Tissue factor expression provokes escape from tumor dormancy and leads to genomic alterations
Bibliographic record
Abstract
The coagulation system links immediate (hemostatic) and late (inflammatory, angiogenic) tissue responses to injury, a continuum that often is subverted in cancer. Here we provide evidence that tumor dormancy is influenced by tissue factor (TF), the cancer cell-associated initiator of the coagulation system and a signaling receptor. Thus, indolent human glioma cells deficient for TF remain viable but permanently dormant at the injection site for nearly a year, whereas the expression of TF leads to a step-wise transition to latent and overt tumor growth phases, a process that is preceded by recruitment of vascular (CD105(+)) and myeloid (CD11b(+) and F4/80(+)) cells. Importantly, the microenvironment orchestrated by TF expression drives permanent changes in the phenotype, gene-expression profile, DNA copy number, and DNA methylation state of the tumor cells that escape from dormancy. We postulate that procoagulant events in the tissue microenvironment (niche) may affect the fate of occult tumor cells, including their biological and genetic progression to initiate a full-blown malignancy.
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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".