Epigenetic Modification of Von Willebrand Factor (VWF) Leads to its Expression in Cancer Cells with Increased Metastatic Activity
Bibliographic record
Abstract
VWF is an adhesive procoagulant protein that is exclusively expressed in endothelial cell (EC) and megakaryocytes. It is key initiator of blood clotting cascade. Increased plasma levels of VWF and alterations in coagulation system in patients with metastasis and cancer progression are reported. We hypothesised that a subpopulation of some cancer cells of non‐endothelial origin may acquire VWF expression and as a result develop enhanced metastatic potential. RT‐PCR, western blot and Immunoflourescent (IF) analyses showed significant levels of VWF expression in an osteosarcoma (Saos2) and glioma (U251, M016, M049) cell lines. Chromatin IP assays demonstrated a similar pattern of transcription factors binding as is observed for VWF gene in EC. The epigenetic modification analysis showed that histone modification of the VWF promoter in glioma (U251, M016, M049) and Saos2 is consistent with transcriptionally active VWF promoter. In vitro cell‐cell interaction analyses showed that cancer cell lines expressing VWF, exhibited increased affinity to adhere to the platelets and an EC monolayer under sheer stress. IF analyses of human glioma tumor samples, demonstrated VWF expression in some cells of non‐endothelial origin in the tumor region, highly suggestive of VWF expression in a subset of glioma cancer cells. Chick Chorioallantoic Membrane assay showed increased extravasation and metastatic lesions for cancer cells expressing VWF. A subpopulation of cancer cells of non‐endothelial origin acquires denovo expression of VWF as a result of epigenetic modification of the VWF promoter. Acquired VWF expressions by cancer cells increase their adhesive properties and may contribute to their metastatic potential.
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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".