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Phenotype-driven precision oncology as a guide for clinical decisions one patient at a time

机译:表型驱动的精密肿瘤学可一次指导一名患者的临床决策

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Genomics-driven cancer therapeutics has gained prominence in personalized cancer treatment. However, its utility in indications lacking biomarker-driven treatment strategies remains limited. Here we present a “phenotype-driven precision-oncology” approach, based on the notion that biological response to perturbations, chemical or genetic, in ex vivo patient-individualized models can serve as predictive biomarkers for therapeutic response in the clinic. We generated a library of “screenable” patient-derived primary cultures (PDCs) for head and neck squamous cell carcinomas that reproducibly predicted treatment response in matched patient-derived-xenograft models. Importantly, PDCs could guide clinical practice and predict tumour progression in two n?=?1 co-clinical trials. Comprehensive “-omics” interrogation of PDCs derived from one of these models revealed YAP1 as a putative biomarker for treatment response and survival in ~24% of oral squamous cell carcinoma. We envision that scaling of the proposed PDC approach could uncover biomarkers for therapeutic stratification and guide real-time therapeutic decisions in the future.
机译:基因组学驱动的癌症治疗方法在个性化癌症治疗中日益突出。然而,其在缺乏由生物标记物驱动的治疗策略的适应症中的效用仍然有限。在这里,我们提出一种“表型驱动的精确肿瘤学”方法,其基于以下概念:在离体患者个体化模型中对扰动(化学或遗传)的生物学反应可以作为临床治疗反应的预测性生物标志物。我们为头颈部鳞状细胞癌生成了一个“可筛选的”患者来源的原代培养物(PDC)库,该库可再现地预测在匹配的患者来源的异种移植模型中的治疗反应。重要的是,PDC可以指导临床实践并通过两项n?=?1共同临床试验来预测肿瘤的进展。从这些模型之一得出的对PDC的全面“组学”询问显示,YAP1是在约24%的口腔鳞状细胞癌中治疗应答和存活率的公认生物标志物。我们设想,提议的PDC方法的扩展规模可能会发现用于治疗分层的生物标志物,并在将来指导实时治疗决策。

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