Patient Derived Xenograft Models: An Emerging Platform for Translational Cancer Research
By M. Hidalgo, F. Amant, A. Biankin, E. Budinská, A. Byrne, Carlos Caldas, R. Clarke, S. de Jong, J. Jonkers, G. Mælandsmo and 4 more. Cancer Discovery, 2014
1,525 citations recorded by the source corpus.
Recently, there has been increasing interest in the development and characterization of patient derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal histological and genetic characteristics of their donor tumor and remain stable across passages. These models have been shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, biological studies, and personalized medicine strategies. This paper summarizes the current state of the art in this field including methodological issues, available collections, practical applications, challenges and shortcoming, and future directions, and introduces a European consortium of PDX models.
Subfields: Biotechnology, Cancer Research, Oncology
View Paper: https://www.semanticscholar.org/paper/d94c2fef6ea1af61521719f83fc1607fb17b5992
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In Cancer Research
In Oncology
Citations in the corpus
- Cancer Evolution: Mathematical Models and Computational Inference (2014, background): “Xenografts, although more closely related to a real tumor, are affected by different immune response and microenvironment in the host, but they can model tumor progression in a living organism over time with little sampling restrictions (Hidalgo et al. 2014).”