Putative Cancer Stem Cell Markers are Frequently Expressed by Melanoma Cells in Vitro and in Situ but are also Present in Benign Differentiated Cells
Bibliographic record
Abstract
BACKGROUND: Currently, there remains an incomplete view of cancer stem cells (CSCs) in solid tumours. METHODS: We studied a panel of putative CSC surface markers (ALDH1A1, ABCG2, CD44v7/8, CD44v10, CD133, CD271, and Nestin) in 40 established melanoma cell lines and four early-passage melanoma strains by flow cytometry. We additionally examined 40 formalin-fixed paraffin-embedded melanoma tissues using immunofluorescence microscopy. This was compared with their expression in healthy skin, normal differentiated melanocytes and fibroblasts. RESULTS: Most of the putative CSC markers were expressed by both melanoma cell lines and tissues. When present, these proteins were expressed by the majority of cells in the population. However, the expression of these markers by cells in healthy skin sections, normal differentiated melanocytes, and fibroblasts revealed that differentiated non-malignant cells also expressed CSC markers indicating that they lack of specificity for CSCs. Culturing cell lines under conditions more characteristic of the tumour microenvironment upregulated CSC marker expressions in a proportion of cell lines, which correlated with improved cell growth and viability. CONCLUSIONS: . Further, we showed that these putative markers lack specificity for CSCs because they are also expressed in differentiated non-malignant cell types (melanocytes, fibroblasts, and skin), which could limit their use as therapeutic targets. These data are consistent with the emerging notion of CSC plasticity and phenotype switching within cancer cell populations.
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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 | 0.000 |
| 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".