Clinical Utility of Microarray-Based Gene Expression Profiling in the Diagnosis and Subclassification of Leukemia: Report From the International Microarray Innovations in Leukemia Study Group

Author:

Haferlach Torsten1,Kohlmann Alexander1,Wieczorek Lothar1,Basso Giuseppe1,Kronnie Geertruy Te1,Béné Marie-Christine1,De Vos John1,Hernández Jesus M.1,Hofmann Wolf-Karsten1,Mills Ken I.1,Gilkes Amanda1,Chiaretti Sabina1,Shurtleff Sheila A.1,Kipps Thomas J.1,Rassenti Laura Z.1,Yeoh Allen E.1,Papenhausen Peter R.1,Liu Wei-min1,Williams P. Mickey1,Foà Robin1

Affiliation:

1. From the European LeukemiaNet, Gene Expression Profiling Working Group; MLL Munich Leukemia Laboratory, Munich; Department of Hematology and Oncology, University Hospital Benjamin Franklin, Charité, Berlin, Germany; Laboratorio di Ematologia e Oncologia Pediatrica, Università di Padova, Padova; Division of Hematology, “Sapienza” University, Rome, Italy; Centre Hospitalier Universitaire Montpellier, Hôpital St Eloi, Institut de Recherche en Biothérapie, Montpellier, France; Centro de Investigación del...

Abstract

Purpose The Microarray Innovations in Leukemia study assessed the clinical utility of gene expression profiling as a single test to subtype leukemias into conventional categories of myeloid and lymphoid malignancies. Methods The investigation was performed in 11 laboratories across three continents and included 3,334 patients. An exploratory retrospective stage I study was designed for biomarker discovery and generated whole-genome expression profiles from 2,143 patients with leukemias and myelodysplastic syndromes. The gene expression profiling–based diagnostic accuracy was further validated in a prospective second study stage of an independent cohort of 1,191 patients. Results On the basis of 2,096 samples, the stage I study achieved 92.2% classification accuracy for all 18 distinct classes investigated (median specificity of 99.7%). In a second cohort of 1,152 prospectively collected patients, a classification scheme reached 95.6% median sensitivity and 99.8% median specificity for 14 standard subtypes of acute leukemia (eight acute lymphoblastic leukemia and six acute myeloid leukemia classes, n = 693). In 29 (57%) of 51 discrepant cases, the microarray results had outperformed routine diagnostic methods. Conclusion Gene expression profiling is a robust technology for the diagnosis of hematologic malignancies with high accuracy. It may complement current diagnostic algorithms and could offer a reliable platform for patients who lack access to today's state-of-the-art diagnostic work-up. Our comprehensive gene expression data set will be submitted to the public domain to foster research focusing on the molecular understanding of leukemias.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

Cancer Research,Oncology

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