Dynamic CTC phenotypes in metastatic prostate cancer models visualized using magnetic ranking cytometry
Bibliographic record
Abstract
Tumors can shed thousands of cells into the circulation daily. These circulating tumor cells (CTCs) are heterogeneous, and their phenotypes change dynamically. Real-time monitoring of CTC phenotypes is crucial to elucidate the role of CTCs in the metastatic cascade. Here, we monitor phenotypic changes in CTCs in mice xenografted with tumors with varying aggressiveness during cancer progression and a course of chemotherapy to study the metastatic potential of CTCs and changes in the properties of these cells in response to treatment. A new device that enables magnetic ranking cytometry (MagRC) is employed to profile the phenotypic properties of CTCs. Overall, CTCs from metastatic xenografts in mice display dynamic and heterogeneous profiles while non-metastatic models had static profiles. Decreased heterogeneity followed by a reduction in metastasis incidence was observed after a course of chemotherapy administered to highly metastatic xenografts. Phenotypic profiling of CTCs could be employed to monitor disease progression and predict therapeutic responses.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".