Department of Surgery, National University of Ireland, Galway, Ireland.
BMC Mol Biol. 2010 Feb 1;11:12. doi: 10.1186/1471-2199-11-12.
Gene expression analysis has many applications in cancer diagnosis, prognosis and therapeutic care. Relative quantification is the most widely adopted approach whereby quantification of gene expression is normalised relative to an endogenously expressed control (EC) gene. Central to the reliable determination of gene expression is the choice of control gene. The purpose of this study was to evaluate a panel of candidate EC genes from which to identify the most stably expressed gene(s) to normalise RQ-PCR data derived from primary colorectal cancer tissue.
The expression of thirteen candidate EC genes: B2M, HPRT, GAPDH, ACTB, PPIA, HCRT, SLC25A23, DTX3, APOC4, RTDR1, KRTAP12-3, CHRNB4 and MRPL19 were analysed in a cohort of 64 colorectal tumours and tumour associated normal specimens. CXCL12, FABP1, MUC2 and PDCD4 genes were chosen as target genes against which a comparison of the effect of each EC gene on gene expression could be determined. Data analysis using descriptive statistics, geNorm, NormFinder and qBasePlus indicated significant difference in variances between candidate EC genes. We determined that two genes were required for optimal normalisation and identified B2M and PPIA as the most stably expressed and reliable EC genes.
This study identified that the combination of two EC genes (B2M and PPIA) more accurately normalised RQ-PCR data in colorectal tissue. Although these control genes might not be optimal for use in other cancer studies, the approach described herein could serve as a template for the identification of valid ECs in other cancer types.
基因表达分析在癌症诊断、预后和治疗护理中有广泛的应用。相对定量是最广泛采用的方法,其中基因表达的定量相对于内源性表达的对照(EC)基因进行归一化。可靠地确定基因表达的关键是选择对照基因。本研究的目的是评估一组候选 EC 基因,从中鉴定最稳定表达的基因(多个),以对源自原发性结直肠癌组织的 RQ-PCR 数据进行归一化。
在 64 例结直肠肿瘤和肿瘤相关正常标本的队列中分析了 13 个候选 EC 基因:B2M、HPRT、GAPDH、ACTB、PPIA、HCRT、SLC25A23、DTX3、APOC4、RTDR1、KRTAP12-3、CHRNB4 和 MRPL19。选择 CXCL12、FABP1、MUC2 和 PDCD4 基因作为靶基因,以比较每个 EC 基因对基因表达的影响。使用描述性统计、geNorm、NormFinder 和 qBasePlus 进行数据分析表明,候选 EC 基因之间的方差存在显著差异。我们确定需要两个基因进行最佳归一化,并确定 B2M 和 PPIA 为最稳定和可靠的 EC 基因。
本研究确定,两种 EC 基因(B2M 和 PPIA)的组合更准确地对结直肠组织中的 RQ-PCR 数据进行了归一化。尽管这些对照基因在其他癌症研究中可能不是最佳选择,但本文描述的方法可以作为在其他癌症类型中鉴定有效 EC 的模板。