Abstract 811: Histological heterogeneity contributes to sunitinib resistance in clear cell renal cell carcinoma
Bibliographic record
Abstract
Abstract Introduction: The receptor tyrosine kinase (RTK) inhibitor sunitinib is the first line treatment for advanced clear cell renal cell carcinoma (ccRCC). Sunitinib inhibits angiogenesis via blocking signaling through VEGFR. About 80% of patients develop resistance after a drug-sensitive period. Molecular changes early in treatment may impact drug resistance, but are poorly understood. Experimental Procedures: ACHN, 786-O and Renca cell lines were treated with 1 µM sunitinib. NSG mice were s.c. xenografted with the model cell lines and were treated with sunitinib at 40 mg/kg/day dose. mRNA expression was screened using Illumina HT-12 bead chip array and miRNA expression was assessed by Nanostring nCounter assay. R statistical packages were used for data processing. Reactome and miRPath softwares were used for downstream analysis. Results: Sunitinib treatment of ccRCC xenografts led to several early changes in tumor histology, such as the emergence of live tumor areas within the necrotic spaces. These areas showed membranous staining for E-cadherin, and β-catenin, while the rest of the tumor and vehicle-treated tumors were negative. In vitro model cell lines developed cancer spheroids when treated with sunitinib. Cancer spheroids were highly tumorigenic and metastatic, and expressed several established cancer stem cell markers. ccRCC cancer spheres, but not the 2D adherent cells, showed membranous staining for E-cadherin and β-catenin; similarly to the live tumor areas observed in in vivo sunitinib treatment. In vitro inhibition of E-cadherin by EGTA or by siRNA, interfered with viability of sunitinib treated ccRCC cell lines. Conclusions: Sunitinib treatment causes early phenotypic changes of the tumor in vivo and in vitro. The formation of highly metastatic and tumorigenic cancer spheres in model cell lines is the most prominent effect in vitro. We provide preliminary evidence that sunitinib induced in vitro cancer spheres and the live tumor areas that survive within necrotic patches of the sunitinib-treated xenografts, are related. Finally, membranous expression of E-cadherin enhances the survival of ccRCC cell lines under sunitinib treatment. Citation Format: Zsuzsanna Lichner, Rola Saleeb, Henriett Butz, Roy Nofech-Mozes, Sara Riad, Mina Farag, Andras Kapus, George Yousef. Histological heterogeneity contributes to sunitinib resistance in clear cell renal cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 811. doi:10.1158/1538-7445.AM2017-811
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".