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Genomic characteristics and drug screening among organoids derived from non-small cell lung cancer patients.

Authors :
Chen JH
Chu XP
Zhang JT
Nie Q
Tang WF
Su J
Yan HH
Zheng HP
Chen ZX
Chen X
Song MM
Yi X
Li PS
Guan YF
Li G
Deng CX
Rosell R
Wu YL
Zhong WZ
Source :
Thoracic cancer [Thorac Cancer] 2020 Aug; Vol. 11 (8), pp. 2279-2290. Date of Electronic Publication: 2020 Jul 07.
Publication Year :
2020

Abstract

Background: Patient-derived organoid (PDO) models are highly valuable and have potentially widespread clinical applications. However, limited information is available regarding organoid models of non-small cell lung cancer (NSCLC). This study aimed to characterize the consistency between primary tumors in NSCLC and PDOs and to explore the applications of PDOs as preclinical models to understand and predict treatment response during lung cancer.<br />Methods: Fresh tumor samples were harvested for organoid culture. Primary tumor samples and PDOs were analyzed via whole-exome sequencing. Paired samples were subjected to immunohistochemical analysis. There were 26 antineoplastic drugs tested in the PDOs. Cell viability was assessed using the Cell Titer Glo assay 7-10 days after drug treatment. A heatmap of log-transformed values of the half-maximal inhibitory concentrations was generated on the basis of drug responses of PDOs through nonlinear regression (curve fit). A total of 12 patients (stages I-III) were enrolled, and 7 paired surgical tumors and PDOs were analyzed.<br />Results: PDOs retained the histological and genetic characteristics of the primary tumors. The concordance between tumors and PDOs in mutations in the top 20 NSCLC-related genes was >80% in five patients. Sample purity was significantly and positively associated with variant allele frequency (Pearson r = 0.82, P = 0.0005) and chromosome stability. The in vitro response to drug screening with PDOs revealed high correlation with the mutation profiles in the primary tumors.<br />Conclusions: PDOs are highly credible models for detecting NSCLC and for prospective prediction of the treatment response for personalized precision medicine.<br />Key Points: Lung cancer organoid models could save precious time of drug testing on patients, and accurately select anticancer drugs according to the drug sensitivity results, so as to provide a powerful supplement and verification for the gene sequencing.<br /> (© 2020 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.)

Details

Language :
English
ISSN :
1759-7714
Volume :
11
Issue :
8
Database :
MEDLINE
Journal :
Thoracic cancer
Publication Type :
Academic Journal
Accession number :
32633046
Full Text :
https://doi.org/10.1111/1759-7714.13542