Cancer-Associated Fibroblasts Drive the Progression of Metastasis through both Paracrine and Mechanical Pressure on Cancer Tissue
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Neoplastic cells recruit fibroblasts through various growth factors and cytokines. These "cancer-associated fibroblasts" (CAF) actively interact with neoplastic cells and form a myofibroblastic microenvironment that promotes cancer growth and survival and supports malignancy. Several products of their paracrine signaling repertoire have been recognized as tumor growth and metastasis regulators. However, tumor-promoting cell signaling is not the only reason that makes CAFs key components of the "tumor microenvironment," as CAFs affect both the architecture and growth mechanics of the developing tumor. CAFs participate in the remodeling of peritumoral stroma, which is a prerequisite of neoplastic cell invasion, expansion, and metastasis. CAFs are not present peritumorally as individual cells but they act orchestrated to fully deploy a desmoplastic program, characterized by "syncytial" (or collective) configuration and altered cell adhesion properties. Such myofibroblastic cohorts are reminiscent of those encountered in wound-healing processes. The view of "cancer as a wound that does not heal" led to useful comparisons between wound healing and tumorigenesis and expanded our knowledge of the role of CAF cohorts in cancer. In this integrative model of cancer invasion and metastasis, we propose that the CAF-supported microenvironment has a dual tumor-promoting role. Not only does it provide essential signals for cancer cell dedifferentiation, proliferation, and survival but it also facilitates cancer cell local invasion and metastatic phenomena.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 it