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Updated: Feb 21, 2026
A Flow Cytometry-Based Cell Surface Protein Binding Assay for Assessing Selectivity and Specificity of an Anticancer Aptamer
Published on: September 13, 2022
Cancer-related mRNA expression analysis using a novel flow cytometry-based assay
Barbara Depreter1,2,3, Jan Philippé1,3,4, Magali Meul2,3
1Department of Clinical Chemistry, Microbiology and Immunology, Ghent University, Ghent, Belgium.
Background:
Cancer-related gene expression data mostly originate from unfractionated bulk samples, leading to "expression averaging" of heterogeneous populations. Multicolor flow cytometry (FCM) may distinguish heterogeneous populations based on the phenotypic characterization of single-cells, but is not applicable for RNA targets. Here, we evaluated the PrimeFlow™ RNA assay, a novel FCM-based assay designed to measure gene expressions, in two cancer entities with high and low RNA target levels.
Methods:
Neuroblastoma (NB) cell lines were studied for MYCN gene expression by PrimeFlow™ and compared with the gold standard, RT-qPCR. Dilution series of NB cells (0.10-11%) were prepared to evaluate performance in small cell populations. Diagnostic material of de novo acute myeloid leukemia (AML) patients was used to measure Wilms' tumor 1 (WT1) expression in bulk leukemic cells and rare subsets, e.g. leukemic stem cells (LSCs). FCM analysis was performed on a FACSCanto II (BD Biosciences) using Infinicyt™ (Cytognos® ) for data analysis. mRNA expression was reported by normalized mean fluorescence intensity (MFI) values and staining indices.
Results:
MYCN mRNA quantified by PrimeFlow™ significantly correlated with RT-qPCR and remained detectable in small (0.1%) populations. Using PrimeFlowTM , WT1 levels were shown to be significantly higher in AML patient samples with WT1 overexpression, previously defined by RT-qPCR. Moreover, WT1 overexpression was distinguishable between heterogeneous cell populations and remained measurable in rare LSCs.
Conclusion:
PrimeFlow™ is a sensitive technique to investigate mRNA expressions, with high concordance to RT-qPCR. High (MYCN) and subtle (WT1) overexpressed mRNA targets can be quantified in heterogeneous and rare subpopulations e.g. LSCs. © 2017 International Clinical Cytometry Society.
Insights
The PrimeFlow™ RNA assay accurately measures gene expression in cancer cells, even rare ones. This flow cytometry method shows high concordance with RT-qPCR for MYCN and WT1 gene expression analysis.
Area of Science:
- Single-cell analysis in oncology
- Molecular diagnostics
- Gene expression profiling
Background:
- Cancer gene expression studies often use bulk samples, averaging heterogeneous cell populations.
- Multicolor flow cytometry (FCM) can phenotype single cells but not RNA targets.
- The PrimeFlow™ RNA assay was evaluated for measuring gene expression via FCM.
Purpose of the Study:
- To evaluate the PrimeFlow™ RNA assay for quantifying gene expression in cancer.
- To assess its performance in detecting both high and low RNA target levels.
- To compare its accuracy against established methods like RT-qPCR.
Main Methods:
- Neuroblastoma cell lines were analyzed for MYCN gene expression using PrimeFlow™ and RT-qPCR.
- Dilution series were used to test detection in small cell populations (0.10-11%).
- Acute myeloid leukemia (AML) patient samples were assessed for WT1 expression in bulk and rare subsets (leukemic stem cells).
Main Results:
- PrimeFlow™ accurately quantified MYCN mRNA, correlating well with RT-qPCR and detecting expression in 0.1% cell populations.
- WT1 levels were significantly higher in AML patients with overexpression, as confirmed by RT-qPCR.
- PrimeFlow™ distinguished WT1 overexpression in heterogeneous cells and detected it in rare leukemic stem cells.
Conclusions:
- PrimeFlow™ RNA assay is a sensitive method for mRNA expression analysis with high concordance to RT-qPCR.
- It enables quantification of both highly and subtly overexpressed mRNA targets in heterogeneous and rare cell subpopulations.
- The assay is valuable for analyzing gene expression in complex biological samples, including rare cell populations like LSCs.
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