STEM-14. GROWTH FACTOR RECEPTOR CO-INHERITANCE DURING ASYMMETRIC CELL DIVISION DRIVES THE CANCER STEM CELL PHENOTYPE
Bibliographic record
Abstract
An asymmetric cell division (ACD) produces a stem cell and a differentiating progeny. Thus ACD ensures the generation of organs with heterogeneous cell populations without depleting pools of stem cells with regenerative capacity. Cancer stem cells (CSCs), which are similar to normal stem cells, can self-renew and regenerate tumors with cellular heterogeneity. CSCs are resistant to therapy and play a critical role in tumor recurrence. ACD has been detected in CSCs from many types of tumors, but its role in CSC fate decision has yet to be fully elucidated. A remaining technical limitation is that ACD is often defined retrospectively based on the observation of an asymmetric fate choice by CSC progeny. We previously demonstrated asymmetric inheritance of a surrogate CSC marker, CD133, during mitosis. To prospectively analyze the biological role of this inheritance asymmetry, we have developed a GFP reporter system capable of monitoring the degree of asymmetry of the CSC marker during mitosis. This reporter also revealed the asymmetric co-inheritance of growth factor receptors, the activation of which overrode the effect of a differentiation-inducing condition that suppresses self-renewal capacity and therapeutic resistance of CSCs. Preliminary time lapse-based lineage tracing detected that daughter cells that inherited higher levels of growth factor receptors based on GFP-reporter signal intensity express higher levels of a core stem cell transcription factor compared to their sister cells that inherited lower levels of growth factor receptors. These data suggest that asymmetrically co-inherited growth factor receptors promote the stem cell state in one of the progeny of a CSC undergoing ACD, ensuring the persistence of a therapeutically resistant population.
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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) | 0.004 | 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".