Wang Ena
Department of Transfusion Medicine, Clinical Center, National Institutes of Health, Bethesda, MD 20892, USA.
J Transl Med. 2005 Jul 25;3:28. doi: 10.1186/1479-5876-3-28.
The study of clinical samples is often limited by the amount of material available to study. While proteins cannot be multiplied in their natural form, DNA and RNA can be amplified from small specimens and used for high-throughput analyses. Therefore, genetic studies offer the best opportunity to screen for novel insights of human pathology when little material is available. Precise estimates of DNA copy numbers in a given specimen are necessary. However, most studies investigate static variables such as the genetic background of patients or mutations within pathological specimens without a need to assess proportionality of expression among different genes throughout the genome. Comparative genomic hybridization of DNA samples represents a crude exception to this rule since genomic amplification or deletion is compared among different specimens directly. For gene expression analysis, however, it is critical to accurately estimate the proportional expression of distinct RNA transcripts since such proportions directly govern cell function by modulating protein expression. Furthermore, comparative estimates of relative RNA expression at different time points portray the response of cells to environmental stimuli, indirectly informing about broader biological events affecting a particular tissue in physiological or pathological conditions. This cognitive reaction of cells is similar to the detection of electroencephalographic patterns which inform about the status of the brain in response to external stimuli. As our need to understand human pathophysiology at the global level increases, the development and refinement of technologies for high fidelity messenger RNA amplification have become the focus of increasing interest during the past decade. The need to increase the abundance of RNA has been met not only for gene specific amplification, but, most importantly for global transcriptome wide, unbiased amplification. Now gene-specific, unbiased transcriptome wide amplification accurately maintains proportionality among all RNA species within a given specimen. This allows the utilization of clinical material obtained with minimally invasive methods such as fine needle aspirates (FNA) or cytological washings for high throughput functional genomics studies. This review provides a comprehensive and updated discussion of the literature in the subject and critically discusses the main approaches, the pitfalls and provides practical suggestions for successful unbiased amplification of the whole transcriptome in clinical samples.
临床样本的研究常常受到可用于研究的材料数量的限制。虽然蛋白质无法以其天然形式进行扩增,但DNA和RNA可以从小样本中进行扩增,并用于高通量分析。因此,当可用材料很少时,基因研究为筛选人类病理学的新见解提供了最佳机会。准确估计给定样本中的DNA拷贝数是必要的。然而,大多数研究调查的是静态变量,如患者的遗传背景或病理标本中的突变,而无需评估整个基因组中不同基因之间表达的比例关系。DNA样本的比较基因组杂交是这条规则的一个粗略例外,因为它直接在不同样本之间比较基因组的扩增或缺失。然而,对于基因表达分析来说,准确估计不同RNA转录本的比例表达至关重要,因为这些比例通过调节蛋白质表达直接控制细胞功能。此外,不同时间点相对RNA表达的比较估计描绘了细胞对环境刺激的反应,间接地反映了在生理或病理条件下影响特定组织的更广泛的生物学事件。细胞的这种认知反应类似于检测脑电图模式,后者反映了大脑对外部刺激的状态。随着我们在全球层面理解人类病理生理学的需求增加,在过去十年中,高保真信使RNA扩增技术的开发和完善已成为越来越受关注的焦点。不仅满足了基因特异性扩增对增加RNA丰度的需求,而且最重要的是满足了全转录组范围、无偏差扩增的需求。现在,基因特异性、无偏差的全转录组扩增能够准确维持给定样本中所有RNA种类之间的比例关系。这使得可以利用通过微创方法(如细针穿刺抽吸(FNA)或细胞学冲洗)获得的临床材料进行高通量功能基因组学研究。本综述对该主题的文献进行了全面且更新的讨论,批判性地讨论了主要方法、陷阱,并为临床样本中成功进行全转录组无偏差扩增提供了实用建议。