Abstract
Identification of appropriate reference genes (RGs) is critical to accurate data interpretation in quantitative real-time PCR (qPCR) experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq) to analyse the transcriptome of a panel of non-melanoma skin cancer lesions, identifying genes that are consistently expressed across all samples. Genes encoding ribosomal proteins were amongst the most stable in this dataset. Validation of this RNA-seq data was examined using qPCR to confirm the suitability of a set of highly stable genes for use as qPCR RGs. These genes will provide a valuable resource for the normalisation of qPCR data for the analysis of non-melanoma skin cancer.
Highlights
There is a growing need for identification of biomarkers of non-melanoma skin cancer (NMSC) for accurate diagnoses of skin lesions, and to predict progression and patient response to novel treatments
We demonstrated the importance of accurate reference genes (RGs) selection by performing relative quantitation analysis for several targeted gene expression profiles in non-photodamaged skin, actinic keratosis (AK) and squamous cell carcinoma (SCC) lesions where normalisation was performed using either new RGs together or traditional RG GAPDH
To demonstrate the significance of our findings in NMSC research, we investigated the difference in expression of keratin 17 (KRT17) in AK between normalization using our candidate RGs and normalization with GAPHD (Fig. 3)
Summary
There is a growing need for identification of biomarkers of non-melanoma skin cancer (NMSC) for accurate diagnoses of skin lesions, and to predict progression and patient response to novel treatments. Quantitative real-time PCR (qPCR) is an integral technique for gene expression analysis in dermatology research, due to its high sensitivity and specificity. An ideal reference should be uniformly expressed in all samples within the given experiment. How to cite this article Hoang et al (2017), RNA-seq reveals more consistent reference genes for gene expression studies in human nonmelanoma skin cancers. A previous preliminary study on a number of cell lines and tumour versus matched normal tissue samples showed that inappropriate choice of RGs may lead to errors when interpreting experiments involving quantitation of gene expression (Janssens et al, 2004)
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call