Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome.

The diagnosis of myelodysplastic syndrome (MDS) currently relies primarily on the morphologic assessment of the patient's bone marrow and peripheral blood cells. Moreover, prognostic scoring systems rely on observer-dependent assessments of blast percentage and dysplasia. Gene expression profiling could enhance current diagnostic and prognostic systems by providing a set of standardized, objective gene signatures. Within the Microarray Innovations in LEukemia study, a diagnostic classification model was investigated to distinguish the distinct subclasses of pediatric and adult leukemia, as well as MDS. Overall, the accuracy of the diagnostic classification model for subtyping leukemia was approximately 93%, but this was not reflected for the MDS samples giving only approximately 50% accuracy. Discordant samples of MDS were classified either into acute myeloid leukemia (AML) or "none-of-the-targets" (neither leukemia nor MDS) categories. To clarify the discordant results, all submitted 174 MDS samples were externally reviewed, although this did not improve the molecular classification results. However, a significant correlation was noted between the AML and "none-of-the-targets" categories and prognosis, leading to a prognostic classification model to predict for time-dependent probability of leukemic transformation. The prognostic classification model accurately discriminated patients with a rapid transformation to AML within 18 months from those with more indolent disease.

An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase.

Gene expression profiling has the potential to enhance current methods for the diagnosis of haematological malignancies. Here, we present data on 204 analyses from an international standardization programme that was conducted in 11 laboratories as a prephase to the Microarray Innovations in LEukemia (MILE) study. Each laboratory prepared two cell line samples, together with three replicate leukaemia patient lysates in two distinct stages: (i) a 5-d course of protocol training, and (ii) independent proficiency testing. Unsupervised, supervised, and r(2) correlation analyses demonstrated that microarray analysis can be performed with remarkably high intra-laboratory reproducibility and with comparable quality and reliability.

Intraplatform reproducibility and technical precision of gene expression profiling in 4 laboratories investigating 160 leukemia samples: the DACH study.

BACKGROUND: Gene expression profiling has the potential to offer consistent, objective diagnostic test results once a standardized protocol has been established. We investigated the robustness, precision, and reproducibility of microarray technology. METHODS: One hundred sixty individual patient samples representing 11 subtypes of acute and chronic leukemias, myelodysplastic syndromes, and nonleukemia as a control group were centrally collected and diagnosed as part of the daily routine in the Munich Leukemia Laboratory. The custom AmpliChip Leukemia research microarray was used for technical analyses of quadruplicate mononuclear cell lysates in 4 different laboratories in Germany (D), Austria (A), and Switzerland (CH) (the DACH study). RESULTS: Total-RNA preparations were successfully performed in 637 (99.5%) of 640 cases. Mean differences between pairs of laboratories in the total-RNA yield from the same sample ranged from 0.02 mug to 1.03 mug. Further processing produced 622 successful in vitro transcription reactions (97.6%); the mean differences between laboratories in the cRNA yield from the same sample ranged from 0.40 mug to 6.18 mug. After hybridization to microarrays, a mean of 47.6%, 46.5%, 46.2%, and 46.4% of probe sets were detected as present for the 4 laboratories, with mean signal-intensity scaling factors of 3.1, 3.7, 4.0, and 4.2, respectively. In unsupervised hierarchical cluster and principal component analyses, replicates from the same patient always clustered closely together, with no indications of any association between gene expression profiles due to different operators or laboratories. CONCLUSIONS: Microarray analysis can be performed with high interlaboratory reproducibility and with comparable quality and high technical precision across laboratories.

An international study to standardize the detection and quantitation of BCR-ABL transcripts from stabilized peripheral blood preparations by quantitative RT-PCR.

Due to the lack of comparability of BCR-ABL mRNA quantification results generated by various methodologies in different laboratories, an international multicenter trial was started with the participation of six laboratories (platforms: LightCycler LC, n=3; TaqMan TM, n=3). One hundred and eighty-six PB samples derived from healthy donors were spiked with serial dilutions (1:20 to 1:2x10(6)) of b2a2, b3a2 or e1a2 BCR-ABL positive white blood cells (WBC) from leukemic patients. After PAXgene stabilization, blinding, freezing and distribution, standardized RNA extraction, cDNA synthesis, PCR protocols and data evaluation were carried out. There was no significant difference in the results achieved using LC and TM technologies, but a considerable overall variation (CV=0.74 for ratios BCR-ABL/ABL). Up to a dilution of 1:1,000, 27/30 of the 2.5 mL samples tested positive. For higher dilutions, a PB volume of 5 or 10 ml was required to improve sensitivity. The study showed the feasibility of RQ-PCR standardization independent of the PCR machine used.

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.

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.