药物反应
卡铂
卵巢癌
个性化医疗
精密医学
药品
药物基因组学
紫杉醇
遗传异质性
功效
癌症
生物
医学
化疗
肿瘤科
生物信息学
表型
内科学
药理学
病理
基因
遗传学
顺铂
作者
Chris J. de Witte,Jose Espejo Valle-Inclán,Nizar Hami,Kadi Lõhmussaar,Oded Kopper,Celien P.H. Vreuls,Geertruida N. Jonges,P. J. van Diest,Luan Nguyen,Hans C. Clevers,Wigard P. Kloosterman,Edwin P. J. G. Cuppen,Hugo J.G. Snippert,Ronald Peter Zweemer,Petronella Oda Witteveen,Ellen Stelloo
出处
期刊:Cell Reports
[Cell Press]
日期:2020-06-01
卷期号:31 (11): 107762-107762
被引量:303
标识
DOI:10.1016/j.celrep.2020.107762
摘要
Abstract Purpose There remains an unmet need for preclinical models to enable personalized therapy for ovarian cancer (OC) patients. Recently, patient-derived organoid (PDO) cultures of patients with OC have been established that faithfully represent the histopathological features and genomic landscape of the patient tumor. In this study, we evaluate the capacity of OC PDOs to predict clinical drug response and functional consequences of tumor heterogeneity. Experimental design 36 genomically characterized PDOs from 23 patients with known clinical histories were exposed to chemotherapeutics and targeted drugs. Results OC PDOs maintained genomic features of the original tumor lesion and recapitulated patient response to neoadjuvant carboplatin and paclitaxel combination treatment, according to distinct clinical outcomes (histopathological, biochemical and radiological). PDOs displayed inter-as well as intrapatient drug response heterogeneity, which could in part be explained by genetic aberrations. All PDOs were resistant to PARP-inhibitors, in accordance with homologous recombination pathway fidelity and genome-wide mutation context. KRAS, BRAF and NRAS mutation status predicted response to BRAF-inhibitor vemurafenib and pan-HER-inhibitor afatinib, and explained differential response among four PDOs derived from distinct tumor locations of an individual patient. Importantly, PDO drug screening identified sensitivity to at least one drug for the majority of patients (88%). Conclusions OC PDOs are a valuable preclinical model system that can provide insights in drug response for individual patients with OC, complementary to genetic testing. Generating PDOs of multiple tumor locations can improve clinical decision making and increase our knowledge on genetic and drug response heterogeneity.
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