Selection of reliable reference genes for gene expression study in nasopharyngeal carcinoma
Abstract
Aim: To construct a system for selecting reference genes (RGs) and to select the most optimal RGs for gene expression studies in nasopharyngeal carcinoma (NPC).
Methods: The total RNAs from 20 NPC samples were each labeled with Cy5-dUTP. To create a common control, the total RNA from 15 nasopharyngeal phlogistic (NP) tissues was mixed and labeled via reverse transcription with Cy3-dUTP. cDNA microarrays containing 14 112 genes were then performed. A mathematical approach was constructed to screen stably expressed genes from the microarray data. Using this method, three genes (YARS, EIF3S7, and PFDN1) were selected as candidate RGs. Furthermore, 7 commonly used RGs (HPRT1, GAPDH, TBP, ACTB, B2M, G6PDH, and HBB) were selected as additional potential RGs. Real-time PCR was used to detect these 10 candidate genes' expression levels and the geNorm program was used to find the optimal RGs for NPC studies.
Results: On the basis of the 10 candidate genes' expression stability level, geNorm analysis identified the optimal single RG (YARS or HPRT1) and the most suitable set of RGs (HPRT1, YARS, and EIF3S7) for NPC gene expression studies. In addition, this analysis determined that B2M, G6PDH, and HBB were not appropriate for use as RGs. Interestingly, ACTB was the least stable RG in our study, even though previous studies had indicated that it was one of the most stable RGs. Three novel candidate genes (YARS, EIF3S7, and PFDN1), which were selected from microarray data, were all identified as suitable RGs for NPC research. A RG-selecting system was then constructed, which combines microarray data analysis, a literature screen, real-time PCR, and bioinformatic analysis.
Conclusion: We construct a RG-selecting system that helps find the optimal RGs. This process, applied to NPC research, determined the single RG (YARS or HPRT1) and the set of RGs (HPRT1, YARS, and EIF3S7) that are the most suitable internal controls.
Keywords:
Methods: The total RNAs from 20 NPC samples were each labeled with Cy5-dUTP. To create a common control, the total RNA from 15 nasopharyngeal phlogistic (NP) tissues was mixed and labeled via reverse transcription with Cy3-dUTP. cDNA microarrays containing 14 112 genes were then performed. A mathematical approach was constructed to screen stably expressed genes from the microarray data. Using this method, three genes (YARS, EIF3S7, and PFDN1) were selected as candidate RGs. Furthermore, 7 commonly used RGs (HPRT1, GAPDH, TBP, ACTB, B2M, G6PDH, and HBB) were selected as additional potential RGs. Real-time PCR was used to detect these 10 candidate genes' expression levels and the geNorm program was used to find the optimal RGs for NPC studies.
Results: On the basis of the 10 candidate genes' expression stability level, geNorm analysis identified the optimal single RG (YARS or HPRT1) and the most suitable set of RGs (HPRT1, YARS, and EIF3S7) for NPC gene expression studies. In addition, this analysis determined that B2M, G6PDH, and HBB were not appropriate for use as RGs. Interestingly, ACTB was the least stable RG in our study, even though previous studies had indicated that it was one of the most stable RGs. Three novel candidate genes (YARS, EIF3S7, and PFDN1), which were selected from microarray data, were all identified as suitable RGs for NPC research. A RG-selecting system was then constructed, which combines microarray data analysis, a literature screen, real-time PCR, and bioinformatic analysis.
Conclusion: We construct a RG-selecting system that helps find the optimal RGs. This process, applied to NPC research, determined the single RG (YARS or HPRT1) and the set of RGs (HPRT1, YARS, and EIF3S7) that are the most suitable internal controls.