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. 2020 May 21;10(1):8468.
doi: 10.1038/s41598-020-64663-4.

Selection of Endogenous Control Reference Genes for Studies on Type 1 or Type 2 Endometrial Cancer

Thangesweran Ayakannu  1   2   3 , Anthony H Taylor  4   5 , Justin C Konje  4   6
Affiliations

Selection of Endogenous Control Reference Genes for Studies on Type 1 or Type 2 Endometrial Cancer

Thangesweran Ayakannu et al. Sci Rep. .

Abstract

A panel of 32 candidate reference genes was used to identify the most stable genes for gene normalisation in quantitative RT-PCR studies using endometrial biopsies obtained from women with endometrial cancer (type 1 or type 2) and without cancer (controls). RNA from the biopsies was isolated, examined for purity and quality, and then reverse transcribed into cDNA before being subjected to real-time qRT-PCR analysis in triplicate within the TaqMan gene Expression Assay kit. The most 'stable' endogenous control genes were then identified using the geNorm qbase + 2 and NormFinder software packages. PSMC4, PUM1 and IPO8 were identified as the best reference genes combination for type 1 endometrial cancer (grades 1, 2 and 3), whereas for type 2 endometrial cancer (serous and carcinosarcoma), UBC, MRPL19, PGK1 and PPIA were the best reference genes combination. We conclude that the use of these normaliser combinations should provide accurate interpretation of gene expression at the transcript level in endometrial cancer studies especially for types 1 and 2 cancers.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
GeNorm analyses of the reference genes. Average expression stability values (geNorm M) of the 32 reference genes are ranked from least to most stable expression (left to right) for type 1 EC data (upper panel) and type 2 EC data (lower panel). Data are presented according to the output file obtained from qbase + 2 software. An M value of ≤ 1.0 indicates more stable gene expression.
Figure 2
Figure 2
Determination of the optimal number of reference genes for normalisation. geNorm V scores, using the pair-wise variation (V) analyses within the geNormPLUS analysis software for the 32 reference genes for the incremental combination of V2/3 to V31/32 genes, are shown. The upper panel shows the data output file obtained for control and type 1 EC samples and the lower panel equivalent output data for control and type 2 EC samples. The horizontal line indicates the position of the geNorm threshold for stability (V = 0.15).
Figure 3
Figure 3
Normfinder analyses of the reference genes. The stability values for each of the 32 ‘housekeeping’ genes are shown, with the least stable on the left and the most stable on the right. A stability value < 0.5 is sufficient to predict either a stable gene in the type 1 EC cohort (upper panel) or the type 2 EC cohort (lower panel).
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References

    1. Jha A, et al. Towards precision medicine: discovering novel gynecological cancer biomarkers and pathways using linked data. J Biomed Semantics. 2017;8:40. doi: 10.1186/s13326-017-0146-9. - DOI - PMC - PubMed
    1. Xi, X. et al. RNA Biomarkers: Frontiers of precision medicine for cancer. Noncoding RNA3, 10.3390/ncrna3010009 (2017). - PMC - PubMed
    1. Torres A, Torres K, Wdowiak P, Paszkowski T, Maciejewski R. Selection and validation of endogenous controls for microRNA expression studies in endometrioid endometrial cancer tissues. Gynecol Oncol. 2013;130:588–594. doi: 10.1016/j.ygyno.2013.06.026. - DOI - PubMed
    1. Ayakannu, T., Taylor, A. H. & Konje, J. C. Cannabinoid receptor expression in estrogen-dependent and estrogen-independent endometrial cancer. J Recept Signal Transduct Res, 1-8, 10.1080/10799893.2018.1531890 (2018). - PubMed
    1. Ayakannu T, et al. Validation of endogenous control reference genes for normalizing gene expression studies in endometrial carcinoma. Mol Hum Reprod. 2015;21:723–735. doi: 10.1093/molehr/gav033. - DOI - PubMed

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