Large-scale CRISPR screening in primary human 3D gastric organoids enables comprehensive dissection of gene-drug interactions

Understanding how genes influence drug responses is critical for advancing personalized cancer treatments. However, identifying these gene-drug interactions in a physiologically relevant human system remains a challenge, as it requires a model that reflects the complexity and heterogeneity among individuals. Here we show that large-scale CRISPR-based genetic screens, including knockout, interference (CRISPRi), activation (CRISPRa), and single-cell approaches, can be applied in primary human 3D gastric organoids to systematically identify genes that affect sensitivity to cisplatin. Our screens uncover genes that modulate cisplatin response. By combining CRISPR perturbations with single-cell transcriptomics, we resolve how genetic alterations interact with cisplatin at the level of individual cells and uncover an unexpected link between fucosylation and cisplatin sensitivity. We identify TAF6L as a regulator of cell recovery from cisplatin-induced cytotoxicity. These results highlight the utility of human organoid models for dissecting gene-drug interactions and offer insights into therapeutic vulnerabilities in gastric cancer.

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Publication Details

Journal
Nature Communications
Published
2025-08-14
DOI
https://doi.org/10.1038/s41467-025-62818-3
Citations
7
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
5.64

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article

Large-scale CRISPR screening in primary human 3D gastric organoids enables comprehensive dissection of gene-drug interactions

Lei S. Qi, Hudson T. Horn, Mo-Fan Huang, Martina Towers et al.
7 citations
Nature Communications
CRISPR and Genetic Engineering
5.64
article

Large-scale CRISPR screening in primary human 3D gastric organoids enables comprehensive dissection of gene-drug interactions

Lei S. Qi, Hudson T. Horn, Mo-Fan Huang, Martina Towers, Michael C. Bassik, Jonathan S. Weissman, Antonia A. Dominguez, Calvin J. Kuo, Madeline Tomaske, Dung‐Fang Lee, Wei-Chieh Yu, Qing Liu, Jin Chen, Yuan‐Hung Lo, C.S. Young
article en
7 citations

Abstract

Understanding how genes influence drug responses is critical for advancing personalized cancer treatments. However, identifying these gene-drug interactions in a physiologically relevant human system remains a challenge, as it requires a model that reflects the complexity and heterogeneity among individuals. Here we show that large-scale CRISPR-based genetic screens, including knockout, interference (CRISPRi), activation (CRISPRa), and single-cell approaches, can be applied in primary human 3D gastric organoids to systematically identify genes that affect sensitivity to cisplatin. Our screens uncover genes that modulate cisplatin response. By combining CRISPR perturbations with single-cell transcriptomics, we resolve how genetic alterations interact with cisplatin at the level of individual cells and uncover an unexpected link between fucosylation and cisplatin sensitivity. We identify TAF6L as a regulator of cell recovery from cisplatin-induced cytotoxicity. These results highlight the utility of human organoid models for dissecting gene-drug interactions and offer insights into therapeutic vulnerabilities in gastric cancer.

Nature CommunicationsVol. 16(1)
The University of Texas MD Anderson Cancer Center (US), Howard Hughes Medical Institute (US), University of California, San Francisco (US), Bay Institute (US), Sana Biotechnology (United States) (US), Stanford Health Care (US), Stanford Medicine (US), Whitehead Institute for Biomedical Research (US), Massachusetts Institute of Technology (US), The University of Texas Southwestern Medical Center (US), The University of Texas Health Science Center at Houston (US), Stanford University (US)
Cancer Prevention and Research Institute of Texas, Ludwig Institute for Cancer Research, Emerson Collective, National Institutes of Health, University of Texas MD Anderson Cancer Center, Stand Up To Cancer, National Cancer Institute
Openalex Percentile: Top 4%
CRISPR and Genetic Engineering
5.64
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