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

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

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.

Entinostat prevents leukemia maintenance in a collaborating oncogene-dependent model of CN-AML.

The incidence of refractory acute myeloid leukemia (AML) is on the increase due in part to an aging population that fails to respond to traditional therapies. High throughput genomic analysis promises better diagnosis, prognosis and therapeutic intervention based on improved patient stratification. Relevant pre-clinical models are urgently required to advance drug development in this area. The collaborating oncogenes, HOXA9 and MEIS1, are frequently co-overexpressed in cytogenetically normal AML (CN-AML) and a conditional transplantation mouse model was developed that demonstrated oncogene-dependency and expression levels comparable to CN-AML patients. Integration of gene signatures obtained from the mouse model and a cohort of CN-AML patients using statistically significant connectivity Map (sscMap) analysis identified Entinostat as a drug with the potential to alter the leukemic condition towards the normal state. Ex vivo treatment of leukemic cells, but not age-matched normal bone marrow controls, with Entinostat validated the gene signature and resulted in reduced viability in liquid culture, impaired colony formation and loss of the leukemia initiating cell. Furthermore, in vivo treatment with Entinostat resulted in prolonged survival of leukemic mice. This study demonstrates that the HDAC inhibitor Entinostat inhibits disease maintenance and prolongs survival in a clinically relevant murine model of cytogenetically normal AML. © 2013 AlphaMed Press

Establishing optimal quantitative-polymerase chain reaction assays for routine diagnosis and tracking of minimal residual disease in JAK2-V617F-associated myeloproliferative neoplasms:a joint European LeukemiaNet/MPN&MPNr-EuroNet (COST action BM0902) study

Reliable detection of JAK2-V617F is critical for accurate diagnosis of myeloproliferative neoplasms (MPNs); in addition, sensitive mutation-specific assays can be applied to monitor disease response. However, there has been no consistent approach to JAK2-V617F detection, with assays varying markedly in performance, affecting clinical utility. Therefore, we established a network of 12 laboratories from seven countries to systematically evaluate nine different DNA-based quantitative PCR (qPCR) assays, including those in widespread clinical use. Seven quality control rounds involving over 21,500 qPCR reactions were undertaken using centrally distributed cell line dilutions and plasmid controls. The two best-performing assays were tested on normal blood samples (n=100) to evaluate assay specificity, followed by analysis of serial samples from 28 patients transplanted for JAK2-V617F-positive disease. The most sensitive assay, which performed consistently across a range of qPCR platforms, predicted outcome following transplant, with the mutant allele detected a median of 22 weeks (range 6-85 weeks) before relapse. Four of seven patients achieved molecular remission following donor lymphocyte infusion, indicative of a graft vs MPN effect. This study has established a robust, reliable assay for sensitive JAK2-V617F detection, suitable for assessing response in clinical trials, predicting outcome and guiding management of patients undergoing allogeneic transplant.

Up-regulated MSI2 is associated with more aggressive chronic myeloid leukemia

A better understanding of events triggering chronic myeloid leukemia progression are critical to optimised clinical management of chronic myeloid leukemia (CML). We sought to validate that increased Musashi 2 (MSI2), a post transcription regulator, expression is associated with progression and prognosis. Screening of 152 CML patients showed MSI2 was significantly decreased among CML patients in CP at diagnosis (p<0.0001), but found no significant difference between the normal control group and treated CML patients in CP. Moreover it was significantly increased (p<0.0001) in advance disease (AD) CML patients. Furthermore, our human hematopoietic cell line data imply MSI2 and BCR-ABL1 mRNA expression correlate. However, these data cast a doubt on earlier reports that MSI2 effects HES1 expression via NUMB-NOTCH signaling.

CD38 expression level and pattern of expression remains a reliable and robust marker of progressive disease in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) follows a variable clinical course which is difficult to predict at diagnosis. We assessed somatic mutation (SHM) status, CD38 and ZAP-70 expression in 87 patients (49 male, 38 female) with stage A CLL and known cytogenetic profile to compare their role in predicting disease progression, which was assessed by the treatment free interval (TFI) from diagnosis. Sixty (69%) patients were SHM+, 24 (28%) were CD38+ and ten (12%) were ZAP-70+. The median TFI for: (i) SHM + versus SHM- patients was 124 versus 26 months; hazard ratio (HR) = 3.6 [95% confidence interval (CI) = 1.8 - 7.3; P = 0.001]: (ii) CD38- versus CD38+ patients was 120 versus 34 months; HR = 2.4 (95% CI = 1.4 - 5.3; P = 0.02); and (iii) ZAP70- versus ZAP70+ was 120 versus 16 months; HR = 3.4 (95% CI = 1.4 - 8.7; P = 0.01). SHM status and CD38 retained prognostic significance on multivariate analysis whereas ZAP-70 did not. We conclude that ZAP-70 analysis does not provide additional prognostic information in this group of patients.

Inter-Laboratory Evaluation of a Next-Generation Sequencing Panel for Acute Myeloid Leukemia

INTRODUCTION: Acute myeloid leukemia (AML) is a heterogeneous clonal disorder often associated with dismal overall survival. The clinical diversity of AML is reflected in the range of recurrent somatic mutations in several genes, many of which have a prognostic and therapeutic value. Targeted next-generation sequencing (NGS) of these genes has the potential for translation into clinical practice. In order to assess this potential, an inter-laboratory evaluation of a commercially available AML gene panel across three diagnostic centres in the UK and Ireland was performed.

METHODS: DNA from six AML patient samples was distributed to each centre and processed using a standardised workflow, including a common sequencing platform, sequencing chips and bioinformatics pipeline. A duplicate sample in each centre was run to assess inter- and intra-laboratory performance.

RESULTS: An average sample read depth of 2725X (range 629-5600) was achieved using six samples per chip, with some variability observed in the depth of coverage generated for individual samples and between centres. A total of 16 somatic mutations were detected in the six AML samples, with a mean of 2.7 mutations per sample (range 1-4) representing nine genes on the panel. 15/16 mutations were identified by all three centres. Allelic frequencies of the mutations ranged from 5.6 to 53.3 % (median 44.4 %), with a high level of concordance of these frequencies between centres, for mutations detected.

CONCLUSION: In this inter-laboratory comparison, a high concordance, reproducibility and robustness was demonstrated using a commercially available NGS AML gene panel and platform.

De novo methylation of tumor suppressor gene p16/INK4a is a frequent finding in multiple myeloma patients at diagnosis.

The p16 gene competes with cyclin D for binding to CDK4/CDK6 and therefore inhibits CDK4/6 complex kinase activity, resulting in dephosphorylation of pRb and related G1 growth arrest. Inactivation of this gene has been involved in a variety of tumors by different mechanisms: homozygous/hemyzygous deletions, point mutations and methylation of a 5' CpG island into exon E1alpha of the p16 gene. Homozygous deletions have been rarely found in multiple myeloma (MM) and no point mutations have been reported. Two recent studies have reported a high prevalence of methylation in the exon E1alpha of the p16 gene, but included only a small number of cases. We have analyzed the methylation pattern of exon E1alpha of the p16 gene in 101 untreated MM and five primary plasma cell leukemias (PCL). A PCR assay, relying on the inability of some restriction enzymes to digest methylated sequences, was used to analyze the methylation status. Southern blot analysis was used to confirm these results. Forty-one of 101 MM patients (40.5%) as well as four of the five (80%) primary PCL patients had shown methylation of the exon E1alpha. Our study confirms that hypermethylation of the p16 gene is a frequent event in MM. Leukemia (2000) 14, 183-187.

Fault Diagnosis in Internal Combustion Engines Using Nonlinear Multivariate Statistics

This paper presents a statistical-based fault diagnosis scheme for application to internal combustion engines. The scheme relies on an identified model that describes the relationships between a set of recorded engine variables using principal component analysis (PCA). Since combustion cycles are complex in nature and produce nonlinear relationships between the recorded engine variables, the paper proposes the use of nonlinear PCA (NLPCA). The paper further justifies the use of NLPCA by comparing the model accuracy of the NLPCA model with that of a linear PCA model. A new nonlinear variable reconstruction algorithm and bivariate scatter plots are proposed for fault isolation, following the application of NLPCA. The proposed technique allows the diagnosis of different fault types under steady-state operating conditions. More precisely, nonlinear variable reconstruction can remove the fault signature from the recorded engine data, which allows the identification and isolation of the root cause of abnormal engine behaviour. The paper shows that this can lead to (i) an enhanced identification of potential root causes of abnormal events and (ii) the masking of faulty sensor readings. The effectiveness of the enhanced NLPCA based monitoring scheme is illustrated by its application to a sensor fault and a process fault. The sensor fault relates to a drift in the fuel flow reading, whilst the process fault relates to a partial blockage of the intercooler. These faults are introduced to a Volkswagen TDI 1.9 Litre diesel engine mounted on an experimental engine test bench facility.