Staurosporine Induced Apoptosis May Activate Cancer Stem-Like Cells (CD44<sup>+</sup>/CD24<sup>-</sup>) in MCF-7 by Upregulating Mucin1 and EpCAM
Bibliographic record
Abstract
Malignant tumors recur after chemotherapy. A small population of cancer stem-like cells within tumors is now generally considered the prime source of the recurrence. To better understand how cancer stem-like cells induce relapse after fractionated chemotherapy, we examined changes in the CD44(+)/CD24(-) cancer stem-like cells population and behavior using the breast cancer cell line MCF-7. Our results show that apart from an increase in the CD44(+)/CD24(-) population, proliferation and clone formation, but not migration, were enhanced after recovery from apoptosis induced by two pulses of staurosporine (STS). The distribution of cells in the cell cycle differed between acutely induced apoptosis and fractionated chemotherapy. Sorted CD44(+)/CD24(-) stem-like cells from MCF-7 cells recovered from STS treatment possessed greater proliferation abilities. We also observed that mucin1 (MUC1) and Epithelial cell adhesion molecule (EpCAM) were up-regulated in abundance coincidently with proliferation and clone formation enhancement. Our findings suggest that fractionated chemotherapy induced apoptosis could stimulate cancer stem-like cell to behave with a stronger malignant property than cancer cells themselves and MUC1 and EpCAM are important factors involving in this process. By demonstrating changes in cancer stem cell during chemotherapy and identifying the crucial factors, we potentially can target them, to eradicate tumors and overcome cancer relapse.
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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 | 0.000 |
| 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".