GeneChip, geNorm, and gastrointestinal tumors: novel reference genes for real-time PCR
Open Access
- 1 August 2007
- journal article
- research article
- Published by American Physiological Society in Physiological Genomics
- Vol. 30 (3), 363-370
- https://doi.org/10.1152/physiolgenomics.00251.2006
Abstract
Accurate quantitation of target genes depends on correct normalization. Use of genes with variable tissue transcription (GAPDH) is problematic, particularly in clinical samples, which are derived from different tissue sources. Using a large-scale gene database (Affymetrix U133A) data set of 36 gastrointestinal (GI) tumors and normal tissues, we identified 8 candidate reference genes and established expression levels by real-time RT-PCR in an independent data set (n = 42). A geometric averaging method (geNorm) identified ALG9, TFCP2, and ZNF410 as the most robustly expressed control genes. Examination of raw CT values demonstrated that these genes were tightly correlated between themselves (R2 > 0.86, P < 0.0001), with low variability [coefficient of variation (CV) r = 0.93, P = 0.001). In comparison, the alternative control gene, GAPDH, exhibited the highest variability (CV = 18.1%), was significantly differently expressed between tissue types (P = 0.05), was poorly correlated with the three reference genes (R2 < 0.4), and was considered the least stable gene. To illustrate the importance of correct normalization, the target gene, MTA1, was significantly overexpressed (P = 0.0006) in primary GI neuroendocrine tumor (NET) samples (vs. normal GI samples) when normalized by geNormATZ but not when normalized using GAPDH. The geNormATZ approach was, in addition, applicable to adenocarcinomas; MTA1 was overexpressed (P < 0.04) in malignant colon, pancreas, and breast tumors compared with normal tissues. We provide a robust basis for the establishment of a reference gene set using GeneChip data and provide evidence for the utility of normalizing a malignancy-associated gene (MTA1) using novel reference genes and the geNorm approach in GI NETs as well as in adenocarcinomas and breast tumors.Keywords
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