Molecular Mechanisms of Tumor Invasion and Metastasis: An Integrated View
Bibliographic record
Abstract
As tumors progress to increased malignancy, cells within them develop the ability to invade into surrounding normal tissues and through tissue boundaries to form new growths (metastases) at sites distinct from the primary tumor. The molecular mechanisms involved in this process are incompletely understood but those associated with cell-cell and cell-matrix adhesion, with the degradation of extracellular matrix, and with the initiation and maintenance of early growth at the new site are generally accepted to be critical. This article discusses current knowledge of molecular events involved in these various processes. The potential role of adhesion molecules (eg. integrins and cadherins) has undergone a major transition over the last ten years, as it has become apparent that such molecules play a major role in signaling from outside to inside a cell, thereby controlling how a cell is able (or not) to sense and interact with its local environment. Similarly the roles of proteolytic enzymes and their inhibitors (eg. matrix metalloproteinases and TIMPs) have also expanded as it has become apparent that they not only have the abilities to break down the components of the extracellular matrix but also are involved in the release of factors which can affect the growth of the tumor cells positively or negatively. Recent work has highlighted the importance of the later, post-extravasational stages of metastasis, where adhesion and proteolysis are now known to play a role along with other processes such as apoptosis, dormancy, growth factor-receptor interactions and signal transduction. Recent work has also demonstrated that not only the immediate cellular microenvironment, in terms of specific cell-cell and cell-matrix interactions, but also the extended cellular microenvironment, in terms of vascular insufficiency and hypoxia in the primary tumor, can modify cellular gene expression and enhance metastasis. Mechanisms of metastasis appear to involve a complex array of genetic and epigenetic changes many of which appear to be specific both for different types of tumors and for different sites of metastasis. Our improved understanding of the expanded roles of the individual molecules involved has resulted in a mechanistic blurring of the previously described discrete stages of the metastatic process.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| 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".