Identification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma

Predicting the drug response of patients with cancer is crucial for implementing targeted therapy. Here, Su et al. make patient-derived cell lines and perform targeted sequencing and RNA-seq to identify CDKN2A/2B loss as a predictor of response to CDK4/6 inhibitors in esophageal squamous cell carcin...

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Autores principales:	Dan Su, Dadong Zhang, Jiaoyue Jin, Lisha Ying, Miao Han, Kaiyan Chen, Bin Li, Junzhou Wu, Zhenghua Xie, Fanrong Zhang, Yihui Lin, Guoping Cheng, Jing-Yu Li, Minran Huang, Jinchao Wang, Kailai Wang, Jianjun Zhang, Fugen Li, Lei Xiong, Andrew Futreal, Weimin Mao
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/03e2472bfffe4d77bb873151b95d70ea
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spelling	oai:doaj.org-article:03e2472bfffe4d77bb873151b95d70ea2021-12-02T17:01:58ZIdentification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma10.1038/s41467-019-12846-72041-1723https://doaj.org/article/03e2472bfffe4d77bb873151b95d70ea2019-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-12846-7https://doaj.org/toc/2041-1723Predicting the drug response of patients with cancer is crucial for implementing targeted therapy. Here, Su et al. make patient-derived cell lines and perform targeted sequencing and RNA-seq to identify CDKN2A/2B loss as a predictor of response to CDK4/6 inhibitors in esophageal squamous cell carcinoma.Dan SuDadong ZhangJiaoyue JinLisha YingMiao HanKaiyan ChenBin LiJunzhou WuZhenghua XieFanrong ZhangYihui LinGuoping ChengJing-Yu LiMinran HuangJinchao WangKailai WangJianjun ZhangFugen LiLei XiongAndrew FutrealWeimin MaoNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-13 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Dan Su Dadong Zhang Jiaoyue Jin Lisha Ying Miao Han Kaiyan Chen Bin Li Junzhou Wu Zhenghua Xie Fanrong Zhang Yihui Lin Guoping Cheng Jing-Yu Li Minran Huang Jinchao Wang Kailai Wang Jianjun Zhang Fugen Li Lei Xiong Andrew Futreal Weimin Mao Identification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma
description	Predicting the drug response of patients with cancer is crucial for implementing targeted therapy. Here, Su et al. make patient-derived cell lines and perform targeted sequencing and RNA-seq to identify CDKN2A/2B loss as a predictor of response to CDK4/6 inhibitors in esophageal squamous cell carcinoma.
format	article
author	Dan Su Dadong Zhang Jiaoyue Jin Lisha Ying Miao Han Kaiyan Chen Bin Li Junzhou Wu Zhenghua Xie Fanrong Zhang Yihui Lin Guoping Cheng Jing-Yu Li Minran Huang Jinchao Wang Kailai Wang Jianjun Zhang Fugen Li Lei Xiong Andrew Futreal Weimin Mao
author_facet	Dan Su Dadong Zhang Jiaoyue Jin Lisha Ying Miao Han Kaiyan Chen Bin Li Junzhou Wu Zhenghua Xie Fanrong Zhang Yihui Lin Guoping Cheng Jing-Yu Li Minran Huang Jinchao Wang Kailai Wang Jianjun Zhang Fugen Li Lei Xiong Andrew Futreal Weimin Mao
author_sort	Dan Su
title	Identification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma
title_short	Identification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma
title_full	Identification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma
title_fullStr	Identification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma
title_full_unstemmed	Identification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma
title_sort	identification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/03e2472bfffe4d77bb873151b95d70ea
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Identification of predictors of drug sensitivity using patient-derived models of esophageal squamous cell carcinoma

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