OPTC-5. Molecular signatures of podoplanin expressing glioblastoma cell subsets with putative role in cancer associated thrombosis and microthrombosis
Bibliographic record
Abstract
Abstract Vascular anomalies, including thrombosis, are a hallmark of glioblastoma (GBM) and an aftermath of dysregulated cancer cell genome and epigenome. Upregulation of podoplanin (PDPN) by cancer cells has recently been linked to an increased risk of venous thromboembolism in glioblastoma patients. Thus, regulation of this platelet activating transmembrane protein by transforming events and release from cancer cells into the circulation are of considerable interest. We took advantage of single-cell and bulk GBM transcriptome dataset mining and investigated the pattern of PDPN expression across several databases. Our analysis indicated that PDPN is expressed by distinct (mesenchymal) glioblastoma cell subpopulations and is downregulated by oncogenic mutations of EGFR and IDH1 genes, via changes in chromatin modifications (EZH2) and DNA methylation, respectively. Additionally, we utilized isogenic and stem GBM cell lines, xenograft models in mice, ELISA assays for PDPN, tissue factor (TF), platelet factor 4 (PF4) and clotting activation markers (D-dimer), and multicolor nano-flow cytometry to show that GBM cells exteriorize PDPN and/or TF as cargo of exosome-like coagulant extracellular vesicles EVs. We also documented an increase of platelet activation (PF4) or coagulation markers (D-dimer) in mice harboring the corresponding PDPN- or TF-expressing glioma xenografts, respectively. While PDPN was a dominant regulator of systemic platelet activation, co-expression of PDPN and TF impacted local microthrombosis. Our work suggests that distinct cellular subsets drive multiple facets of GBM-associated thrombosis and may represent targets for diagnosis and intervention.
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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) | 0.001 | 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".