Sunitinib induces early histomolecular changes in a subset of renal cancer cells that contribute to resistance
Bibliographic record
Abstract
Sunitinib is the standard-of-care, first-line treatment for advanced renal cell carcinoma (RCC). Characteristics of treatment-resistant RCC have been described; however, complex tumor adaptation mechanisms obstruct the identification of significant operators in resistance. We hypothesized that resistance is a late manifestation of early, treatment-induced histomolecular alterations; therefore, studying early drug response may identify drivers of resistance. We describe an epithelioid RCC growth pattern in RCC xenografts, which emerges in sunitinib-sensitive tumors and is augmented during resistance. This growth modality is molecularly and morphologically related to the RCC spheroids that advance during in vitro treatment. Based on time-lapse microscopy, mRNA and microRNA screening, and tumor behavior-related characteristics, we propose that the spheroid and adherent RCC growth patterns differentially respond to sunitinib. Gene expression analysis indicated that sunitinib promoted spheroid formation, which provided a selective survival advantage under treatment. Functional studies confirm that E-cadherin is a key contributor to the survival of RCC cells under sunitinib treatment. In summary, we suggest that sunitinib-resistant RCC cells exist in treatment-sensitive tumors and are histologically identifiable.-Lichner, Z., Saleeb, R., Butz, H., Ding, Q., Nofech-Mozes, R., Riad, S., Farag, M., Varkouhi, A. K., dos Santos, C. C., Kapus, A., Yousef, G. M. Sunitinib induces early histomolecular changes in a subset of renal cancer cells that contribute to resistance.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".