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是否采用 DNA 技术进行分子分型?这是一个问题,特别是在临床应用中!

To DNA or not to DNA? That is the question, when it comes to molecular subtyping for the clinic!

机构信息

Departments of Pathology and Epidemiology and Biostatistics, Section Tumor Biology, Department of Otolaryngology/Head-Neck Surgery, Cancer Center Amsterdam, The Netherlands.

出版信息

Clin Cancer Res. 2011 Aug 1;17(15):4959-64. doi: 10.1158/1078-0432.CCR-11-0462. Epub 2011 Jun 14.

Abstract

Genome-wide RNA expression profiling has yielded tumor subtypes with strong predictive or prognostic value for a wide variety of cancers. Recently, for breast cancer two RNA expression classifiers have been adopted by the World Health Organization (WHO) and approved by the Food and Drug Administration (FDA). Also on the basis of DNA copy number profiles, tumor subtypes with different prognosis have been described, but have not yet led to clinical implementation. The genomic revolution caused by next generation sequencing of DNA samples presents additional mutation, balanced translocations, single-nucleotide polymorphisms (SNP), and copy neutral loss of heterozygosity data simultaneously. We foresee a further boost of the potential of DNA profiling in the clinic when these multidimensional DNA factors will be implemented. Here we evaluate the current stratification power with DNA copy numbers. In a training and validation approach using data of 400 published breast cancer samples, we show that a DNA copy number classifier accurately classifies RNA expression subtypes. We consider this an important step forward for clinical implementation of genomic subtyping using DNA and discuss the extra dimensions upcoming techniques will bring to the DNA palette.

摘要

全基因组 RNA 表达谱分析已经产生了具有广泛预测或预后价值的肿瘤亚型,适用于多种癌症。最近,世界卫生组织(WHO)采用了两种 RNA 表达分类器,并获得了食品和药物管理局(FDA)的批准。此外,基于 DNA 拷贝数谱,还描述了具有不同预后的肿瘤亚型,但尚未应用于临床。新一代 DNA 样本测序所引发的基因组革命同时提供了额外的突变、平衡易位、单核苷酸多态性(SNP)和拷贝中性杂合性丢失数据。当这些多维 DNA 因素得以实施时,我们预计 DNA 分析在临床应用中的潜力将会进一步提升。在这里,我们评估了当前基于 DNA 拷贝数的分层能力。在使用 400 个已发表的乳腺癌样本数据进行的训练和验证方法中,我们证明了 DNA 拷贝数分类器可以准确地对 RNA 表达亚型进行分类。我们认为这是使用 DNA 进行基因组亚型临床应用的重要一步,并讨论了即将出现的技术将为 DNA 图谱带来的额外维度。

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