Renal carcinoma CD105−/CD44− cells display stem-like properties in vitro and form aggressive tumors in vivo
Bibliographic record
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer. Prognosis for ccRCC is generally poor since it is largely resistant to chemo- and radiotherapy. Many studies suggested that cancer stem cells/tumor initiating cells (CSCs/TICs) are responsible for development of tumor, disease progression, aggressiveness, metastasis and drug resistance. However, tumorigenic potential of CSCs/TICs isolated from established RCC cell lines - basic ccRCC research model - has never been investigated in vivo. CD105+, CD105-, CD44+ and CD44- as well as CD44-/CD105- CD44+/CD105+ and CD44-/CD105+ cells were isolated from Caki-1 RCC cell line, confirming coexistence of multiple subpopulations of stem-related phenotype in stable cell line. Sorted cells were injected subcutaneously into NOD SCID mice and tumor growth was monitored with MRI and PET/CT. Tumor growth was observed after implantation of CD105+, CD44+, CD44-, CD44-/CD105+ and CD44-/CD105- but not CD105- or CD44+/CD105+. Implantation of CD44-/CD105- cells induced tumors that were characterized by longer T1 and distinct metabolic pattern than other tumors. All the tumors were characterized by low uptake of [18F]FDG. CD105+ and CD44- tumors expresses Nanog and Oct-4, while CD44- tumors additionally expressed endothelial cell marker - CD31.
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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) | 0.002 | 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".