Insights into cancer metastasis from a clinicopathologic perspective: Epithelial‐Mesenchymal Transition is not a necessary step
Bibliographic record
Abstract
Epithelial-mesenchymal transition (EMT) has been implicated as the critical event initiating cancer invasion and metastasis. After disseminating through the circulation, the malignant cells have been proposed to undergo subsequent mesenchymal-epithelial transition (MET) to form secondary tumors. However, strong evidence from human tumor specimens for this paradigm is lacking. In carcinomas, cancers derived from epithelial tissues, epithelial morphology and gene expression are always retained to some degree. While mesenchymal transdifferentiation may be involved in the pathogenesis of carcinosarcomas, even in these neoplasms, as well as in germ cell tumors capable of multilineage differentiation, the mesenchymal phenotype does not facilitate metastatic progression. Indeed, most cancers invade and travel through lymphatic and blood vessels via cohesive epithelial migration, rather than going through the EMT-MET sequence. EMT gene expression is also consistently associated with high histologic grade and while the transcription factors, Snail, Slug and Twist have traditionally been thought of as inducers of EMT, under certain conditions, they also mediate dedifferentiation and maintenance of the stem cell state. In various malignancies, including basal-like breast cancer and colorectal cancer, the genetically unstable, undifferentiated phenotype predicts early metastatic spread and poor prognosis. This article discusses some of the controversies surrounding differentiation and metastasis from a clinicopathologic perspective and presents evidence that the epithelial phenotype is maintained throughout the process of cancer metastasis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".