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

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Preprint
en
2020

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

0 Datasets

0 Files

en
2020
DOI: 10.21203/rs.3.rs-63366/v1

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Hans Clevers
Hans Clevers

Utrecht University

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Xiaoxi Xu
Shuzhong Wang
Jun Zhou
+26 more

Abstract

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 in 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 matched pairs of PDXs/PDXOs across different cancers could become powerful tools for the future cancer drug discovery.

How to cite this publication

Xiaoxi Xu, Shuzhong Wang, Jun Zhou, Jing Chen, Yujun Huang, Rajendra Kumari, Binchen Mao, Meiling Zheng, jingjing wang, Xiaolong Tu, Xiaoyu An, xiaobo chen, Likun Zhang, Xiaoli Tian, haojie Wang, Xin Dong, Zheng‐Zheng Bao, Sheng Guo, Xuesong Ouyang, Limei Shan, Fei Wang, Xuefei Yan, zhongliang li, Rui Zhang, hongjuan zhang, svenjer meiler, Robert Vries, Hans Clevers, Qi‐Xiang Li (2020). A living biobank of matched pairs of patient-derived xenografts and organoids for cancer pharmacology. , DOI: https://doi.org/10.21203/rs.3.rs-63366/v1.

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Publication Details

Type

Preprint

Year

2020

Authors

29

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.21203/rs.3.rs-63366/v1

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