Oncogenes and Clotting Factors: The Emerging Role of Tumor Cell Genome and Epigenome in Cancer-Associated Thrombosis
Bibliographic record
Abstract
There are emerging linkages between biological and genetic aspects of cancer progression and the mechanisms of cancer-associated thrombosis. It is argued that reciprocal influences between cancer cells, their associated vascular stroma, and the hemostatic system may shape the mechanism of coagulopathy. In this regard, glioblastoma multiforme offers a paradigm where the prevalent occurrence of local microthrombosis and peripheral venous thromboembolism can be linked to the profiles of oncogenic driver mutations and their impact on the expression of coagulation-related genes (coagulome). These relationships can be recapitulated in cellular models of glioblastoma, where the expression of tissue factor, podoplanin, and the release of procoagulant microparticles (extracellular vesicles) remains under the control of oncogenic pathways (epidermal growth factor receptor variant III, isocitrate dehydrogenase 1). These pathways define molecular subtypes of glioblastoma that express differential coagulomes. Moreover, single-cell sequencing of glioblastoma samples reveals a combinatorial rather than common profile of both subtype markers and coagulation-related genes. Based on these emerging observations, the authors suggest that cancers may operate as coagulant composites, where individual cells and their dominant populations express different procoagulant phenotypes, resulting in the net impact on the hemostatic system. They suggest that relating these mechanisms to clinical presentations of thrombosis may facilitate a more causality-based, personalized, and possibly cancer-specific thromboprophylaxis and treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".