Investigating the Impact of a Primary Tumor on Metastasis and Dormancy Using MRI: New Insights into the Mechanism of Concomitant Tumor Resistance
Why this work is in the frame
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Bibliographic record
Abstract
Dormant cancer cells, also referred to as quiescent, slowly cycling or "nonproliferative" cells, are believed to contribute to tumor recurrence and present a therapeutic problem because they are nonresponsive to current therapies that target proliferating cells. Concomitant tumor resistance (CTR) is the ability of a primary tumor to restrict the growth of secondary metastases. In this paper, we investigate these 2 cancer concepts using cellular magnetic resonance imaging (MRI). A new model for CTR is presented where a primary mammary fat pad tumor is generated using a human breast cancer cell line (231) and breast cancer brain metastases are generated using a cell line derived from 231 to be brain metastatic (231-BR). Iron oxide particles are used to label the 231BR cells to allow for tracking of the proliferating cells, which form metastases, and the nonproliferating cells, which remain dormant in the brain. Bioluminescence and fluorescence-activated cell sorting are used to validate the MRI data. The presence of a primary 231 mammary fat pad tumor inhibited the formation of MRI-detectable 231BR brain metastases. More iron-retaining cells persisted in the brains of mice with a primary tumor. Bioluminescence and fluorescence-activated cell sorting provide evidence that signal voids detectable by MRI on day 0 represent live, iron-labeled cells in the brain. This work shows that retention of iron by nonproliferative cancer cells can be exploited to monitor the fate of this important cell population in vivo, and it points to a new mechanism for CTR, the enhancement of dormancy by a primary tumor.
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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 | 0.001 |
| 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 it