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PLoS By Category | Recent PLoS Articles
Biochemistry - Hematology - Molecular Biology

Using Digital RNA Counting and Flow Cytometry to Compare mRNA with Protein Expression in Acute Leukemias
Published: Friday, November 09, 2012
Author: Paula Fernandez et al.

by Paula Fernandez, Max Solenthaler, Olivier Spertini, Stephane Quarroz, Alicia Rovo, Pierre-Yves Lovey, Leda Leoncini, Sylvie Ruault-Jungblut, Mathilde D’Asaro, Olivier Schaad, Mylène Docquier, Patrick Descombes, Thomas Matthes, Swiss Cytometry Society

Background

The diagnosis of malignant hematologic diseases has become increasingly complex during the last decade. It is based on the interpretation of results from different laboratory analyses, which range from microscopy to gene expression profiling. Recently, a method for the analysis of RNA phenotypes has been developed, the nCounter technology (Nanostring® Technologies), which allows for simultaneous quantification of hundreds of RNA molecules in biological samples. We evaluated this technique in a Swiss multi-center study on eighty-six samples from acute leukemia patients.

Methods

mRNA and protein profiles were established for normal peripheral blood and bone marrow samples. Signal intensities of the various tested antigens with surface expression were similar to those found in previously performed Affymetrix microarray analyses. Acute leukemia samples were analyzed for a set of twenty-two validated antigens and the Pearson Correlation Coefficient for nCounter and flow cytometry results was calculated.

Results

Highly significant values between 0.40 and 0.97 were found for the twenty-two antigens tested. A second correlation analysis performed on a per sample basis resulted in concordant results between flow cytometry and nCounter in 44–100% of the antigens tested (mean?=?76%), depending on the number of blasts present in a sample, the homogeneity of the blast population, and the type of leukemia (AML or ALL).

Conclusions

The nCounter technology allows for fast and easy depiction of a mRNA profile from hematologic samples. This technology has the potential to become a valuable tool for the diagnosis of acute leukemias, in addition to multi-color flow cytometry.

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