Lustig Arthur J
Department of Biochemistry and Molecular Biology, Tulane University, USA.
J Cancer Epidemiol Treat. 2015;1(1):28-37. doi: 10.24218/jcet.2015.08. Epub 2015 Aug 12.
Real time qPCR has become the method of choice for rapid large-scale telomere length measurements. Large samples sizes are critical for clinical trials, and epidemiological studies. QPCR has become such routine procedure that it is often used with little critical analysis. With proper controls, the mean telomere size can be derived from the data and even the size can be estimated. But there is a need for more consistent and reliable controls that will provide closer to the actual mean size can be obtained with uniform consensus controls. Although originating at the level of basic telomere research, many researchers less familiar with telomeres often misunderstand the source and significance of the qPCR metric. These include researchers and clinicians who are interested in having a rapid tool to produce exciting results in disease prognostics and diagnostics than in the multiple characteristics of telomeres that form the basis of the measurement. But other characteristics of the non-bimodal and heterogeneous telomeres as well as the complexities of telomere dynamics are not easily related to qPCR mean telomere values. The qPCR metric does not reveal the heterogeneity and dynamics of telomeres. This is a critical issue since mutations in multiple genes including telomerase can cause telomere dysfunction and a loss of repeats. The smallest cellular telomere has been shown to arrest growth of the cell carrying the dysfunction telomere. A goal for the future is a simple method that takes into account the heterogeneity by measuring the highest and lowest values as part of the scheme to compare. In the absence of this technique, Southern blots need to be performed in a subset of qPCR samples for both mean telomere size and the upper and lower extremes of the distribution. Most importantly, there is a need for greater transparency in discussing the limitations of the qPCR data. Given the potentially exciting qPCR telomere size results emerging from clinical studies that relate qPCR mean telomere size estimates to disease states, the current ambiguities have become urgent issues to validate the findings and to set the right course for future clinical investigations.
实时定量聚合酶链反应(qPCR)已成为快速大规模测量端粒长度的首选方法。大样本量对于临床试验和流行病学研究至关重要。qPCR已成为一种常规程序,以至于在使用时常常缺乏严格的分析。通过适当的对照,可以从数据中得出平均端粒大小,甚至可以估计其大小。但是,需要更一致、可靠的对照,以便能通过统一的标准对照获得更接近实际平均大小的值。尽管起源于基础端粒研究层面,但许多不太熟悉端粒的研究人员常常误解qPCR指标的来源和意义。这些人包括研究人员和临床医生,他们更感兴趣的是拥有一种能在疾病预后和诊断中产生令人兴奋结果的快速工具,而不是构成测量基础的端粒的多种特征。但是,非双峰和异质性端粒的其他特征以及端粒动态变化的复杂性并不容易与qPCR平均端粒值相关联。qPCR指标无法揭示端粒的异质性和动态变化。这是一个关键问题,因为包括端粒酶在内的多个基因发生突变会导致端粒功能障碍和重复序列丢失。已证明最小的细胞端粒会阻止携带功能异常端粒的细胞生长。未来的一个目标是找到一种简单的方法,通过测量最高值和最低值来考虑异质性,作为比较方案的一部分。在缺乏这种技术的情况下,需要对一部分qPCR样本进行Southern印迹分析,以确定平均端粒大小以及分布的上限和下限。最重要的是,在讨论qPCR数据的局限性时需要有更高的透明度。鉴于临床研究中出现的将qPCR平均端粒大小估计值与疾病状态相关联的潜在令人兴奋的结果,当前的模糊性已成为验证研究结果和为未来临床研究确定正确方向的紧迫问题。