Cancer stem cells are underestimated by standard experimental methods in clear cell renal cell carcinoma
Bibliographic record
Abstract
Rare cancer stem cells (CSC) are proposed to be responsible for tumour propagation and re-initiation and are functionally defined by identifying tumour-initiating cells (TICs) using the xenotransplantation limiting dilution assay (LDA). While TICs in clear cell renal cell carcinoma (ccRCC) appeared rare in NOD/SCID/IL2Rγ(-/-) (NSG) mice, xenografts formed more efficiently from small tumour fragments, indicating the LDA underestimated ccRCC TIC frequency. Mechanistic interrogation of the LDA identified multiple steps that influence ccRCC TIC quantitation. For example, tissue disaggregation destroys most ccRCC cells, common assays significantly overestimate tumour cell viability, and microenvironmental supplementation with human extracellular factors or pharmacological inhibition of anoikis increase clonogenicity and tumourigenicity of ccRCC cell lines and primary tumour cells. Identification of these previously uncharacterized concerns that cumulatively lead to substantial underestimation of TICs in ccRCC provides a framework for development of more accurate TIC assays in the future, both for this disease and for other cancers.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".