Frequency of cells expressing CD44, a Head and Neck cancer stem cell marker: Correlation with tumor aggressiveness
Bibliographic record
Abstract
BACKGROUND: We previously identified by flow cytometry a Lineage-CD44+ (Lin-CD44+) subpopulation of cells with cancer stem cell properties in head and neck squamous cell carcinoma (HNSCC). We now correlate clinical and histologic factors with Lin-CD44+ cell frequency. METHODS: The study included 31 patients with HNSCC, of whom 87% had stage IV disease. The frequency of Lin-CD44+ cells and the success of xenografting patient tumors in mice were correlated with clinical and pathologic data. RESULTS: The mean frequency of Lin-CD44+ cells was 25% (0.4%-81%). It was 36% in patients who had recurrence versus 15% for those without recurrence (p = .04). Successful xenograft implantation occurred in 53%. Seventy-five percent of patients with successful xenografts had recurrence versus 21% of patients with unsuccessful xenografts (p = .003). CONCLUSIONS: Successful xenograft implantation and a high frequency of Lin-CD44+ cells correlate with known poor prognostic factors such as advanced T classification and recurrence. These findings may support the stem cell concept in HNSCC.
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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 | 0.001 |
| 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) | 0.002 | 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".