Evaluation of Alternative In Vivo Drug Screening Methodology: A Single Mouse Analysis
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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.
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Several large studies have validated the 1 × 1 × 1 mouse clinical trial approach, showing high reproducibility and identification of known predictive biomarkers.
“Several large studies have validated this approach, showing high reproducibility and identification of known predictive biomarkers (31, 32, 38).”
From Preclinical Modeling of Navtemadlin Pharmacokinetics, Pharmacodynamics, and Efficacy in IDH–Wild-type Glioblastoma (2025) · cites this paper as [38]
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Research works printed but not linked: 2
- [48]Kolb EA Gorlick R Houghton PJ Morton CL Neale G Keir ST Initial testing (stage 1) of AZD6244 (ARRY-142886) by the Pediatric Preclinical Testing Program Pediatr Blood Cancer 2010 55 4 668 77 20806365 PMC3004092
- [50]Smith MA Hampton OA Reynolds CP Kang MH Maris JM Gorlick R Initial testing (stage 1) of the PARP inhibitor BMN 673 by the Pediatric Preclinical Testing Program: PALB2 mutation predicts exceptional in vivo response to BMN 673 Pediatr Blood Cancer 2015 62 91 98 25263539 PMC4456187
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- Authors
- Murphy, B., Yin, H., Maris, J. M., Kolb, E. A., Gorlick, R., Reynolds, C. P., Kang, M. H., Keir, S. T., Kurmasheva, R. T., Dvorchik, I., Wu, J., Billups, C. A., Boateng, N., Smith, M. A., Lock, R. B., & Houghton, P. J.
- Affiliations
- Nationwide Children's Hospital (US)
- Children's Hospital of Philadelphia (US)
- Alfred I. duPont Hospital for Children (US)
- Children's Hospital at Montefiore (US)
- Texas Tech University (US)
- Duke Medical Center (US)
- The University of Texas at San Antonio Health Science Center (US)
- St. Jude Children's Research Hospital (US)
- National Cancer Institute (US)
- Children's Cancer Institute Australia (AU)
- Corresponding author
- Houghton, Peter J.
- ORCID
- Venue
- Cancer Research
- Published
- 2016-10-01
- Volume
- 76
- Issue
- 19
- Pages
- 5798-5809
- ISSN
- 0008-5472 (ISSN-L)
- 1538-7445
- PMC
- PMC5050128
- OpenAlex
- W2492058432
- Cited by
- 69
- References
- 48
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 5 · 2023: 2 · 2022: 8 · 2021: 10 · 2020: 7 · 2019: 10 · 2018: 4 · 2017: 8 · 2016: 1
- FWCI
- 11.79
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
- UNSWorks (UNSW Sydney) (submittedVersion, cc-by-nc-nd)
- Funders
- National Cancer Institute (NO1-CM42216 and UO1CA199297)
- Topics
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Veterinary Oncology Research
- Keywords
- tumor xenograft models, anticancer drug screening, predictive value, objective response rate, molecularly targeted agents, childhood cancer, tumor heterogeneity
- MeSH terms
- Animals, Humans, Neoplasms, Retrospective Studies, Xenograft Model Antitumor Assays, Cell Line, Tumor, Mice, Precursor Cell Lymphoblastic Leukemia-Lymphoma
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