Ferdowsi University of Mashhad

Document Type : Research Articles

Authors

1 Department of Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran

2 Stem Cell and Regenerative Medicine Research Centre, Iran University of Medical Sciences (IUMS), Tehran, Iran

Abstract

Cancer is one of the most challenging diseases in the world. It is widely accepted that knowing the molecular aspects of diseases, including cancers, helps to develop methods for their therapy and diagnosis. Long non-coding RNAs (lncRANs) are a novel category of regulatory genes known to be involved in cancer incidence. The expression of these genes is said to be suitable of using in prognosis, diagnosis, targeted therapy, etc. The RT-qPCR method that is widely used for analyzing the gene expression requires the application of appropriate reference genes as the internal control. The expression status of a proper housekeeping reference gene is not supposed to change under experimental circumstances. This study aimed to find a suitable reference gene in the U87 cells after overexpression of a gene of interest. To this aim, the expression status of four common reference genes (ACTB, β2M, GAPDH, and HPRT1) was examined in the transfected U87 cells. The U87 cells were transfected with a vector overexpressing YWHAE-lncRNA and an empty vector (mock). After total RNA extraction and cDNA synthesis, RT-qPCR was applied using the aforementioned internal control genes. Data were analyzed, and their graphs were plotted in GraphPad Prism 8.2 software. Β2M showed the most change; accordingly, GAPDH and HPRT1 expression levels were changed about 5 and 4 times, respectively. Of the candidate genes, only the ACTB gene had a consistent expression level in two different modes of transfection, and therefore, it is suggested as an appropriate reference gene for the study of gene expression in the transfected U87 cell line. It is remained to be tested if β2M, GAPDH, and HPRT1 common internal controls are specifically affected by YWHAE-lncRNA overexpression or other lncRNAs may affect their expression as well.

Keywords

Aithal M. and Rajeswari N. (2015) Validation of housekeeping genes for gene expression analysis in glioblastoma using quantitative real-time polymerase chain reaction. Brain Tumor Research and Treatment 3(1): 24–29. 
Akiyama Y., Komiyama M., Miyata H., Yagoto M., Ashizawa T., Iizuka A., et al. (2014) Novel cancer-testis antigen expression on glioma cell lines derived from high-grade glioma patients. Oncology Reports 31:1683– 1690.
Appin C. L. and Brat D. J. (2014) Molecular genetics of gliomas. Cancer Journal 20:66–72.
Choori M., Boozarpour S., Moradi A. and Jorjani E. (2018) Investigation of POU5F1 and NANOG gene expression in colon cancer cell line (Caco-2) treated by dendrosomal nano-curcumin. Cellular and Molecular Researches (Iranian Journal of Biology) 31(3):292-301.
Dundas J. and Ling M. (2012) Reference genes for measuring mRNA expression. Theory in Biosciences 131:215–223.
Futreal P. A., Coin L., Marshall M., Down T., Hubbard T., Wooster R., et al. (2004) A census of human cancer genes. Nature Reviews Cancer 4(3):177–83.
Gabriele R., Arend K., Boris K., Pantelis S., Roland G. and Marco T. (2018) ACTB and SDHA are suitable endogenous reference genes for gene expression studies in human astrocytomas using quantitative RT-PCR. Technology in Cancer Research & Treatment 17:1-6.
Grube S., Go¨ttig T., Freitag D., Ewald C., Kalff R. and Walter J. (2015) Selection of suitable reference genes for expression analysis in human glioma using RT-Qpcr. Journal of Neurooncology 123:35–42.
Hornberg J. J., Bruggeman F. J., Westerhoff H. V. and Lankelma J. (2006) Cancer: a systems biology disease. Biosystems 83(2–3):81–90.
Jung T. Y., Choi Y. D., Kim Y. H., Lee J. J., Kim H. S., Kim J. S., et al. (2013) Immunological characterization of glioblastoma cells for immunotherapy. Anticancer Research 33(6):2525-33.
Kreth S., Heyn J., Grau S., Kretzschmar H. A., Egensperger R. and Kreth F. W. (2010) Identification of valid endogenous control genes for determining gene expression in human glioma. Neuro-Oncology 12:570–579.
Li Y., Liu Y., Zhu H., Chen X., Tian M., Wei Y., et al. (2020) N-acetylglucosaminyltransferase I promotes glioma cell proliferation and migration through increasing the stability of the glucose transporter GLUT1. FEBS Letters 594(2):358-366.
Lin Y. H., Guo L., Yan F., Dou Z. Q., Yu Q. and Chen G. (2020) Long non-coding RNA HOTAIRM1 promotes proliferation and inhibits apoptosis of glioma cells by regulating the miR-873-5p/ZEB2 axis. Chinese Medical Journal 133(2):174-182.
Liu T., Zhang T., Zhou F., Wang J., Zhai X., Mu N., et al.  (2017) Identification of genes and pathways potentially related to PHF20 by gene expression profile analysis of glioblastoma U87 cell line. Cancer Cell International 17: 87.
Lou J. Y., Luo J., Yang S. C., Ding G. F., Liao W., Zhou R. X., et al. (2020) Long non-coding RNA SUMO1P3 promotes glioma progression via the Wnt/β-catenin pathway. European Review for Medical and Pharmacological Sciences 24(18):9571-9580.
Louis D. N., Ohgaki H., Wiestler O. D., Cavenee W. K., Burger P. C., Jouvet A., et al. (2007) The 2007 WHO classification of tumors of the central nervous system. Acta Neuropathology 114:97–109.
Nie Q. M., Lin Y. Y., Yang X., Shen L., Guo L. M., Que S. L., et al. (2015) IDH1R¹³²H decreases the proliferation of U87 glioma cells through upregulation of microRNA-128a. Molecular Medicine Reports 12(5):6695-701.
Nolan T., Hands R. E. and Bustin S. A. (2006) Quantification of mRNA using real-time RT-PCR. Nature Protocols 1:1559–1582.
Röhn G., Koch A., Krischek B., Stavrinou P., Goldbrunner R. and Timmer M. (2018) ACTB and SDHA are suitable endogenous reference genes for gene expression studies in human astrocytomas using quantitative RT-PCR. Technology in Cancer Research & Treatment 1:17.
Soltanian S., and Sheikhbahaei M. (2021) Identification of suitable housekeeping genes for quantitative gene expression analysis during retinoic acid-induced differentiation of embryonal carcinoma NCCIT cells. Journal of Cell and Molecular Research 12(2):104-10.
Taylor S. C., Nadeau K., Abbasi M., Lachance C., Nguyen M. and Fenrich J. (2019) The ultimate qPCR experiment: producing publication quality, reproducible data the first time. Trends in Biotechnology 37(7):761-774.
Valente V., Teixeira S. A., Neder L., Okamoto O. K., Oba-Shinjo S. M., Marie S. K., et al. (2014) Selection of suitable housekeeping genes for expression analysis in glioblastoma using quantitative RT-PCR. Annals of Neurosciences 21(2):62-3.
Wang Z., Chen N., Yang J., Wang Q. and Li A. (2019) Microarray gene profiling analysis of glioblastoma cell line U87 reveals suppression of the FANCD2/Fanconi anemia pathway by the combination of Y15 and temozolomide. Archives of Medical Science 15(4):1035-1046.
Wong M. L. and Medrano J. F. (2005) Real-time PCR for mRNA quantitation. Biotechniques 39:75–85.
Xu N., Liu B., Lian C., Doycheva D. M., Fu Z., Liu Y., et al. (2018) Long noncoding RNA AC003092.1 promotes temozolomide chemosensitivity through miR-195/TFPI-2 signaling modulation in glioblastoma. Cell Death 19(12):1139.
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