Comparative single‐cell transcriptomic profiling of patient‐derived renal carcinoma cells in cellular and animal models of kidney cancer
Why this work is in the frame
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Bibliographic record
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer that often displays resistance to conventional cancer therapies, including chemotherapy and radiation therapy. Targeted treatments, including immunotherapies and small molecular inhibitors, have been associated with improved outcomes. However, variations in the patient response and the development of resistance suggest that more models that better recapitulate the pathogenesis and metastatic mechanisms of ccRCC are required to improve our understanding and disease management. Here, we examined the transcriptional landscapes of in vitro cell culture as well as in vivo orthotopic and metastatic NOD/SCID-γ mouse models of ccRCC using a single patient-derived RCC243 cell line to allow unambiguous comparison between models. In our mouse model assays, RCC243 cells formed metastatic tumors, and all tumors retained clear cell morphology irrespective of model type. Notably, gene expression profiles differed markedly between the RCC243 tumor models-cell culture, orthotopic tumors, and metastatic tumors-suggesting an impact of the experimental model system and whether the tumor was orthotopic or metastatic. Furthermore, we found conserved prognostic markers between RCC243 tumor models and human ccRCC patient datasets, and genes upregulated in metastatic RCC243 were associated with worse patient outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it