INSERM, U955 EQ07, Paris Est University, Créteil, France.
Br J Cancer. 2010 Mar 16;102(6):1037-43. doi: 10.1038/sj.bjc.6605573. Epub 2010 Feb 23.
Microenvironmental conditions in normal or tumour tissues and cell lines may interfere on further biological analysis. To evaluate transcript variations carefully, it is common to use stable housekeeping genes (HKG) to normalise quantitative microarrays or real-time polymerase chain reaction results. However, recent studies argue that HKG fluctuate according to tissues and treatments. So, as an example of HKG variation under an array of conditions that are common in the cancer field, we evaluate whether hypoxia could have an impact on HKG expression.
Expression of 10 commonly used HKG was measured on four cell lines treated with four oxygen concentrations (from 1 to 20%).
Large variations of HKG transcripts were observed in hypoxic conditions and differ along with the cell line and the oxygen concentration. To elect the most stable HKG, we compared the three statistical means based either on PCR cycle threshold coefficient of variation calculation or two specifically dedicated software. Nevertheless, the best HKG dramatically differs according to the statistical method used. Moreover, using, as a reference, absolute quantification of a target gene (here the proteinase activating receptor gene 1 (PAR1) gene), we show that the conclusions raised about PAR1 variation in hypoxia can totally diverge according to the selected HKG used for normalisation.
The choice of a valid HKG will determine the relevance of the results that will be further interpreted, and so it should be seriously considered. The results of our study confirm unambiguously that HKG variations must be precisely and systematically determined before any experiment for each situation, to obtain reliable normalised results in the experimental setting that has been designed. Indeed, such assay design, functional for all in vitro systems, should be carefully evaluated before any extension to other experimental models including in vivo ones.
正常或肿瘤组织和细胞系的微环境条件可能会干扰进一步的生物学分析。为了仔细评估转录变体，通常使用稳定的管家基因 (HKG) 对定量微阵列或实时聚合酶链反应结果进行归一化。然而，最近的研究表明 HKG 根据组织和处理而波动。因此，作为癌症领域常见的一系列条件下 HKG 变化的一个例子，我们评估了缺氧是否会对 HKG 表达产生影响。
在四种细胞系中，用四种氧浓度（1 到 20%）处理后，测量了 10 种常用 HKG 的表达。
在缺氧条件下观察到 HKG 转录本的大量变化，并且随细胞系和氧浓度而变化。为了选择最稳定的 HKG，我们比较了基于 PCR 循环阈值变异系数计算或两种专门软件的三种统计方法。然而，最佳 HKG 根据所使用的统计方法而有很大差异。此外，使用绝对定量的靶基因（这里是蛋白酶激活受体基因 1 (PAR1) 基因）作为参考，我们表明，根据用于归一化的所选 HKG，对 PAR1 在缺氧中的变化的结论可能完全不同。
选择有效的 HKG 将决定进一步解释的结果的相关性，因此应认真考虑。我们的研究结果明确证实，在为每个情况设计的实验中，必须在进行任何实验之前精确和系统地确定 HKG 变化，以获得可靠的归一化结果。事实上，这种适用于所有体外系统的实验设计应在扩展到包括体内模型在内的其他实验模型之前进行仔细评估。
