Profiling Functional and Biochemical Phenotypes of Circulating Tumor Cells Using a Two‐Dimensional Sorting Device
Bibliographic record
Abstract
During cancer progression, tumors shed circulating tumor cells (CTCs) into the bloodstream. CTCs that originate from the same primary tumor can have heterogeneous phenotypes and, while some CTCs possess benign properties, others have high metastatic potential. Deconstructing the heterogeneity of CTCs is challenging and new methods are needed that can sort small numbers of cancer cells according to their phenotypic properties. Here we describe a new microfluidic approach that profiles, along two independent phenotypic axes, the behavior of heterogeneous cell subpopulations. Cancer cells are first profiled according to expression of a surface marker using a nanoparticle-enabled approach. Along the second dimension, these subsets are further separated into subpopulations corresponding to migration profiles generated in response to a chemotactic agent. We deploy this new technique and find a strong correlation between the surface expression and migration potential of CTCs present in blood from mice with xenografted tumors. This system provides an important new means to characterize functional diversity in circulating tumor cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".