Biologic and experimental variation of measured cancer stem cells
Bibliographic record
Abstract
Whereas it has become clear that measured stem cell frequencies in tumors greatly depend on the assay system used, the research focus now shifts towards identification of the biologic variability of cancer stem cells in different disease subsets. In a recent study we quantified the frequency and in vitro expansion potential of leukemia initiating cells in a murine model of acute myeloid leukemia driven either by retroviral overexpression of MN1 and a control vector, or by MN1 and a HOX gene through limiting dilution transplantation assays in syngeneic mice. Both leukemia-initiating cell frequency and expansion potential were increased by over two orders of magnitude in the two-oncogene compared to the one-oncogene model, documenting the functional heterogeneity of leukemia-initiating cells. Loss-of-function studies showed that STAT5b and STAT1 are critical for the enhanced self-renewal activity. Here we discuss implications of our findings and potential sources of experimental variability of measured leukemia or cancer stem cell frequencies.
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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 | 0.006 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".