DNA microarray analysis of hematopoietic stem cell-like fractions from individuals with the M2 subtype of acute myeloid leukemia

Gene expression profiling in the myelodysplastic syndromes

The myelodysplastic syndromes (MDS) are a heterogeneous group of haematopoietic malignancies, characterized by blood cytopenias, ineffective hematopoiesis and hypercellular bone marrow. Several genetic alterations have been reported in MDS but these are not MDS-specific and the underlying molecular causes of the disease remain poorly understood. Gene expression microarray technology allows the simultaneous parallel analysis of many thousands of genes and has already provided novel insights into cancer pathogenesis. In this review we discuss the results of several recent studies which utilize the enormous power of microarray technology for the study of MDS. Several exciting findings have emerged from these early studies that highlight the potential of this technology to further our understanding of the molecular pathogenesis of this disorder. It is clear, however, that these findings should be confirmed in larger sets of MDS patients.

DNA micro-array analysis of myelodysplastic syndrome

Myelodysplastic syndrome (MDS) is an enigmatic disorder characterized by ineffective hematopoiesis and dysplastic morphology of blood cells. The clinical course of MDS consists of distinct stages, with early stages often progressing to advanced ones or to acute myeloid leukemia (AML). Little is known of the molecular pathogenesis of MDS or of the mechanism of its stage progression. DNA micro-array analysis, which allows simultaneous monitoring of the expression levels of tens of thousands of genes, has the potential to provide insight into the pathophysiology of MDS. Several studies have applied this new technology to compare gene expression profiles either between MDS and the healthy condition, among the different stages of MDS or between MDS-derived AML and de novo AML. Selection of an appropriate hematopoietic fraction is important for such studies, which to date have been performed with differentiated granulocytes, CD34+ progenitors and CD133+ immature cells. These studies have revealed that each stage of MDS has its own 'molecular signature', indicating the feasibility of differential diagnosis of MDS based on gene expression profile. They have also demonstrated that the current clinical diagnosis of MDS results in the misclassification of patients with regard to these molecular signatures.

Applications of microarray technology to Acute Myelogenous Leukemia

Microarray technology is a powerful tool, which has been applied to further the understanding of gene expression changes in disease. Array technology has been applied to the diagnosis and prognosis of Acute Myelogenous Leukemia (AML). Arrays have also been used extensively in elucidating the mechanism of and predicting therapeutic response in AML, as well as to further define the mechanism of AML pathogenesis. In this review, we discuss the major paradigms of gene expression array analysis, and provide insights into the use of software tools to annotate the array dataset and elucidate deregulated pathways and gene interaction networks. We present the application of gene expression array technology to questions in acute myelogenous leukemia; specifically, disease diagnosis, treatment and prognosis, and disease pathogenesis. Finally, we discuss several new and emerging array technologies, and how they can be further utilized to improve our understanding of AML.

Gene stage-specific expression in the microenvironment of pediatric myelodysplastic syndromes

Using cDNA microarray assays we have observed a clear difference in the gene expression pattern between bone marrow stromal cells obtained from healthy children (CT) and from pediatric patients with either myelodysplastic syndromes (MDS) or acute myeloid leukemia (AML) associated with MDS (MDS-AML). The global gene function profiling analysis indicated that in the pediatric MDS microenvironment the disease stages may be characterized mainly by underexpression of genes associated with biological processes such as transport. Furthermore, a subset of downregulated genes related to endocytosis and protein secretion was able to discriminate MDS from MDS-AML.

Consensus guidelines for microarray gene expression analyses in leukemia from three European leukemia networks

A plethora of studies have documented that gene expression profiling using DNA microarrays for various types of hematological malignancies provides novel information, which may have diagnostic and prognostic implications. However, to successfully use microarrays for this purpose, the quality and reproducibility of the whole procedure need to be guaranteed. Critical steps of the method are handling, processing and storage of the leukemic sample, purification of tumor cells (or lack thereof), RNA extraction methods, quality control of RNA, labeling techniques, hybridization, washing, scanning, spot filtering, normalization and initial interpretation, and finally the biostatistical analysis. These items have been extensively discussed and evaluated in different multi-center quality rounds within the three networks, that is, I-BFM-SG, the German Competence Network 'Acute and Chronic Leukemias' and the European LeukemiaNet. Based on the exchange of knowledge and experience between the three networks over the last few years, we have formulated guidelines for performing microarray experiments in leukemia. We confine ourselves to leukemias, but many of these requirements also apply to lymphomas or other clinical samples, including solid tumors.

Gene expression profiling data in lymphoma and leukemia: review of the literature and extrapolation of pertinent clinical applications

CONTEXT

Gene expression (GE) analyses using microarrays have become an important part of biomedical and clinical research in hematolymphoid malignancies. However, the methods are time-consuming and costly for routine clinical practice.

OBJECTIVES

To review the literature regarding GE data that may provide important information regarding pathogenesis and that may be extrapolated for use in diagnosing and prognosticating lymphomas and leukemias; to present GE findings in Hodgkin and non-Hodgkin lymphomas, acute leukemias, and chronic myeloid leukemia in detail; and to summarize the practical clinical applications in tables that are referenced throughout the text.

DATA SOURCE

PubMed was searched for pertinent literature from 1993 to 2005.

CONCLUSIONS

Gene expression profiling of lymphomas and leukemias aids in the diagnosis and prognostication of these diseases. The extrapolation of these findings to more timely, efficient, and cost-effective methods, such as flow cytometry and immunohistochemistry, results in better diagnostic tools to manage the diseases. Flow cytometric and immunohistochemical applications of the information gained from GE profiling assist in the management of chronic lymphocytic leukemia, other low-grade B-cell non-Hodgkin lymphomas and leukemias, diffuse large B-cell lymphoma, nodular lymphocyte-predominant Hodgkin lymphoma, and classic Hodgkin lymphoma. For practical clinical use, GE profiling of precursor B acute lymphoblastic leukemia, precursor T acute lymphoblastic leukemia, and acute myeloid leukemia has supported most of the information that has been obtained by cytogenetic and molecular studies (except for the identification of FLT3 mutations for molecular analysis), but extrapolation of the analyses leaves much to be gained based on the GE profiling data.

Advances in the molecular genetics of acute leukemia

Acute leukemias are characterized by the unrestrained clonal proliferation of hematopoietic precursor cells coupled with aberrant or arrested differentiation. The molecular basis of hematopoiesis and leukemogenesis is still being defined, yet it is increasingly evident that acute leukemias have recurrent molecular features that can be exploited for diagnostic, prognostic, and therapeutic purposes. Modern molecular technologies already influence treatment strategies for these diseases, and it is likely that as such technology matures it will have an increasing impact on all aspects of acute leukemia management. This article reviews recent developments in the molecular classification, prognostication, and treatment of the acute leukemias.

Microarray analysis of tumour antigen expression in presentation acute myeloid leukaemia

Acute myeloid leukaemia (AML) is a difficult to treat disease, especially for those patients who have no eligible haematopoietic stem cell (HSC) donor. One of the most promising treatment options for these patients is immunotherapy. To investigate the expression of known tumour antigens in AML, we analysed microarray data from 124 presentation AML patient samples and investigated the present/absent calls of 82 tumour-specific or -associated antigens. We found 11 antigens which were expressed in AML patient samples but not normal donors. Nine of these were cancer-testis (CT) antigens, previously shown to be expressed in tumour cells and immunologically protected sites and at very low levels, if at all, in normal tissues. Expression was confirmed using real-time PCR. We have identified a number of CT antigens with expression in presentation AML samples but not normal donor samples, which may provide effective targets for future immunotherapy treatments early in disease.

Experimental trial for diagnosis of pancreatic ductal carcinoma based on gene expression profiles of pancreatic ductal cells

Pancreatic ductal carcinoma (PDC) remains one of the most intractable human malignancies, mainly because of the lack of sensitive detection methods. Although gene expression profiling by DNA microarray analysis is a promising tool for the development of such detection systems, a simple comparison of pancreatic tissues may yield misleading data that reflect only differences in cellular composition. To directly compare PDC cells with normal pancreatic ductal cells, we purified MUC1-positive epithelial cells from the pancreatic juices of 25 individuals with a normal pancreas and 24 patients with PDC. The gene expression profiles of these 49 specimens were determined with DNA microarrays containing >44 000 probe sets. Application of both Welch's analysis of variance and effect size-based selection to the expression data resulted in the identification of 21 probe sets corresponding to 20 genes whose expression was highly associated with clinical diagnosis. Furthermore, correspondence analysis and 3-D projection with these probe sets resulted in separation of the transcriptomes of pancreatic ductal cells into distinct but overlapping spaces corresponding to the two clinical classes. To establish an accurate transcriptome-based diagnosis system for PDC, we applied supervised class prediction algorithms to our large data set. With the expression profiles of only five predictor genes, the weighted vote method diagnosed the class of samples with an accuracy of 81.6%. Microarray analysis with purified pancreatic ductal cells has thus provided a basis for the development of a sensitive method for the detection of PDC.

Reproducibility, fidelity, and discriminant validity of mRNA amplification for microarray analysis from primary hematopoietic cells

Analysis of gene expression in clinical samples poses special challenges, including limited RNA availability and poor RNA quality. Quantitative information regarding reliability of RNA amplification methodologies applied to primary cells and representativeness of resulting gene expression profiles is limited. We evaluated four protocols for RNA amplification from peripheral blood mononuclear cells. Results obtained with 100 ng or 10 ng of RNA amplified using two rounds of cDNA synthesis and in vitro transcription were compared with control 2.5-microg RNA samples processed using a single round of in vitro transcription. Samples were hybridized to Affymetrix HG-U133A arrays. Considerable differences in results were obtained with different protocols. The optimal protocol resulted in highly reproducible gene expression profiles from amplified samples (r = 0.98) and good correlation between amplified and control samples (r = 0.94). Using the optimal protocol dissimilarities of gene expression between mononuclear cells from a normal individual and a patient with myelodysplastic syndrome were primarily maintained after amplification compared with controls. We conclude that small variations in methodology introduce considerable distortion of gene expression profiles obtained after RNA amplification from clinical samples and too strong a focus on a very small number of genes picked from an array analysis could be unduly influenced by seemingly acceptable methodologies. However, it is possible to obtain reproducible and representative results using optimized protocols.

Stratification of Acute Myeloid Leukemia Based on Gene Expression Profiles

Acute myeloid leukemia (AML) is characterized by clonal growth of immature leukemic blasts and develops either de novo or secondarily to anticancer treatment or to other hematologic disorders. Given that the current classification of AML, which is based on blast karyotype and morphology, is not sufficiently robust to predict the prognosis of each affected individual, new stratification schemes that are of better prognostic value are needed. Global profiling of gene expression in AML blasts has the potential both to identify a small number of genes whose expression is associated with clinical outcome and to provide insight into the molecular pathogenesis of this condition. Emerging genomics tools, especially DNA microarray analysis, have been applied in attempts to isolate new molecular markers for the differential diagnosis of AML and to identify genes that contribute to leukemogenesis. Progress in bioinformatics has also yielded means with which to classify patients according to clinical parameters such as long-term prognosis. The application of such analysis to large sets of gene expression data has begun to provide the basis for a new AML classification that is more powerful with regard to prediction of prognosis.

Gene expression profiles at diagnosis in de novo childhood AML patients identify FLT3 mutations with good clinical outcomes

Fms-like tyrosine kinase 3 (FLT3) mutations are associated with unfavorable outcomes in children with acute myeloid leukemia (AML). We used DNA microarrays to identify gene expression profiles related to FLT3 status and outcome in childhood AML. Among 81 diagnostic specimens, 36 had FLT3 mutations (FLT3-MUs), 24 with internal tandem duplications (ITDs) and 12 with activating loop mutations (ALMs). In addition, 8 of 19 specimens from patients with relapses had FLT3-MUs. Predictive analysis of microarrays (PAM) identified genes that differentiated FLT3-ITD from FLT3-ALM and FLT3 wild-type (FLT3-WT) cases. Among the 42 specimens with FLT3-MUs, PAM identified 128 genes that correlated with clinical outcome. Event-free survival (EFS) in FLT3-MU patients with a favorable signature was 45% versus 5% for those with an unfavorable signature (P = .018). Among FLT3-MU specimens, high expression of the RUNX3 gene and low expression of the ATRX gene were associated with inferior outcome. The ratio of RUNX3 to ATRX expression was used to classify FLT3-MU cases into 3 EFS groups: 70%, 37%, and 0% for low, intermediate, and high ratios, respectively (P < .0001). Thus, gene expression profiling identified AML patients with divergent prognoses within the FLT3-MU group, and the RUNX3 to ATRX expression ratio should be a useful prognostic indicator in these patients. (Blood. 2004;104:2646-2654)

DNA microarray analysis of dysplastic morphology associated with acute myeloid leukemia

OBJECTIVE

Acute myeloid leukemia (AML) develops de novo or secondarily to either myelodysplastic syndrome (MDS) or anticancer treatment (therapy-related leukemia, TRL). Prominent dysplasia of blood cells is apparent in individuals with MDS-related AML as well as in some patients with TRL or even with de novo AML. The clinical entity of AML with multilineage dysplasia (AML-MLD) is likely to be an amalgamation of MDS-related AML and de novo AML-MLD. The aim of this study was to clarify, by the use of high-density oligonucleotide microarrays, whether these subcategories of AML are intrinsically distinct from each other.

MATERIALS AND METHODS

The AC133+ hematopoietic stem cell-like fractions were purified from the bone marrow of individuals with de novo AML without dysplasia (n = 15), AML-MLD (n = 11), MDS-related AML (n = 11), or TRL (n = 2), and were subjected to the synthesis of cRNA which was subsequently hybridized to microarray harboring oligonucleotide corresponding to more than 12,000 probe sets.

RESULTS

We could identify many genes whose expression was specific to these various subcategories of AML. Furthermore, with the correspondence analysis/three-dimensional projection strategy, we were able to visualize the independent, yet partially overlapping, nature of current AML subcategories on the basis of their transcriptomes.

CONCLUSION

Our data indicate the possibility of subclassification of AML based on gene expression profiles of leukemic blasts.

Distinctive gene expression profiles of CD34 cells from patients with myelodysplastic syndrome characterized by specific chromosomal abnormalities

Aneuploidy, especially monosomy 7 and trisomy 8, is a frequent cytogenetic abnormality in the myelodysplastic syndromes (MDSs). Patients with monosomy 7 and trisomy 8 have distinctly different clinical courses, responses to therapy, and survival probabilities. To determine disease-specific molecular characteristics, we analyzed the gene expression pattern in purified CD34 hematopoietic progenitor cells obtained from MDS patients with monosomy 7 and trisomy 8 using Affymetrix GeneChips. Two methods were employed: standard hybridization and a small-sample RNA amplification protocol for the limited amounts of RNA available from individual cases; results were comparable between these 2 techniques. Microarray data were confirmed by gene amplification and flow cytometry using individual patient samples. Genes related to hematopoietic progenitor cell proliferation and blood cell function were dysregulated in CD34 cells of both monosomy 7 and trisomy 8 MDS. In trisomy 8, up-regulated genes were primarily involved in immune and inflammatory responses, and down-regulated genes have been implicated in apoptosis inhibition. CD34 cells in monosomy 7 showed up-regulation of genes inducing leukemia transformation and tumorigenesis and apoptosis and down-regulation of genes controlling cell growth and differentiation. These results imply distinct molecular mechanisms for monosomy 7 and trisomy 8 MDS and implicate specific pathogenic pathways.