Metastatic medulloblastoma remodels the local leptomeningeal microenvironment to promote further metastatic colonization and growth
Bibliographic record
Abstract
Leptomeningeal metastases are the major source of morbidity and mortality for patients with medulloblastoma. The biology of the leptomeningeal metastases and the local tumour microenvironment are poorly characterized. Here we show that metastasis-associated meningeal fibroblasts (MB-MAFs) are transcriptionally distinct and signal extensively to tumour cells and the tumour microenvironment. Metastatic cells secrete platelet-derived growth factor (PDGF) ligands into the local microenvironment to chemotactically recruit meningeal fibroblasts. Meningeal fibroblasts are reprogrammed to become MB-MAFs, expressing distinct transcriptomes and secretomes, including bone morphogenetic proteins. Active bone morphogenetic protein signalling and co-implantation of tumour cells with MB-MAFs enhances the colonization of the leptomeninges by medulloblastoma cells and promotes the growth of established metastases. Furthermore, treatment of patient-derived xenograft mice with a PDGF-receptor-α neutralizing antibody enhances overall survival in vivo. Collectively, our results define a targetable intercellular communication cascade in the metastatic niche to treat leptomeningeal disease. Abeysundara, Rasnitsyn, Fong et al. report that the presence of leptomeningeal metastatic tumour cells leads to the recruitment and remodelling of fibroblasts, which, in turn, facilitate the colonization and outgrowth of medulloblastoma cells in the leptomeninges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".