Acoustic Printing of Patient‐Derived Organoids That Preserve Tumor Microenvironment for Personalized Drug Screening

Author:

Gong Zhiyi1,Mao Yiqian1,Huang Lanxiang23,Tang Xuan23,Zhang Lingling1,Xu Yaqi23,Ding Zhao4,Zhao Xingzhong1ORCID,Wang Fubing235ORCID,Guo Shishang16ORCID

Affiliation:

1. Key Laboratory of Artificial Micro‐ and Nano‐structures of Ministry of Education School of Physics and Technology Wuhan University 430072 Wuhan P. R. China

2. Department of Laboratory Medicine Zhongnan Hospital of Wuhan University 430062 Wuhan P. R. China

3. Center for Single‐Cell Omics and Tumor Liquid Biopsy Zhongnan Hospital of Wuhan University 430062 Wuhan P. R. China

4. Department of Colorectal and Anal Surgery Hubei Key Laboratory of Intestinal and Colorectal Diseases Zhongnan Hospital of Wuhan University 430071 Wuhan P. R. China

5. Wuhan Research Center for Infectious Diseases and Cancer Chinese Academy of Medical Sciences 430062 Wuhan P. R. China

6. Hubei Yangtze Memory Laboratories 430205 Wuhan P. R. China

Abstract

AbstractPatient personalized treatment models can predict treatment response and assist in determining the optimal treatment option for individual patients. The tumor microenvironment mediates tumor development and prognosis. However, current tumor models such as patient‐derived tumor xenograft (PDX) and 2D culture models fail to preserve the patient‐derived tumor microenvironment. Herein, a technique for acoustic‐droplet‐printing‐of‐patient‐derived‐organoids (ADPDOs) is reported, which allows for high‐throughput, high‐viability, rapid, and uniform printing preparation of patient‐derived organoids. In particular, the ADPDOs are uniform in size and retain the parental tumor/fibroblast cell composition, mimicking a more realistic 3D environment of parent tissue in vitro, with histological features and protein expression closer to that of the tissue. Therefore, ADPDOs hold promise for application in personalized precision therapy for different patients. The authors test the clinical drug treatment response of different patients in a fast and convenient way to predict the therapeutic effect of various patients. Thus, this technique has great potential for predicting treatment response to personalized cancer therapy and constructing complex 3D tissue models.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Industrial and Manufacturing Engineering,Mechanics of Materials,General Materials Science

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