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Science. 2018 Feb 23;359(6378):920-926. doi: 10.1126/science.aao2774.

Patient-derived organoids model treatment response of metastatic gastrointestinal cancers.

Author information

1
Division of Molecular Pathology, The Institute of Cancer Research, London, UK.
2
Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
3
Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research and Royal Marsden Hospital, London, UK.
4
Department of Medicine, The Royal Marsden NHS Trust, London, UK.
5
Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London, UK.
6
Department of Radiology, The Royal Marsden NHS Trust, London, UK.
7
Ralph Lauren Centre for Breast Cancer Research, Royal Marsden Hospital NHS Trust, London, UK.
8
Division of Clinical Studies, The Institute of Cancer Research, London, UK.
9
Department of Medicine, Surgical Pathology and Cytopathology Unit, University of Padua, Padua, Italy.
10
Cancer Research UK Beatson Institute, Glasgow, UK.
11
Division of Molecular Pathology, The Institute of Cancer Research, London, UK. nicola.valeri@icr.ac.uk.

Abstract

Patient-derived organoids (PDOs) have recently emerged as robust preclinical models; however, their potential to predict clinical outcomes in patients has remained unclear. We report on a living biobank of PDOs from metastatic, heavily pretreated colorectal and gastroesophageal cancer patients recruited in phase 1/2 clinical trials. Phenotypic and genotypic profiling of PDOs showed a high degree of similarity to the original patient tumors. Molecular profiling of tumor organoids was matched to drug-screening results, suggesting that PDOs could complement existing approaches in defining cancer vulnerabilities and improving treatment responses. We compared responses to anticancer agents ex vivo in organoids and PDO-based orthotopic mouse tumor xenograft models with the responses of the patients in clinical trials. Our data suggest that PDOs can recapitulate patient responses in the clinic and could be implemented in personalized medicine programs.

PMID:
29472484
PMCID:
PMC6112415
DOI:
10.1126/science.aao2774
[Indexed for MEDLINE]
Free PMC Article

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