期刊
SCIENCE
卷 359, 期 6378, 页码 920-+出版社
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.aao2774
关键词
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资金
- Cancer Research UK [CEA A18052, C52506/A22909, C309/A11566, C2739/A22897]
- National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at The Royal Marsden NHS Foundation Trust
- Institute of Cancer Research [A62, A100, A101, A159]
- European Union [CIG 334261]
- Wellcome Trust [105104/Z/14/Z]
- Cancer Research UK Cancer Imaging Centre [C1060/A16464]
- Bayer Oncology Group Research Grant
- Chris Rokos Fellowship in Evolution and Cancer
- Merck-Serono
- Novartis
- Roche
- Sanofi Oncology
- Amgen
- Celgene
- Sanofi
- Merck Serono
- AstraZeneca
- Bayer
- Merrimack
- MedImmune
- Cancer Research UK [16464, 22909, 18052, 11566, 22897] Funding Source: researchfish
- Cancer Research UK
- Versus Arthritis [21139] Funding Source: researchfish
- National Institute for Health Research [NF-SI-0512-10122] Funding Source: researchfish
- Pancreatic Cancer Action [PCA-EDCA16-002] Funding Source: researchfish
- Pancreatic Cancer UK [RIF2014_01_Braconi] Funding Source: researchfish
- Wellcome Trust [105104/Z/14/Z] Funding Source: researchfish
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.
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