Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology

Shuyi Ji; Li Feng; Zile Fu; Gaohua Wu; Yingcheng Wu; Youpei Lin; Dayun Lu; Yuanli Song; Peng Cui; Zijian Yang; Chen Sang; Guohe Song; Shangli Cai; Yuanchuang Li; Hanqing Lin; Shu Zhang; Xiaoying Wang; Shuangjian Qiu; Xiaoming Zhang; Guoqiang Hua; Junqiang Li; Jian Zhou; Zhi Dai; Xiangdong Wang; Li Ding; Pei Wang; Daming Gao; Bing Zhang; Henry Rodriguez; Jia Fan; Hans Clevers; Hu Zhou; Yidi Sun; Qiang Gao

doi:10.1126/scitranslmed.adg3358

Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology

Shuyi Ji, Li Feng, Zile Fu, Gaohua Wu, Yingcheng Wu, Youpei Lin, Dayun Lu, Yuanli Song, Peng Cui, Zijian Yang, Chen Sang, Guohe Song, Shangli Cai, Yuanchuang Li, Hanqing Lin, Shu Zhang, Xiaoying Wang, Shuangjian Qiu, Xiaoming Zhang, Guoqiang HuaJunqiang Li, Jian Zhou, Zhi Dai, Xiangdong Wang, Li Ding, Pei Wang, Daming Gao, Bing Zhang, Henry Rodriguez, Jia Fan, Hans Clevers, Hu Zhou, Yidi Sun, Qiang Gao

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

Abstract

Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.

Original language	English
Article number	eadg3358
Journal	Science translational medicine
Volume	15
Issue number	706
DOIs	https://doi.org/10.1126/scitranslmed.adg3358
State	Published - Jul 26 2023

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Ji, S., Feng, L., Fu, Z., Wu, G., Wu, Y., Lin, Y., Lu, D., Song, Y., Cui, P., Yang, Z., Sang, C., Song, G., Cai, S., Li, Y., Lin, H., Zhang, S., Wang, X., Qiu, S., Zhang, X., ... Gao, Q. (2023). Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology. Science translational medicine, 15(706), Article eadg3358. https://doi.org/10.1126/scitranslmed.adg3358

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title = "Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology",

abstract = "Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.",

author = "Shuyi Ji and Li Feng and Zile Fu and Gaohua Wu and Yingcheng Wu and Youpei Lin and Dayun Lu and Yuanli Song and Peng Cui and Zijian Yang and Chen Sang and Guohe Song and Shangli Cai and Yuanchuang Li and Hanqing Lin and Shu Zhang and Xiaoying Wang and Shuangjian Qiu and Xiaoming Zhang and Guoqiang Hua and Junqiang Li and Jian Zhou and Zhi Dai and Xiangdong Wang and Li Ding and Pei Wang and Daming Gao and Bing Zhang and Henry Rodriguez and Jia Fan and Hans Clevers and Hu Zhou and Yidi Sun and Qiang Gao",

note = "Publisher Copyright: Copyright {\textcopyright} 2023 The Authors, some rights reserved;",

year = "2023",

month = jul,

day = "26",

doi = "10.1126/scitranslmed.adg3358",

language = "English",

volume = "15",

journal = "Science translational medicine",

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Ji, S, Feng, L, Fu, Z, Wu, G, Wu, Y, Lin, Y, Lu, D, Song, Y, Cui, P, Yang, Z, Sang, C, Song, G, Cai, S, Li, Y, Lin, H, Zhang, S, Wang, X, Qiu, S, Zhang, X, Hua, G, Li, J, Zhou, J, Dai, Z, Wang, X, Ding, L, Wang, P, Gao, D, Zhang, B, Rodriguez, H, Fan, J, Clevers, H, Zhou, H, Sun, Y & Gao, Q 2023, 'Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology', Science translational medicine, vol. 15, no. 706, eadg3358. https://doi.org/10.1126/scitranslmed.adg3358

TY - JOUR

T1 - Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology

AU - Ji, Shuyi

AU - Feng, Li

AU - Fu, Zile

AU - Wu, Gaohua

AU - Wu, Yingcheng

AU - Lin, Youpei

AU - Lu, Dayun

AU - Song, Yuanli

AU - Cui, Peng

AU - Yang, Zijian

AU - Sang, Chen

AU - Song, Guohe

AU - Cai, Shangli

AU - Li, Yuanchuang

AU - Lin, Hanqing

AU - Zhang, Shu

AU - Wang, Xiaoying

AU - Qiu, Shuangjian

AU - Zhang, Xiaoming

AU - Hua, Guoqiang

AU - Li, Junqiang

AU - Zhou, Jian

AU - Dai, Zhi

AU - Wang, Xiangdong

AU - Ding, Li

AU - Wang, Pei

AU - Gao, Daming

AU - Zhang, Bing

AU - Rodriguez, Henry

AU - Fan, Jia

AU - Clevers, Hans

AU - Zhou, Hu

AU - Sun, Yidi

AU - Gao, Qiang

PY - 2023/7/26

Y1 - 2023/7/26

N2 - Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.

AB - Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.

UR - http://www.scopus.com/inward/record.url?scp=85165880395&partnerID=8YFLogxK

U2 - 10.1126/scitranslmed.adg3358

DO - 10.1126/scitranslmed.adg3358

M3 - Article

C2 - 37494474

AN - SCOPUS:85165880395

SN - 1946-6234

VL - 15

JO - Science translational medicine

JF - Science translational medicine

IS - 706

M1 - eadg3358

ER -

Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology

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