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在临床试验中实施个体化癌症基因组学。

Implementing personalized cancer genomics in clinical trials.

机构信息

Biometric Research Branch, US National Cancer Institute, Bethesda, Maryland 20892-7434, USA.

出版信息

Nat Rev Drug Discov. 2013 May;12(5):358-69. doi: 10.1038/nrd3979.

DOI:10.1038/nrd3979
PMID:23629504
Abstract

The recent surge in high-throughput sequencing of cancer genomes has supported an expanding molecular classification of cancer. These studies have identified putative predictive biomarkers signifying aberrant oncogene pathway activation and may provide a rationale for matching patients with molecularly targeted therapies in clinical trials. Here, we discuss some of the challenges of adapting these data for rare cancers or molecular subsets of certain cancers, which will require aligning the availability of investigational agents, rapid turnaround of clinical grade sequencing, molecular eligibility and reconsidering clinical trial design and end points.

摘要

最近,癌症基因组高通量测序的兴起支持了癌症分子分类的扩展。这些研究已经确定了潜在的预测性生物标志物,表明异常的癌基因途径激活,并可能为在临床试验中为患者匹配分子靶向治疗提供依据。在这里,我们讨论了为罕见癌症或某些癌症的分子亚群改编这些数据所面临的一些挑战,这将需要调整研究性药物的可及性、临床级测序的快速周转、分子合格性,并重新考虑临床试验设计和终点。

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Implementing personalized cancer genomics in clinical trials.在临床试验中实施个体化癌症基因组学。
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Leveraging State-of-the-Art AI Algorithms in Personalized Oncology: From Transcriptomics to Treatment.在个性化肿瘤学中利用最先进的人工智能算法:从转录组学到治疗
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Basket Trials: Past, Present, and Future.篮子试验:过去、现在与未来。
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