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Assessing therapy response in patient-derived xenografts
Janosch Ortmann1,2, Ladislav Rampášek3,4,5, Elijah Tai3
1Département AOTI, Université du Québec à Montréal, Montréal, QC H2X3X2, Canada.
Science Translational Medicine
|November 17, 2021
Summary
A new method, KuLGaP, accurately quantifies drug treatment response in mouse cancer models by analyzing tumor size and variation. This approach improves the translation of preclinical findings to clinical practice, reducing false positives.
Area of Science:
- Oncology
- Pharmacology
- Biostatistics
Background:
- Accurate quantification of drug treatment response in preclinical cancer models is crucial for developing effective therapies.
- Current methods often fail to fully utilize experimental data, leading to challenges in translating findings to clinical practice.
Purpose of the Study:
- To introduce and validate KuLGaP, a novel, theoretically grounded measure for quantifying drug treatment response in mouse cancer models.
- To compare KuLGaP against existing response measures using patient-derived xenograft (PDX) models.
Main Methods:
- Development of the KuLGaP measure, designed to integrate tumor size over time and replicate variation.
- Comparative analysis of KuLGaP against four established response measures using data from 329 patient-derived xenograft (PDX) models.
Main Results:
- KuLGaP demonstrated higher selectivity compared to existing measures.
- The KuLGaP measure effectively reduces the risk of false-positive outcomes in preclinical studies.
- Results obtained using KuLGaP showed better alignment with human treatment outcomes.
Conclusions:
- KuLGaP offers a more robust and reliable method for quantifying drug efficacy in preclinical cancer research.
- The improved translation of laboratory findings to clinical practice is a key advantage of KuLGaP.
- KuLGaP is proposed as a potential standard measure for drug treatment quantification in mouse models, accessible via kulgap.ca.
