Document Type

Journal Article

Publication Title

Cells

Volume

12

Issue

13

PubMed ID

37443822

Publisher

MDPI

School

School of Medical and Health Sciences

RAS ID

61899

Funders

National Institutes of Health / National Eye Institute / NIH National Heart, Lung, and Blood Institute / NIH National Institute on Aging

Comments

Schröder, H. M., Niebergall-Roth, E., Norrick, A., Esterlechner, J., Ganss, C., Frank, M. H., & Kluth, M. A. (2023). Drug regulatory-compliant validation of a qPCR assay for bioanalysis studies of a cell therapy product with a special focus on matrix interferences in a wide range of organ tissues. Cells, 12(13), article 1788. https://doi.org/10.3390/cells12131788

Abstract

Quantitative polymerase chain reaction (qPCR) has emerged as an important bioanalytical method for assessing the pharmacokinetics of human-cell-based medicinal products after xenotransplantation into immunodeficient mice. A particular challenge in bioanalytical qPCR studies is that the different tissues of the host organism can affect amplification efficiency and amplicon detection to varying degrees, and ignoring these matrix effects can easily cause a significant underestimation of the true number of target cells in a sample. Here, we describe the development and drug regulatory-compliant validation of a TaqMan qPCR assay for the quantification of mesenchymal stromal cells in the range of 125 to 20,000 cells/200 L lysate via the amplification of a human-specific, highly repetitive α-satellite DNA sequence of the chromosome 17 centromere region HSSATA17. An assessment of matrix effects in 14 different mouse tissues and blood revealed a wide range of spike recovery rates across the different tissue types, from 11 to 174%. Based on these observations, we propose performing systematic spike-and-recovery experiments during assay validation and correcting for the effects of the different tissue matrices on cell quantification in subsequent bioanalytical studies by multiplying the back-calculated cell number by tissue-specific factors derived from the inverse of the validated percent recovery rate.

DOI

10.3390/cells12131788

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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