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Nat Med. 2015 Nov;21(11):1318-25. doi: 10.1038/nm.3954. Epub 2015 Oct 19.

High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response.

Author information

1
Oncology Disease Area, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA.
2
Oncology Disease Area, Novartis Institutes for Biomedical Research, Basel, Switzerland.
3
Department of Oncology Translational Medicine, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA.
4
China Novartis Institutes for Biomedical Research, Shanghai, China.
5
Oncology Disease Area, Novartis Institutes for Biomedical Research, Emeryville, California, USA.

Abstract

Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

PMID:
26479923
DOI:
10.1038/nm.3954
[Indexed for MEDLINE]

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