Breast Cancer Metastatic Dormancy and Relapse: An Enigma of Microenvironment(s)
Bibliographic record
Abstract
Multiple factors act in concert to define the fate of disseminated tumor cells (DTC) to enter dormancy or develop overt metastases. Here, we review these factors in the context of three stages of the metastatic cascade that impact DTCs. First, cells can be programmed within the primary tumor microenvironment to promote or inhibit dissemination, and the primary tumor can condition a premetastatic niche. Then, cancer cells from the primary tumor spread through hematogenous and lymphatic routes, and the primary tumor sends cues systematically to regulate the fate of DTCs. Finally, DTCs home to their metastatic site, where they are influenced by various organ-specific aspects of the new microenvironment. We discuss these factors in the context of breast cancer, where about one-third of patients develop metastatic relapse. Finally, we discuss how the standard-of-care options for breast cancer might affect the fate of DTCs.
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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 | 0.002 | 0.001 |
| 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".