Colonization of distant organs by tumor cells generating circulating homotypic clusters adaptive to fluid shear stress
Bibliographic record
Abstract
Once disseminated tumor cells (DTCs) arrive at a metastatic organ, they remain there, latent, and become seeds of metastasis. However, the clonal composition of DTCs in a latent state remains unclear. Here, we applied high-resolution DNA barcode tracking to a mouse model that recapitulated the metastatic dormancy of head and neck squamous cell carcinoma (HNSCC). We found that clones abundantly circulated peripheral blood dominated DTCs. Through analyses of multiple barcoded clonal lines, we identified specific subclonal population that preferentially generated homotypic circulating tumor cell (CTC) clusters and dominated DTCs. Despite no notable features under static conditions, this population significantly generated stable cell aggregates that were resistant to anoikis under fluid shear stress (FSS) conditions in an E-cadherin-dependent manner. Our data from various cancer cell lines indicated that the ability of aggregate-constituting cells to regulate cortical actin-myosin dynamics governed the aggregates' stability in FSS. The CTC cluster-originating cells were characterized by the expression of a subset of E-cadherin binding factors enriched with actin cytoskeleton regulators. Furthermore, this expression signature was associated with locoregional and metastatic recurrence in HNSCC patients. These results reveal a biological selection of tumor cells capable of generating FSS-adaptive CTC clusters, which leads to distant colonization.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".