RESUMEN
Accurate and reliable relative gene expression analysis via the Reverse Transcription-quantitative Real Time PCR (RT-qPCR) method strongly depends on employing several stable reference genes as normalizers. Utilization of the reference genes without analyzing their expression stability under each experimental condition causes RT-qPCR analysis error as well as false output. Similar to cancerous tissues, cancer cell lines also exhibit various gene expression profiles. It is crucial to recognize stable reference genes for well-known cancer cell lines to minimize RT-qPCR analysis error. In this study, we showed the expression level and investigated the expression stability of eight common reference genes that are ACTB, YWHAZ, HPRT1, RNA18S, TBP, GAPDH, UBC, and B2M, in two sets of cancerous cell lines. One set contains MCF7, SKBR3, and MDA-MB231 as breast cancer cell lines. Another set includes three hepatic cancer cell lines, including Huh7, HepG2, and PLC-PRF5. Three excel-based softwares comprising geNorm, BestKeeper, and NormFinder, and an online tool, namely RefFinder were used for stability analysis. Although all four algorithms did not show the same stability ranking of nominee genes, the overall results showed B2M and ACTB as the least stable reference genes for the studied breast cancer cell lines. While TBP had the lowest expression stability in the three hepatic cancer cell lines. Moreover, YWHAZ, UBC, and GAPDH showed the highest stability in breast cancer cell lines. Besides that, a panel of five nominees, including ACTB, HPRT1, UBC, YWHAZ, and B2M showed higher stability than others in hepatic cancer cell lines. We believe that our results would help researchers to find and to select the best combination of the reference genes for their own experiments involving the studied breast and hepatic cancer cell lines. To further analyze the reference genes stability for each experimental condition, we suggest researchers to consider the provided stability ranking emphasizing the unstable reference genes.
Asunto(s)
Neoplasias Hepáticas , Algoritmos , Humanos , Células MCF-7 , Programas InformáticosRESUMEN
Accurate relative gene expression analysis by reverse transcription-quantitative polymerase chain reaction relies on the usage of suitable reference genes for data normalization. The RNA content of small extracellular vesicles including exosomes is growingly considered as cancer biomarkers. So, reliable relative quantification of exosomal messenger RNA (mRNA) is essential for cancer diagnosis and prognosis applications. However, suitable reference genes for accurate normalization of a target gene in exosomes derived from cancer cells are not depicted yet. Here, we analyzed the expression and stability of eight well-known reference genes namely GAPDH, B2M, HPRT1, ACTB, YWHAZ, UBC, RNA18S, and TBP in exosomes-isolated from the liver (Huh7, HepG2, PLC/PRF/5) and breast (SK-BR-3) cancer cell lines using five different algorithms including geNorm, BestKeeper, Delta Ct, NormFinder, and RefFinder. Our results showed that ACTB, TBP, and HPRT1 were not expressed in exosomes-isolated from studied liver and breast cancer cell lines. The geNorm and BestKeeper algorithms indicated GAPDH and UBC as the most stable candidates. Moreover, Delta Ct and NormFinder algorithms showed YWHAZ as the most stable reference genes. Comprehensive ranking calculated by the RefFinder algorithm also pointed out GAPDH, YWHAZ, and UBC as the first three stable reference genes. Taken together, this study validated the common reference genes stability in exosomal mRNA derived from liver and breast cancer cell lines for the first time. We believe that this study would be the first step in finding more stable reference genes in exosomes that triggers more accurate detection of exosomal biomarkers.