Cancer as a tissue: The significance of cancer‐stromal interactions in the development, morphogenesis and progression of human upper digestive tract cancer
Bibliographic record
Abstract
We review the significance of cancer-stromal interactions (CSIs) in the development, morphogenesis and progression of human gastric and esophageal cancer based on the data obtained from co-culture experiments. Orthotopic fibroblasts in the gastric cancer stroma not only promoted their growth by cancer cells but were also responsible for the mobility, morphogenesis and epithelial-to-mesenchymal transition (EMT) of the cancer cells through CSI. Bone marrow-derived mesenchymal stem cells could be part of the origin of cancer-associated fibroblasts (CAFs) of the gastric cancer providing an advantageous microenvironment for the restoration of cancer stem cells with the induction of the EMT. Tumor-associated macrophages (TAMs) may differentiate from bone marrow-derived monocytes/macrophages within the tumor microenvironment of esophageal cancer and participate in the growth and the progression of esophageal squamous cell carcinomas (ESCCs). Macrophages infiltrated into the intraepithelial neoplastic lesions of the esophagus may function as a biological promoter by promoting the growth and motility of squamous epithelia. Tumor cells build up "cancer as a tissue" by taking advantage of the existing network of growth factors, cytokines and chemokines through the interactions of TAMs, CAFs and cancer cells themselves.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".