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Circulating microRNAs in the identification of biological fluids: A new approach to standardization of expression-based diagnostics

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Abstract

Molecular profiling of normal tissues is a regular and necessary step when developing systems for expression analyses in biological samples, including diagnostic panels for various diseases and conditions. Yet there are still no rigorous criteria to allow precise typing of normal tissues. A main problem is that the methods employed in diagnostic expression testing are difficult to standardize. While various technologies, instruments, and reagents are available, universal protocols of handling biological material are lacking, thus impairing the reproducibility of data from independent studies. The review describes a new approach to standardizing circulating microRNA studies in forensic biology, which has relatively recently (7–8 years ago) come to employ RNA markers in molecular typing of tissues and biological fluids. Forensic biology is now one of the few disciplines where several panels of tissue mRNA markers have been developed within a short period of time and a number of specific microRNA markers have been established and validated for several biological fluids. To allow their successful use, new protocols have been combined with the available, rigidly standardized system of genetic personal identification. Although a ready diagnostic product has still not been obtained with this well-working approach, the apparent efficiency of the standardization methods clearly demonstrates that the problem is possible to solve in other biomedical fields, including those where RNA-based diagnostic protocols are still under development.

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Abbreviations

STR:

short tandem repeat

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  1. LLC Nearmedic Plus, Moscow, 125252, Russia

    A. S. Bavykin

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Original Russian Text © A.S. Bavykin, 2017, published in Molekulyarnaya Biologiya, 2017, Vol. 51, No. 4, pp. 573–581.

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Bavykin, A.S. Circulating microRNAs in the identification of biological fluids: A new approach to standardization of expression-based diagnostics. Mol Biol 51, 506–513 (2017). https://doi.org/10.1134/S0026893317040045

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