Data from Phenotypic Heterogeneity and Metastasis of Breast Cancer Cells
Bibliographic record
Abstract
Abstract Although intratumoral genomic heterogeneity can impede cancer research and treatment, less is known about the effects of phenotypic heterogeneities. To investigate the role of cell migration heterogeneities in metastasis, we phenotypically sorted metastatic breast cancer cells into two subpopulations based on migration ability. Although migration is typically considered to be associated with metastasis, when injected orthotopically in vivo, the weakly migratory subpopulation metastasized significantly more than the highly migratory subpopulation. To investigate the mechanism behind this observation, both subpopulations were assessed at each stage of the metastatic cascade, including dissemination from the primary tumor, survival in the circulation, extravasation, and colonization. Although both subpopulations performed each step successfully, weakly migratory cells presented as circulating tumor cell (CTC) clusters in the circulation, suggesting clustering as one potential mechanism behind the increased metastasis of weakly migratory cells. RNA sequencing revealed weakly migratory subpopulations to be more epithelial and highly migratory subpopulations to be more mesenchymal. Depletion of E-cadherin expression from weakly migratory cells abrogated metastasis. Conversely, induction of E-cadherin expression in highly migratory cells increased metastasis. Clinical patient data and blood samples showed that CTC clustering and E-cadherin expression are both associated with worsened patient outcome. This study demonstrates that deconvolving phenotypic heterogeneities can reveal fundamental insights into metastatic progression. More specifically, these results indicate that migratory ability does not necessarily correlate with metastatic potential and that E-cadherin promotes metastasis in phenotypically sorted breast cancer cell subpopulations by enabling CTC clustering. Significance: This study employs phenotypic cell sorting for migration to reveal a weakly migratory, highly metastatic breast cancer cell subpopulation regulated by E-cadherin, highlighting the dichotomy between cancer cell migration and metastasis.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.005 | 0.002 |
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".