Patient derived renal cell carcinoma xenografts exhibit distinct sensitivity patterns in response to antiangiogenic therapy and constitute a suitable tool for biomarker development
Bibliographic record
Abstract
// Julia Schueler 1 , Kerstin Klingner 1 , Daniel Bug 3 , Caren Zoeller 7 , Armin Maier 1 , Meng Dong 8 , Kerstin Willecke 8 , Anne-Lise Peille 1 , Eva Steiner 4 , Manuel Landesfeind 1 , John A. Copland 2 , Gabrielle M. Siegers 6 , Axel Haferkamp 5 , Katharina Boehm 5 , Igor Tsaur 5 and Meike Schneider 5 1 Charles River Discovery Research Services Germany GmbH, Freiburg, Germany 2 Department of Cancer Biology, Mayo Clinic, Jacksonville, FL, USA 3 LfB – Lehrstuhl für Bildverarbeitung, RWTH Aachen University, Aachen, Germany 4 Department of Urology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany 5 Department of Urology, Medical Center Johannes Gutenberg University, Mainz, Germany 6 Department of Experimental Oncology, University of Alberta, 5-142W Katz Group Centre, Edmonton, Canada 7 Department of Radiation Oncology, University Hospital of Würzburg, Würzburg, Germany 8 Dr. Margarete Fischer-Bosch - Institut für Klinische Pharmakologie, Stuttgart, Germany Correspondence to: Meike Schneider, email: meikeschneider310@gmail.com Keywords: HMGB1; renal cell carcinoma; damage associated molecular pattern; bevacizumab; VEGF Received: November 11, 2017 Accepted: June 12, 2018 Published: July 24, 2018 ABSTRACT Systemic treatment is necessary for one third of patients with renal cell carcinoma. No valid biomarker is currently available to tailor personalized therapy. In this study we established a representative panel of patient derived xenograft (PDX) mouse models from patients with renal cell carcinomas and determined serum levels of high mobility group B1 (HMGB1) protein under treatment with sunitinib, pazopanib, sorafenib, axitinib, temsirolimus and bevacizumab. Serum HMGB1 levels were significantly higher in a subset of the PDX collection, which exhibited slower tumor growth during subsequent passages than tumors with low HMGB1 serum levels. Pre-treatment PDX serum HMGB1 levels also correlated with response to systemic treatment: PDX models with high HMGB1 levels predicted response to bevacizumab. Taken together, we provide for the first time evidence that the damage associated molecular pattern biomarker HMGB1 can predict response to systemic treatment with bevacizumab. Our data support the future evaluation of HMGB1 as a predictive biomarker for bevacizumab sensitivity in patients with renal cell carcinoma.
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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".