High throughput digital quantification of mRNA abundance in primary human acute myeloid leukemia samples

Jacqueline E. Payton, Nicole R. Grieselhuber, Li Wei Chang, Mark Murakami, Gary K. Geiss, Daniel C. Link, Rakesh Nagarajan, Mark A. Watson, Timothy J. Ley

Research output: Contribution to journalArticlepeer-review

104 Scopus citations

Abstract

Acute promyelocytic leukemia (APL) is characterized by the t(15;17) chromosomal translocation, which results in fusion of the retinoic acid receptor α (RARA) gene to another gene, most commonly promyelocytic leukemia (PML). The resulting fusion protein, PML-RARA, initiates APL, which is a subtype (M3) of acute myeloid leukemia (AML). In this report, we identify a gene expression signature that is specific to M3 samples; it was not found in other AML subtypes and did not simply represent the normal gene expression pattern of primary promyelocytes. To validate this signature for a large number of genes, we tested a recently developed high throughput digital technology (NanoString nCounter). Nearly all of the genes tested demonstrated highly significant concordance with our microarray data (P < 0.05). The validated gene signature reliably identified M3 samples in 2 other AML datasets, and the validated genes were substantially enriched in our mouse model of APL, but not in a cell line that inducibly expressed PML-RARA. These results demonstrate that nCounter is a highly reproducible, customizable system for mRNA quantification using limited amounts of clinical material, which provides a valuable tool for biomarker measurement in low-abundance patient samples.

Original languageEnglish
Pages (from-to)1714-1726
Number of pages13
JournalJournal of Clinical Investigation
Volume119
Issue number6
DOIs
StatePublished - Jun 1 2009

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