Selection of suitable reference genes for accurate normalization of gene expression profile studies in non-small cell lung cancer.
Selection of suitable reference genes for accurate normalization of gene expression profile studies in non-small cell lung cancer.
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DOI：
10.1186/1471-2407-6-200
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发表时间：
2006-07-26
期刊：
影响因子：
3.8
通讯作者：
Calogero RA
中科院分区：
文献类型：
--
作者：
Saviozzi S;Cordero F;Lo Iacono M;Novello S;Scagliotti GV;Calogero RA
在实时定量RT-PCR中，归一化数据的准确性很大程度上依赖于参考基因(RGS)的可靠性。未能使用适当的控制基因对qPCR数据进行归一化可能会导致基因表达谱有偏见，以及精确度较低，从而只有表达水平的粗略变化才被宣布具有统计意义，或者表达模式被错误地描述。因此，确定潜在的RGS是否适合特定的实验目的是至关重要的。本研究的目的是确定和验证RGS在区分正常肺和肿瘤肺表达谱中的应用。用基因芯片技术产生的肺癌转录图谱的荟萃分析被用来识别五个假定的RG。应用Taqman探针对18例非小细胞肺癌(NSCLC)根治术患者肺组织冰冻标本进行检测，并与7种常用RGS的一致性进行比较。显示的12个RGS的Ct值范围很大：除rRNA18S(平均值为9.8)外，所有商品化RGS和ESD的平均值在19至26之间，而微阵列选择的RGS(BTF-3、YAP1、HIST1H2BC、RPL30)的平均值超过26。通过(1)描述性统计；(2)等价性检验；(3)GeNorm小应用程序，评估RG在样本群体内和实验条件下(肿瘤与正常肺标本)的表达稳定性。结果表明，POLR2A、rRNA18S、YAP1和ESD是最稳定的RGS。这些数据表明POLR2A、rRNA18S、YAP1和ESD是最适合于非小细胞肺癌基因表达谱研究的RGS。此外，他们强调了商业RGS的局限性，并表明全基因组转录图谱研究的元数据分析可能识别新的RGS。
In real-time RT quantitative PCR (qPCR) the accuracy of normalized data is highly dependent on the reliability of the reference genes (RGs). Failure to use an appropriate control gene for normalization of qPCR data may result in biased gene expression profiles, as well as low precision, so that only gross changes in expression level are declared statistically significant or patterns of expression are erroneously characterized. Therefore, it is essential to determine whether potential RGs are appropriate for specific experimental purposes. Aim of this study was to identify and validate RGs for use in the differentiation of normal and tumor lung expression profiles. A meta-analysis of lung cancer transcription profiles generated with the GeneChip technology was used to identify five putative RGs. Their consistency and that of seven commonly used RGs was tested by using Taqman probes on 18 paired normal-tumor lung snap-frozen specimens obtained from non-small-cell lung cancer (NSCLC) patients during primary curative resection. The 12 RGs displayed showed a wide range of Ct values: except for rRNA18S (mean 9.8), the mean values of all the commercial RGs and ESD ranged from 19 to 26, whereas those of the microarray-selected RGs (BTF-3, YAP1, HIST1H2BC, RPL30) exceeded 26. RG expression stability within sample populations and under the experimental conditions (tumour versus normal lung specimens) was evaluated by: (1) descriptive statistic; (2) equivalence test; (3) GeNorm applet. All these approaches indicated that the most stable RGs were POLR2A, rRNA18S, YAP1 and ESD. These data suggest that POLR2A, rRNA18S, YAP1 and ESD are the most suitable RGs for gene expression profile studies in NSCLC. Furthermore, they highlight the limitations of commercial RGs and indicate that meta-data analysis of genome-wide transcription profiling studies may identify new RGs.
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