Pan-Cancer Analysis of TCGA Data Revealed Promising Reference Genes for qPCR Normalization - Krasnov, George S.; Kudryavtseva, Anna V.; Snezhkina, Anastasiya V.; Lakunina, Valentina A.; Beniaminov, Artemy D.; Melnikova, Nataliya V.; Dmitriev, Alexey A. (Frontiers in Genetics, 2019)
Quantitative PCR (qPCR) remains the most widely used technique for gene expression evaluation. Obtaining reliable data using this method requires reference genes with stable mRNA level under experimental conditions. This issue is especially crucial in cancer studies because each tumor has a unique molecular portrait. The Cancer Genome Atlas (TCGA) project provides RNA-Seq data for thousands of samples corresponding to dozens of cancers and presents the basis for assessment of the suitability of genes as reference ones for qPCR data normalization. Using TCGA RNA-Seq data and previously developed CrossHub tool, we evaluated mRNA level of 32 traditionally used reference genes in 12 cancer types, including those of lung, breast, prostate, kidney, and colon. We developed an 11-component scoring system for the assessment of gene expression stability. Among the 32 genes, PUM1 was one of the most stably expressed in the majority of examined cancers, whereas GAPDH, which is widely used as a reference gene, showed significant mRNA level alterations in more than a half of cases. For each of 12 cancer types, we suggested a pair of genes that are the most suitable for use as reference ones. These genes are characterized by high expression stability and absence of correlation between their mRNA levels. Next, the scoring system was expanded with several features of a gene: mutation rate, number of transcript isoforms and pseudogenes, participation in cancer-related processes on the basis of Gene Ontology, and mentions in PubMed-indexed articles. All the genes covered by RNA-Seq data in TCGA were analyzed using the expanded scoring system that allowed us to reveal novel promising reference genes for each of examined cancer types and identify several ‘universal’ pan-cancer reference gene candidates, including SF3A1, CIAO1, and SFRS4. The choice of suitable reference genes is the basis for precise expression evaluation by qPCR. Here, we suggest optimal pairs of traditionally used reference genes for 12 cancer types and identified novel promising reference genes that demonstrate high expression stability and other features of reliable and convenient reference genes (high expression level, low mutation rate, non-involvement in cancer-related processes, single transcript isoform, and absence of pseudogenes).