Role of the Microenvironment in Liver Metastasis: From Pre- to Prometastatic Niches
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
Liver metastases remain a major barrier to successful management of malignant disease, particularly for cancers of the gastrointestinal tract but also for other malignancies, such as breast carcinoma and melanoma. The ability of metastatic cells to survive and proliferate in the liver is determined by the outcome of complex, reciprocal interactions between tumor cells and different local resident subpopulations, including the sinusoidal endothelium, stellate, Kupffer, and inflammatory cells that are mediated through cell-cell and cell-extracellular matrix adhesion and the release of soluble factors. Cross-communication between different hepatic resident cells in response to local tissue damage and inflammation and the recruitment of bone marrow cells further enhance this intercellular communication network. Both resident and recruited cells can play opposing roles in the progression of metastasis, and the balance of these divergent effects determines whether the tumor cells will die, proliferate, and colonize the new site or enter a state of dormancy. Moreover, this delicate balance can be tilted in favor of metastasis, if factors produced by the primary tumor precondition the microenvironment to form niches of activated resident cells that promote tumor expansion. This review aims to summarize current knowledge on these diverse interactions and the impact they can have on the clinical management of hepatic metastases. Clin Cancer Res; 22(24); 5971-82. ©2016 AACR.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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