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鉴定miR-4644作为肝细胞癌循环miRNA定量的合适内源性标准化物。

Identification of miR-4644 as a suitable endogenous normalizer for circulating miRNA quantification in hepatocellular carcinoma.

作者信息

Zhao Jun, Zhu Xin-Chao, Wu Xiao-Song, Wang Lin, Zhu Can-Can, Yang Ke, Deng Guo-Qing, Wang An, Liu Yong, Jia Wei-Dong, Zhu Ling

机构信息

Center of Engineering Technology Research for Biomedical Optical Instrument, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.

Science Island Branch of Graduate School, University of Science and Technology of China, Hefei 230026, China.

出版信息

J Cancer. 2020 Oct 17;11(23):7032-7044. doi: 10.7150/jca.48903. eCollection 2020.

DOI:10.7150/jca.48903
PMID:33123293
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7592003/
Abstract

Circulating microRNAs (miRNAs) have proved to be promising biomarkers for early diagnosis and therapeutic monitoring in cancers. Particularly for hepatocellular carcinoma (HCC), detection of circulating miRNA biomarkers as a new diagnostic approach has been written into the latest Guidelines for Diagnosis and Treatment of Primary Liver Cancer in China (2019 edition). However, no general consensus on an ideal endogenous normalizer for circulating miRNAs quantification has been reached, so it will affect the accuracy of quantitative results. In this study, we aim to identify a stable endogenous normalizer for analyzing circulating miRNAs. Candidate miRNAs were selected by screening dataset GSE104310, as well as data statistics and analysis. Five commonly reference genes were chosen for further comparison and verification. Then, the expression levels of these genes in serum were analyzed by quantitative reverse transcription PCR (RT-qPCR) among four groups, including patients diagnosed with HCC, chronic hepatitis B (CHB), liver cirrhosis, and healthy subjects. Furthermore, the stability of target genes was evaluated using geNorm, NormFinder, comparative ΔCq programs, and validated by database. We also explored the availability of the miRNA combination, and compared the performance difference between combination and individuals, as well as the selectivity of miRNA references in the combinations. 11 candidate miRNAs were obtained, and miR-4644 stood out among these miRNAs, and proved to be much more stable than other endogenous miRNAs. Further study showed that miR-4644 exhibited higher stability and expression abundance than other commonly miRNA reference controls. Finally, we discovered the combination of miR-4644 and miR-16 revealed high performance in stability when compared to miRNA individuals. Furthermore, the combination consisted of references with closer nature could give rise to amplification effects in stability. Our findings demonstrated that miR-4644 is an ideal endogenous normalizer for circulating microRNA quantification in hepatocellular carcinoma. Besides, combining miR-4644 with miR-16 into a whole as a reference control would greatly improve the accuracy of quantification.

摘要

循环微RNA(miRNA)已被证明是癌症早期诊断和治疗监测的有前景的生物标志物。特别是对于肝细胞癌(HCC),检测循环miRNA生物标志物作为一种新的诊断方法已被写入中国最新的《原发性肝癌诊疗规范(2019年版)》。然而,对于循环miRNA定量的理想内源性标准化物尚未达成普遍共识,因此这会影响定量结果的准确性。在本研究中,我们旨在鉴定一种用于分析循环miRNA的稳定内源性标准化物。通过筛选数据集GSE104310以及数据统计和分析来选择候选miRNA。选择五个常用的参考基因进行进一步比较和验证。然后,通过定量逆转录PCR(RT-qPCR)分析这四个组(包括诊断为HCC、慢性乙型肝炎(CHB)、肝硬化的患者和健康受试者)血清中这些基因的表达水平。此外,使用geNorm、NormFinder、比较ΔCq程序评估靶基因的稳定性,并通过数据库进行验证。我们还探索了miRNA组合的可用性,比较了组合与单个miRNA的性能差异以及组合中miRNA参考的选择性。获得了11个候选miRNA,其中miR-4644在这些miRNA中脱颖而出,并且被证明比其他内源性miRNA更稳定。进一步研究表明,miR-4644比其他常用的miRNA参考对照具有更高的稳定性和表达丰度。最后,我们发现与单个miRNA相比,miR-4644和miR-16的组合在稳定性方面表现出高性能。此外,由性质更接近的参考组成的组合在稳定性方面可能会产生放大效应。我们的研究结果表明,miR-4644是肝细胞癌循环微RNA定量的理想内源性标准化物。此外,将miR-4644与miR-16组合作为一个整体作为参考对照将大大提高定量的准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/03da31041cad/jcav11p7032g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/7058829f9ac9/jcav11p7032g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/31d363b583e6/jcav11p7032g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/e9fe00cda889/jcav11p7032g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/280687d7d401/jcav11p7032g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/03da31041cad/jcav11p7032g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/faae47201fc9/jcav11p7032g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/3275a12f7c66/jcav11p7032g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/7058829f9ac9/jcav11p7032g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/31d363b583e6/jcav11p7032g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/e9fe00cda889/jcav11p7032g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/280687d7d401/jcav11p7032g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf1/7592003/03da31041cad/jcav11p7032g007.jpg

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