Mesenchymal Stem Cells and Fibroblasts Contribute to Microvascular Proliferation in Glioblastoma and are Correlated with Immunosuppression and Poor Outcome
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Microvascular proliferation (MVP) is a disease-defining hallmark of glioblastoma and other World Health Organization grade 4 gliomas. MVP also serves as a poor prognostic marker in various solid tumors. Despite its clinical significance, the mechanisms and biological consequences of MVP are controversial and remain unclear. In this study, we performed single-cell RNA sequencing on paired CD45-CD105+ vascular/perivascular stromal cells (PVSC) and CD45+CD105± immune cells from 16 primary glioma patient samples, both with and without MVP. This analysis revealed the presence of developmentally related mesenchymal stem cells alongside cancer-associated fibroblasts, pericytes, fibromyocytes, and smooth muscle cells within the CD45-CD105+ compartment. RNA velocity analysis identified PDGFRB as a putative driver gene guiding mesenchymal stem cells toward more mature PVSCs in the context of MVP. Signaling network analysis and digital spatial profiling uncovered interactions between PDGFRB+ PVSCs and immunosuppressive myeloid cell subsets enriched in the perivascular niche, suggesting targetable receptor-ligand interactions. Additionally, a gene signature of MVP-associated PVSCs from gliomas predicted worse prognosis in multiple other solid tumors. This study provides a transcriptomic cell atlas of PVSCs and immune cells in glioma, helping to refine the biological model of MVP which has traditionally focused on endothelial cells.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it