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

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.Colorectal cancer (CRC) is one of the most common causes of cancer worldwide affecting almost a million people annually and resulting in approximately 500,000 deaths [1]. Approximately 5% of individuals born today will be diagnosed with colorectal cancer during their lives, representing a lifetime risk of 1 in 19. CRC remains a serious threat to life with approximately 20% of patients presenting with late stage metastatic disease. Although 5 year survival rates are favourable at 80-90% for early stage disease, this drops significantly to less than 10% with the presence of distal metastasis.The majority of colorectal tumours originate from adenomatous precursor lesions and develop along a well-defined adenoma-carcinoma sequence. According to this model the culmination of mutational events including activation of oncogenes and loss of function of tumour suppressor genes results in the emergence of carcinomas [2]. Molecular profiling across the spectrum of normal-