Tissue Factor and Cancer Stem Cells
Bibliographic record
Abstract
A common feature in the progression of multiple human malignancies is the protracted deregulation of the coagulation system, often referred to as cancer coagulopathy. Indeed, cancer cells and their vascular stroma often exhibit procoagulant properties, of which deregulation of tissue factor (TF) expression is a notable, although not the sole example. These changes can be traced to oncogenic influences affecting epidermal growth factor receptor (EGFR), EGFRvIII, K-ras, p53, PTEN, and probably many other proto-oncogenes and tumor suppressors in tumor parenchyma. Cancer stem cells (CSCs)/tumor initiating cells (TICs) are thought to represent the primary target and the main cellular effector through which oncogenic mutations exert their tumor-inducing effects. In so doing, CSCs/TICs depend on interactions with the tumor vasculature, which forms supportive niches for their clonal growth. We postulate that TF contributes to these interactions (directly or indirectly) through procoagulant and signaling effects, the latter executed in concert with juxtaposed protease activated receptors (mainly PAR-1 and PAR-2). TF/PAR system acts as a "blood sensing" mechanism, whereby cancer cells, including CSCs/TICs, may respond to plasma proteases (Factors VIIa, Xa, and IIa) and their related microenvironmental changes (fibrin deposition, activation of platelets). A growing body of still largely circumstantial evidence suggests that these events may contribute to the CSC/TIC niche, which could influence tumor initiation, metastasis, recurrence, and therapeutic intractability. Indeed, certain types of cancer cells harboring markers of CSCs (CD133) exhibit elevated TF expression and depend on this receptor to efficiently initiate tumor growth. We propose that both tumor cell-associated and host-related TF could influence the properties of CSCs, and that agents targeting the TF/PAR system may represent a hitherto unappreciated therapeutic opportunity to control cancer progression by influencing the CSC/TIC compartment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 | 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".