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

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Authors

Vlachogiannis, G
Hedayat, S
Vatsiou, A
Jamin, Y
Fernández-Mateos, J
Khan, K
Lampis, A
Eason, K
Huntingford, I
Burke, R
Rata, M
Koh, D-M
Tunariu, N
Collins, D
Hulkki-Wilson, S
Ragulan, C
Spiteri, I
Moorcraft, SY
Chau, I
Rao, S
Watkins, D
Fotiadis, N
Bali, M
Darvish-Damavandi, M
Lote, H
Eltahir, Z
Smyth, EC
Begum, R
Clarke, PA
Hahne, JC
Dowsett, M
de Bono, J
Workman, P
Sadanandam, A
Fassan, M
Sansom, OJ
Eccles, S
Starling, N
Braconi, C
Sottoriva, A
Robinson, SP
Cunningham, D
Valeri, N

Document Type

Journal Article

Date

2018-02-23

Date Accepted

2018-01-11

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.

Citation

Science (New York, N.Y.), 2018, 359 (6378), pp. 920 - 926

Source Title

Publisher

AMER ASSOC ADVANCEMENT SCIENCE

ISSN

0036-8075

eISSN

1095-9203

Research Team

Signal Transduction & Molecular Pharmacology
Gastrointestinal Cancers Clinical Trials
Medicine (RMH Smith Cunningham)
Prostate Cancer Targeted Therapy Group
Endocrinology
Evolutionary Genomics & Modelling
Functional Genomics
Gastrointestinal Cancer Biology and Genomics
Systems and Precision Cancer Medicine
Pre-Clinical MRI
Hit Discovery & Structural Design

Notes