Detecting functional changes with [18F]FAZA in a renal cell carcinoma mouse model following sunitinib therapy
Bibliographic record
Abstract
BACKGROUND: The multitargeting tyrosine kinase inhibitor (TKI) sunitinib is currently the first-line drug therapy for metastasizing renal cell carcinoma (RCC). TKIs have profound effects on tumor angiogenesis, leading to modifications of the tumor microenvironment. The goal of this study was to determine whether these treatment-induced changes can be detected with [(18)F]FAZA. METHODS: The present study utilized positron emission tomography (PET) to analyze tumor oxygenation status during and after sunitinib therapy in the murine Caki-1 RCC tumor model. Dynamic and static scans were performed, as well as ex vivo biodistributions at 3 h post injection (p.i.). Immunohistochemical analysis of tumor tissue was carried out for the quantification of pimonidazole binding and the hypoxia-associated factors CD-31, Ki-67, and Von Willebrand factor (VWF). In addition, in vitro cellular uptake studies were done to analyze the direct effects of sunitinib on the Caki-1 cells. RESULTS: During therapy with sunitinib (40 mg/kg/day), uptake of [(18)F]FAZA into Caki-1 mice decreased by 46 ± 5% (n = 4; 5 days) at 3 h post injection (p.i.) during the first study and 22 ± 5% (n = 8; 9 days) during the long-term study, indicating a decrease in the tumor's hypoxia level. However, when drug therapy was stopped, this effect was reversed completely, and the tumor [(18)F]FAZA uptake increased to 126 ± 6% (n = 6) of the control tumor uptake, indicative of an even higher level of tumor hypoxia compared to the therapy starting point. Sunitinib had no direct effect on [(18)F]FAZA uptake into Caki-1 cells in vitro. CONCLUSION: [(18)F]FAZA PET could be used to monitor drug response during sunitinib therapy in RCC and may guide combination therapies based on the tumor's hypoxia status.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".