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  5. A living biobank of matched pairs of patient-derived xenografts and organoids for cancer pharmacology

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Article
en
2023

A living biobank of matched pairs of patient-derived xenografts and organoids for cancer pharmacology

0 Datasets

0 Files

en
2023
Vol 18 (1)
Vol. 18
DOI: 10.1371/journal.pone.0279821

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Hans Clevers
Hans Clevers

Utrecht University

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Zheng‐Zheng Bao
Sheng Guo
Xuesong Ouyang
+21 more

Abstract

Patient-derived tumor xenograft (PDX)/organoid (PDO), driven by cancer stem cells (CSC), are considered the most predictive models for translational oncology. Large PDX collections reflective of patient populations have been created and used extensively to test various investigational therapies, including population-trials as surrogate subjects in vivo . PDOs are recognized as in vitro surrogates for patients amenable for high-throughput screening (HTS). We have built a biobank of carcinoma PDX-derived organoids (PDXOs) by converting an existing PDX library and confirmed high degree of similarities between PDXOs and parental PDXs in genomics, histopathology and pharmacology, suggesting “biological equivalence or interchangeability” between the two. Here we demonstrate the applications of PDXO biobank for HTS “matrix” screening for both lead compounds and indications, immune cell co-cultures for immune-therapies and engineering enables in vitro/in vivo imaging. This large biobank of >550 matched pairs of PDXs/PDXOs across different cancers could become powerful tools for the future cancer drug discovery.

How to cite this publication

Zheng‐Zheng Bao, Sheng Guo, Xuesong Ouyang, Limei Shang, Fei Wang, Xuefei Yan, Rui Zhang, Robert G. Vries, Hans Clevers, Qi‐Xiang Li, Xiaoxi Xu, Rajendra Kumari, Jun Zhou, Jing Chen, Binchen Mao, Jingjing Wang, Meiling Zheng, Xiaolong Tu, Xiaoyu An, Xiaobo Chen, Likun Zhang, Xiaoli Tian, Haojie Wang, Xin Dong (2023). A living biobank of matched pairs of patient-derived xenografts and organoids for cancer pharmacology. , 18(1), DOI: https://doi.org/10.1371/journal.pone.0279821.

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Publication Details

Type

Article

Year

2023

Authors

24

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1371/journal.pone.0279821

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