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Evaluation of Alternative In Vivo Drug Screening Methodology: A Single Mouse Analysis
Brendan Murphy1, Han Yin1, John M Maris2
1Center for Childhood Cancer and Blood Diseases, The Research Institute, Nationwide Children's Hospital, Columbus, Ohio.
Abstract:
Traditional approaches to evaluating antitumor agents using human tumor xenograft models have generally used cohorts of 8 to 10 mice against a limited panel of tumor models. An alternative approach is to use fewer animals per tumor line, allowing a greater number of models that capture greater molecular/genetic heterogeneity of the cancer type. We retrospectively analyzed 67 agents evaluated by the Pediatric Preclinical Testing Program to determine whether a single mouse, chosen randomly from each group of a study, predicted the median response for groups of mice using 83 xenograft models. The individual tumor response from a randomly chosen mouse was compared with the group median response using established response criteria. A total of 2,134 comparisons were made. The single tumor response accurately predicted the group median response in 1,604 comparisons (75.16%). The mean tumor response correct prediction rate for 1,000 single mouse random samples was 78.09%. Models had a range for correct prediction (60%-87.5%). Allowing for misprediction of ± one response category, the overall mean correct single mouse prediction rate was 95.28%, and predicted overall objective response rates for group data in 66 of 67 drug studies. For molecularly targeted agents, occasional exceptional responder models were identified and the activity of that agent confirmed in additional models with the same genotype. Assuming that large treatment effects are targeted, this alternate experimental design has similar predictive value as traditional approaches, allowing for far greater numbers of models to be used that more fully encompass the heterogeneity of disease types. Cancer Res; 76(19); 5798-809. ©2016 AACR.
Insights
Using a single mouse per tumor model can accurately predict antitumor agent efficacy. This approach allows testing more models, capturing greater cancer genetic diversity for improved drug development.
Area of Science:
- Oncology
- Pharmacology
- Translational Research
Background:
- Traditional preclinical testing uses 8-10 mice per human tumor xenograft model.
- This limits the number of tumor models evaluated, potentially missing crucial cancer heterogeneity.
Purpose of the Study:
- To determine if a single mouse per model can predict overall treatment response.
- To assess if a reduced animal model approach enhances the evaluation of antitumor agents.
Main Methods:
- Retrospective analysis of 67 agents and 83 xenograft models from the Pediatric Preclinical Testing Program.
- Compared individual mouse responses to group median responses using established criteria.
- Performed 2,134 individual comparisons and 1,000 random single-mouse sample simulations.
Main Results:
- Single mouse responses predicted group median response in 75.16% of comparisons.
- Mean correct prediction rate was 78.09% across 1,000 simulations.
- With a one-category tolerance, prediction accuracy reached 95.28%, correctly predicting 66 of 67 drug studies.
Conclusions:
- A single-mouse design is a viable alternative for preclinical antitumor agent evaluation.
- This method allows for broader assessment of tumor models, capturing disease heterogeneity.
- It supports identifying targeted agents and confirming activity in genetically similar models.

