurrence and represents a therapeutic vulnerability in GBM. Targeting microenvironmental contributors such as OLs may complement existing GBM therapies.
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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".