Identification of endogenous control genes for normalisation of real-time quantitative PCR data in colorectal cancer

• Published in: BMC molecular biology 2010-02, Vol.11 (1), p.12-12, Article 12
• Main Authors: Kheirelseid, Elrasheid A H, Chang, Kah Hoong, Newell, John, Kerin, Michael J, Miller, Nicola
• Format: Article
• Language: English
• Subjects: beta 2-Microglobulin - genetics; beta 2-Microglobulin - standards; Biomarkers, Tumor - genetics; Cohort Studies; Colorectal cancer; Colorectal Neoplasms - genetics; Efficiency; Gene expression; Gene Expression Regulation, Neoplastic; Genetic aspects; Health aspects; Humans; Medical research; Peptidylprolyl Isomerase - genetics; Peptidylprolyl Isomerase - standards; Polymerase chain reaction; Polymerase Chain Reaction - standards; Reference Standards; Research article; Standard deviation; Statistical analysis; Studies
• ISSN: 1471-2199; 1471-2199
• 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.