Molecular characterization of acute leukemias by use of microarray technology

Identification of a molecular signature predictive of sensitivity to differentiation induction in acute myeloid leukemia

Acute myeloid leukemia (AML) blasts are immature committed myeloid cells unable to spontaneously undergo terminal maturation, and characterized by heterogeneous sensitivity to natural differentiation inducers. Here, we show a molecular signature predicting the resistance or sensitivity of six myeloid cell lines to differentiation induced in vitro with retinoic acid or vitamin D. The identified signature was further validated by TaqMan assay for the prediction of response to an in vitro differentiation assay performed on 28 freshly isolated AML blast populations. The TaqMan assay successfully predicts the in vitro resistance or responsiveness of AML blasts to differentiation inducers. Furthermore, performing a meta-analysis of publicly available microarray data sets, we also show the accuracy of our prediction on known phenotypes and suggest that our signature could become useful for the identification of patients eligible for new therapeutic strategies.

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.

Construction and validation of a bone marrow tissue microarray

BACKGROUND

The use of tissue microarrays (TMAs) is now a generally accepted method for the investigation of solid tumours. However, little is known about the applicability of the TMA technique for analysis of patients with acute leukaemia. A bone marrow (BM)-TMA analysis with 15 different immunohistochemical markers was performed. The TMA was validated by comparison with the corresponding full tissue sections.

MATERIALS AND METHODS

A BM-TMA comprising 148 cases of acute leukaemia, including 115 acute myeloid leukaemia (AML) and 33 acute lymphoblastic leukaemia (ALL) cases, was constructed. Expression of CD3, CD10, CD15, CD20, CD34, CD61, CD68, CD79a, CD99, CD117, CD138, myeloperoxidase, haemoglobin A1, glycophorin and terminal deoxynucleotidyl transferase was immunohistochemically analysed. 50 cases of the TMA were directly compared with the corresponding full tissue section to validate the results.

RESULTS

Morphologically and immunohistochemically, 6 (4%) of 148 cases and 765 (11%) cores of 6912 individual analyses were not evaluable. A direct comparison of TMA cases with conventional full sections showed a concordance of the results of 100%.

CONCLUSIONS

The small size of bone-marrow biopsies and the presence of bony trabeculae do not preclude construction and analysis of acute leukaemia TMAs. Acute leukaemia cases on TMA displayed the characteristic phenotypic profiles expected in different AML and ALL subtypes. Therefore, the TMA technique is also a promising method for high-throughput analysis of combined marker expression and clinicopathological correlations in patients with leukaemia.

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.

Gene expression profiling of adult acute myeloid leukemia identifies novel biologic clusters for risk classification and outcome prediction

To determine whether gene expression profiling could improve risk classification and outcome prediction in older acute myeloid leukemia (AML) patients, expression profiles were obtained in pretreatment leukemic samples from 170 patients whose median age was 65 years. Unsupervised clustering methods were used to classify patients into 6 cluster groups (designated A to F) that varied significantly in rates of resistant disease (RD; P < .001), complete response (CR; P = .023), and disease-free survival (DFS; P = .023). Cluster A (n = 24), dominated by NPM1 mutations (78%), normal karyotypes (75%), and genes associated with signaling and apoptosis, had the best DFS (27%) and overall survival (OS; 25% at 5 years). Patients in clusters B (n = 22) and C (n = 31) had the worst OS (5% and 6%, respectively); cluster B was distinguished by the highest rate of RD (77%) and multidrug resistant gene expression (ABCG2, MDR1). Cluster D was characterized by a "proliferative" gene signature with the highest proportion of detectable cytogenetic abnormalities (76%; including 83% of all favorable and 34% of unfavorable karyotypes). Cluster F (n = 33) was dominated by monocytic leukemias (97% of cases), also showing increased NPM1 mutations (61%). These gene expression signatures provide insights into novel groups of AML not predicted by traditional studies that impact prognosis and potential therapy.

Identification of novel genes with prognostic value in childhood leukemia using cDNA microarray and quantitative RT-PCR

The aim of this study was to identify genes distinctively expressed or suppressed in childhood leukemia with different prognoses, using cDNA microarray and quantitative reverse transcription-polymerase chain reaction (RT-PCR). The expression levels of the selected genes by cDNA microarray were quantified in primary leukemic blasts from 44 patients (acute lymphoblastic leukemia, 28; acute myelogenous leukemia (AML), 13; transient myeloproliferative disorder, 3). The expression levels of CDKN2C, CRADD, and IGFBP-2 genes were significantly associated with the event-free survival of the patients in AML. The present results suggest that a combination of cDNA microarray and quantitative RT-PCR may be useful to identify novel genes with prognostic value in childhood AML.

c-Myb is an essential downstream target for homeobox-mediated transformation of hematopoietic cells

Abdominal-type HoxA genes in combination with Meis1 are well-documented on-cogenes in various leukemias but it is unclear how they exert their transforming function. Here we used a system of conditional transformation by an inducible mixed lineage leukemia-eleven-nineteen leukemia (MLL-ENL) oncoprotein to overexpress Hoxa9 and Meis1 in primary hematopoietic cells. Arrays identified c-Myb and a c-Myb target (Gstm1) among the genes with the strongest response to Hoxa9/Meis1. c-Myb overexpression was verified by Northern blot and quantitative reverse transcription-polymerase chain reaction (RT-PCR). Also MLL-ENL activated c-Myb through up-regulation of Hoxa9 and Meis1. Consequently, short-term suppression of c-Myb by small inhibitory RNA (siRNA) efficiently inhibited transformation by MLL-ENL but did not impair transformation by transcription factor E2A-hepatic leukemia factor (E2A-HLF). The anti c-Myb siRNA effect was abrogated by coexpression of a c-Myb derivative with a mutated siRNA target site. The introduction of a dominant-negative c-Myb mutant had a similar but weaker effect on MLL-ENL-mediated transformation. Hematopoietic precursors from mice homozygous for a hypo-morphic c-Myb allele were more severely affected and could be transformed neither by MLL-ENL nor by E2A-HLF. Ectopic expression of c-Myb induced a differentiation block but c-Myb alone was not transforming in a replating assay similar to Hoxa9/Meis1. These results suggest that c-Myb is essential but not sufficient for Hoxa9/Meis1 mediated transformation.

PHARMACOGENOMICS OF ACUTE LEUKEMIA

Over the past four decades, treatment of acute leukemia in children has made remarkable progress, from this disease being lethal to now achieving cure rates of 80% for acute lymphoblastic leukemia and 45% for acute myeloid leukemia. This progress is largely owed to the optimization of existing treatment modalities rather than the discovery of new agents. However, the annual number of patients with leukemia who experience relapse after initial therapy remains greater than that of new cases of most childhood cancers. The aim of pharmacogenetics is to develop strategies to personalize medications and tailor treatment regimens to individual patients, with the goal of enhancing efficacy and safety through better understanding of the person's genetic makeup. In this review, we summarize recent pharmacogenomic studies related to the treatment of pediatric acute leukemia. These include work using candidate-gene approaches, as well as genome-wide studies using haplotype mapping and gene expression profiling. These strategies illustrate the promise of pharmacogenomics to further advance the treatment of human cancers, with childhood leukemia serving as a paradigm.

Gene expression profiles in acute myeloid leukemia with common translocations using SAGE

Identification of the specific cytogenetic abnormality is one of the critical steps for classification of acute myeloblastic leukemia (AML) which influences the selection of appropriate therapy and provides information about disease prognosis. However at present, the genetic complexity of AML is only partially understood. To obtain a comprehensive, unbiased, quantitative measure, we performed serial analysis of gene expression (SAGE) on CD15(+) myeloid progenitor cells from 22 AML patients who had four of the most common translocations, namely t(8;21), t(15;17), t(9;11), and inv(16). The quantitative data provide clear evidence that the major change in all these translocation-carrying leukemias is a decrease in expression of the majority of transcripts compared with normal CD15(+) cells. From a total of 1,247,535 SAGE tags, we identified 2,604 transcripts whose expression was significantly altered in these leukemias compared with normal myeloid progenitor cells. The gene ontology of the 1,110 transcripts that matched known genes revealed that each translocation had a uniquely altered profile in various functional categories including regulation of transcription, cell cycle, protein synthesis, and apoptosis. Our global analysis of gene expression of common translocations in AML can focus attention on the function of the genes with altered expression for future biological studies as well as highlight genes/pathways for more specifically targeted therapy.

Comparison of mRNA abundance quantified by gene expression profiling and percentage of positive cells using immunophenotyping for diagnostic antigens in acute and chronic leukemias

BACKGROUND

Microarray analysis is considered a future diagnostic tool in leukemias. Whereas data accumulate on specific gene expression patterns in biologically defined leukemia entities, data on the correlation between flow cytometrically determined protein expression, which are essential in the diagnostic setting today, and microarray results are limited.

METHODS

The results obtained by microarray analysis were compared using the Affymetrix GeneChip HG-U133 system in parallel with flow cytometric findings of 36 relevant targets in 814 patients with newly diagnosed acute and chronic leukemias as well as in normal bone marrow samples.

RESULTS

In a total of 21,581 individual comparisons between signal intensities obtained by microarray analysis and percentages of positive cell as determined by flow cytometry, coefficients of correlation in the range of 0.171 to 0.807 were obtained. In particular, the degree of correlation was high in the following genes critical in the diagnostic setting: CD4, CD8, CD13 (ANPEP), CD33, CD23 (FCER2), CD64 (FCGR1A), CD117 (KIT), CD34, MPO, CD20 (MS4A1), CD7 (range of r, 0.589-0.807).

CONCLUSIONS

The present data prove the high degree of correlation between findings obtained by microarray analysis and flow cytometry. They are in favor of a future application of the microarray technology as a robust diagnostic tool in leukemias.

Discovering causes and cures for cancer from gene expression analysis

Tumorigenesis is governed by a series of complex genetic and epigenetic changes. Both mechanisms can result in either the silencing or aberrant expression of messages in a cell. Gene expression profiling techniques such as the serial analysis of gene expression (SAGE) or microarray analysis can provide global overviews of these changes, as well identify key genes and pathways involved in this process. This review outlines the current roles of these techniques in cancer research, and how they may contribute to finding not only mechanisms of this disease, but potential targets for therapy.

The Mark Coventry Award: white blood cell gene expression: a new approach toward the study and diagnosis of infection

We introduce a new genomic approach toward the study and diagnosis of infection. Our purpose is to show that synovial fluid white blood cells express a gene expression "signature" that differentiates septic from aseptic inflammation. Synovial fluid was aspirated from patients with acute Staphylococcus aureus infections or acute gout of the knee. Differential cell counts included predominantly neutrophils in all aspirates. Ribonucleic acid was isolated from the synovial-fluid white blood cells and was analyzed on the Affymetrix U133A GeneChip. The neutrophils from a patient whose knee is infected with Staphylococcus aureus can be distinguished from the neutrophils found in gout by nature of their differential gene expression. There are 1615 genes that have an expression level that is significantly different between the groups. The 124 most significant differences are in genes from immune pathways including the interleukin pathway, the tumor necrosis factor pathway, and the antibacterial response. The neutrophils at a site of infection (Staphylococcus aureus) express different genes than the neutrophils at a site of aseptic inflammation (gout). To our knowledge, this is the first in vivo demonstration of this principle. The differences in neutrophil gene expression may be used to develop simple laboratory tests that distinguish the causes of inflammation in a total joint arthroplasty.

LEVEL OF EVIDENCE

Diagnostic study, Level II-1. See the Guidelines for Authors for a complete description of levels of evidence.

Towards a pathogenesis-oriented therapy of acute myeloid leukemia

Genetic and molecular techniques have provided increasing insights into the biology of acute myeloid leukemia (AML). These investigations showed that AML is not a homogeneous disease but a heterogeneous group of biologically different subentities. These subentities are currently primarily defined by cytogenetics by which three main subgroups can be discriminated: AML with balanced translocations, AML with unbalanced aberrations and AML without cytogenetically detectable aberrations. Within the latter group molecular alterations are identified in more than half of cases such as NPM mutations, FLT3 mutations, MLL duplications and mutations of CEBP-alpha. The clinical meaning of these findings is illustrated by substantial differences in response to therapy and long-term outcome. As demonstrated by the recent multicenter trial of the German AML Cooperative Group (AMLCG) and other studies intensification of induction therapy may improve the results in distinct subtypes but fails to do so in others. Therefore, new strategies need to be explored which incorporate the knowledge about the biology of AML to develop biology adapted treatment strategies. This process has just begun and is predominantly determined by the availability of new agents and their evaluation in clinical phase I and II studies. A variety of targets are currently explored and some trials have yielded promising results already. The step towards a biology adapted treatment of AML is long and requires the combined efforts of researchers, clinicians and the pharmaceutical industry. The first steps towards this goal have been taken and give rise to the hope for more effective and more specific therapies of AML.

Gene expression profiling in acute myeloid leukemia

Over the last decades, significant advances have been made in the knowledge and treatment of acute myeloid leukemia (AML). The WHO has recognized this new information by incorporating into its classification morphologic, immunophenotypic, genetic, and clinical features in an attempt to define biologically and clinically relevant entities. Nevertheless, well-defined cytogenetic subgroups exhibit considerable heterogeneity, and in many AML subtypes the pathogenic event is still not known. A classification system based on the underlying molecular pathogenetic abnormalities would be ideal, but such detailed knowledge is not yet available. Novel approaches in genomics, such as surveying the expression levels of thousands of genes in parallel using DNA microarray technology, open possibilities to further refine the studies on AML. Today, gene expression profiling in AML is becoming well established and has already been proven to be valuable in diagnosing different cytogenetic subtypes, discovering novel AML subclasses, and predicting clinical outcome. Recently, gene expression profiling studies in AML showed a remarkable level of concordance in findings, which may ultimately lead to an increasingly refined molecular taxonomy. While many challenges remain to be overcome, a combination of gene expression profiling with other microarray-based applications, high-throughput mutational analyses and proteomic approaches will not only significantly contribute to the classification and therapeutic decision making of AML, but also give important insights into the true pathobiologic nature of this type of leukemia.

Gene Expression Profiles of B-lineage Adult Acute Lymphocytic Leukemia Reveal Genetic Patterns that Identify Lineage Derivation and Distinct Mechanisms of Transformation

PURPOSE

To characterize gene expression signatures in acute lymphocytic leukemia (ALL) cells associated with known genotypic abnormalities in adult patients.

EXPERIMENTAL DESIGN

Gene expression profiles from 128 adult patients with newly diagnosed ALL were characterized using high-density oligonucleotide microarrays. All patients were enrolled in the Italian GIMEMA multicenter clinical trial 0496 and samples had >90% leukemic cells. Uniform phenotypic, cytogenetic, and molecular data were also available for all cases.

RESULTS

T-lineage ALL was characterized by a homogeneous gene expression pattern, whereas several subgroups of B-lineage ALL were evident. Within B-lineage ALL, distinct signatures were associated with ALL1/AF4 and E2A/PBX1 gene rearrangements. Expression profiles associated with ALL1/AF4 and E2A/PBX1 are similar in adults and children. BCR/ABL+ gene expression pattern was more heterogeneous and was most similar to ALL without known molecular rearrangements. We also identified a set of 83 genes that were highly expressed in leukemia blasts from patients without known molecular abnormalities who subsequently relapsed following therapy. Supervised analysis of kinase genes revealed a high-level FLT3 expression in a subset of cases without molecular rearrangements. Two other kinases (PRKCB1 and DDR1) were highly expressed in cases without molecular rearrangements, as well as in BCR/ABL-positive ALL.

CONCLUSIONS

Genomic signatures are associated with phenotypically and molecularly well defined subgroups of adult ALL. Genomic profiling also identifies genes associated with poor outcome in cases without molecular aberrations and specific genes that may be new therapeutic targets in adult ALL.

Modern diagnostics in acute leukemias

Acute leukemias are a heterogeneous group of diseases. The different subtypes are characterized by certain clinical features and specific laboratory findings. Large clinical trials have confirmed the important impact of the underlying biology of each subtype for clinical outcome. Improvements in patient's treatment resulting in better survival rates are closely linked to the biological understanding of the disease subtypes, which is assessed by specific diagnostic approaches. Thus, several diagnostic techniques are mandatory at diagnosis for classification and for individual therapeutic decisions. Furthermore they are also needed for follow up studies focusing especially on minimal residual disease (MRD) to guide further treatment decisions based on the response of the disease to given treatment protocols. Only by using a comprehensive diagnostic panel including cytomorphology, cytochemistry, multiparameter flow cytometry (MFC), cytogenetics, fluorescence in situ hybridization (FISH) and molecular genetic methods the correct diagnosis in acute leukemias can be established today. The results serve as a mandatory prerequisite for individual treatment strategies and for the evaluation of treatment response using especially newly defined and highly specific MRD markers.

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.

CD34 expression in native human acute myelogenous leukemia blasts: differences in CD34 membrane molecule expression are associated with different gene expression profiles

BACKGROUND

The stem cell marker CD34 is expressed by leukemia blasts only for a subset of patients with acute myelogenous leukemia (AML). It is still controversial as to whether CD34 expression (defined as at least 10-20% positive cells) has any prognostic effect in patients with AML who receive intensive chemotherapy. The present study investigated whether gene expression profiling could be used to further subclassify CD34(+) AML cell populations.

METHODS

AML blasts derived from 25 patients were examined; these patients were randomly selected from a larger consecutive group of patients. CD34 protein expression was determined by flow cytometry and expressed as the percentage of positive cells. Gene expression profiles were determined by complementary DNA microarrays.

RESULTS

By unsupervised hierarchical clustering our patients could be grouped into two or three major subsets depending on the methodologic approach before clustering analysis (filtering or flooring of data, respectively). However, both approaches identified a cluster characterized by high gene expression and membrane molecule level of CD34. When using the floored expression profiles, the patient cluster characterized by increased CD34 gene expression was also characterized by a high percentage of CD34(+) cells (median 82%, range 56-100%) compared with the two other major clusters (median 19%, range <1-55%), but three of four outpatients also showed a high percentage of CD34(+) cells.

CONCLUSION

A major proportion of patients with AML and high CD34 expression (usually >80% CD34(+) cells; nearly all patients had >50% positive cells) showed similarities in gene expression profile. In contrast, patients with lower CD34 expression often had a profile similar to those of patients regarded as CD34(-) according to conventional criteria. Our results suggest that the possible prognostic effect of CD34 expression should be reevaluated in clinical studies using additional or alternative cutoff values to describe CD34 expression.

Global approach to the diagnosis of leukemia using gene expression profiling

Accurate diagnosis and classification of leukemias are the bases for the appropriate management of patients. The diagnostic accuracy and efficiency of present methods may be improved by the use of microarrays for gene expression profiling. We analyzed gene expression profiles in 937 bone marrow and peripheral blood samples from 892 patients with all clinically relevant leukemia subtypes and from 45 nonleukemic controls by U133A and U133B GeneChip arrays. For each subgroup, differentially expressed genes were calculated. Class prediction was performed using support vector machines. Prediction accuracy was estimated by 10-fold cross-validation and was assessed for robustness in a 100-fold resampling approach using randomly chosen test sets consisting of one third of the samples. Applying the top 100 genes of each subgroup, an overall prediction accuracy of 95.1% was achieved that was confirmed by resampling (median, 93.8%; 95% confidence interval, 91.4%-95.8%). In particular, acute myeloid leukemia (AML) with t(15;17), AML with t(8;21), AML with inv(16), chronic lymphatic leukemia (CLL), and pro–B-cell acute lymphoblastic leukemia (pro–B-ALL) with t(11q23) were classified with 100% sensitivity and 100% specificity. Accordingly, cluster analysis completely separated all 13 subgroups analyzed. Gene expression profiling can predict all clinically relevant subentities of leukemia with high accuracy.

Prospective gene expression analysis accurately subtypes acute leukaemia in children and establishes a commonality between hyperdiploidy and t(12;21) in acute lymphoblastic leukaemia

We have prospectively analysed and correlated the gene expression profiles of children presenting with acute leukaemia to the Royal London and Great Ormond Street Hospitals with morphological diagnosis, immunophenotype and karyotype. Total RNA extracted from freshly sorted blast cells was obtained from 84 lymphoblastic [acute lymphoblastic leukaemia (ALL)], 20 myeloid [acute myeloid leukaemia (AML)] and three unclassified acute leukaemias and hybridised to the high density Affymetrix U133A oligonucleotide array. Analysis of variance and significance analysis of microarrays was used to identify discriminatory genes. A novel 50-gene set accurately identified all patients with ALL and AML and predicted for a diagnosis of AML in three patients with unclassified acute leukaemia. A unique gene set was derived for each of eight subtypes of acute leukaemia within our data set. A common profile for children with ALL with an ETV6-RUNX1 fusion, amplification or deletion of ETV6, amplification of RUNX1 or hyperdiploidy with an additional chromosome 21 was identified. This suggests that these rearrangements share a commonality in biological pathways that maintains the leukaemic state. The gene TERF2 was most highly expressed in this group of patients. Our analyses demonstrate that not only is microarray analysis the single most effective tool for the diagnosis of acute leukaemias of childhood but it has the ability to identify unique biological pathways. To further evaluate its prognostic value it needs to be incorporated into the routine diagnostic analysis for large-scale clinical trials in childhood acute leukaemias.

New insights into MLL gene rearranged acute leukemias using gene expression profiling: shared pathways, lineage commitment, and partner genes

Rearrangements of the MLL gene occur in both acute lymphoblastic and acute myeloid leukemias (ALL, AML). This study addressed the global gene expression pattern of these two leukemia subtypes with respect to common deregulated pathways and lineage-associated differences. We analyzed 73 t(11q23)/MLL leukemias in comparison to 290 other acute leukemias and demonstrate that 11q23 leukemias combined are characterized by a common specific gene expression signature. Additionally, in unsupervised and supervised data analysis algorithms, ALL and AML cases with t(11q23) segregate according to the lineage they are derived from, that is, myeloid or lymphoid, respectively. This segregation can be explained by a highly differing transcriptional program. Through the use of novel biological network analyses, essential regulators of early B cell development, PAX5 and EBF, were shown to be associated with a clear B-lineage commitment in lymphoblastic t(11q23)/MLL leukemias. Also, the influence of the different MLL translocation partners on the transcriptional program was directly assessed. Interestingly, gene expression profiling did not reveal a clear distinct pattern associated with one of the analyzed partner genes. Taken together, the identified molecular expression pattern of MLL fusion gene samples and biological networks revealed new insights into the aberrant transcriptional program in 11q23/MLL leukemias.

Children and adults with acute lymphoblastic leukaemia have similar gene expression profiles

OBJECTIVES

To compare the gene expression pattern in children and adults with acute lymphoblastic leukaemia (ALL) in order to improve our understanding of the difference in disease biology and prognosis.

METHODS

The gene expression profiles in diagnostic samples from 29 children and 15 adults with ALL were analysed using the oligonucleotide chip Hu95ver2a, produced by Affymetrix.

RESULTS

Unsupervised hierarchical cluster analysis revealed that, in spite of differences in outcome, patients clustered irrespective of age, first by T-cell or B-precursor immunophenotype, and second by cytogenetic changes within the B-precursor group. The expression pattern analysis allowed the reclassification of some samples into the proper cytogenetic group. We also showed that separate clustering of samples with the BCR/ABL translocation could be explained by different breakpoint regions in the BCR. No significant difference in gene expression was observed between samples with and without CDKN2A deletion within the B-precursor group. Analysis of different age groups revealed a similarity in expression profiles when infants with the MLL translocation and adults over 40 yr of age were compared irrespective of karyotype.

CONCLUSIONS

In spite of the difference in clinical outcome, the gene expression pattern in children and adults with ALL is very similar and is primarily dependent on immunophenotype and cytogenetic aberrations. However, when age groups are compared, the expression patterns of infants and adults over 40 show a remarkable similarity.

Pattern robustness of diagnostic gene expression signatures in leukemia

Microarray technology has been proposed as an addition to the methods in current use for diagnosing leukemia. Before a new technology can be used in a diagnostic setting, the method has to be shown to produce robust results. It is known that, given the technical aspects of specimen sampling and target preparation, global gene expression patterns can change dramatically. Various parameters such as RNA degradation, shipment time, sample purity, and patient age can principally influence measured gene expression. However, thus far, no information has been available on the robustness of a diagnostic gene expression signature. We demonstrate here that for a subset of acute leukemia, expression profiling is applicable in a diagnostic setting, considering various influencing parameters. With the use of a set of differentially expressed genes, that is, a diagnostic gene expression signature, four genetically defined acute myeloid leukemia subtypes with recurrent chromosomal aberrations can clearly be identified. In addition, we show that preparation by different operators and using different sample-handling procedures did not impair the robustness of diagnostic expression signatures. In conclusion, our results provide additional support for the applicability of microarrays in a diagnostic setting, and we have been encouraged to enroll patients in a prospective study in which microarrays will be tested as an additional routine diagnostic method in parallel with standard diagnostic procedures.

Global gene expression as a function of germline genetic variation

Common, functional, germline genetic polymorphisms have been associated with clinical cancer outcomes. Little attention has been paid to the potential phenotypic consequences of germline genetic variation on downstream genes. We determined the germline status of 16 well-characterized functional polymorphisms in 126 children with newly diagnosed acute lymphoblastic leukemia (ALL). We assessed whether global gene expression profiles of diagnostic ALL blasts from the same patients differed by these germline polymorphic genotypes. Gene expression values were adjusted for ALL-subtype-specific patterns. Of the 16 loci, only the UGT1A1 promoter repeat polymorphism [A(TA)nTAA] (UGT1A1*28) and GSTM1 deletion were significant predictors of global gene expression in a supervised approach, which divided patients based on their germline genotypes [UGT1A1: 124 probe sets, false discovery rate (FDR)=13%, P< or =0.0031; GSTM1: 112 probe sets, FDR=42.5%, P< or =0.0084]. Genes whose expression distinguished the UGT1A1 (TA) 7/7 genotype from the other UGT1A1 genotypes included HDAC1, RELA and SLC2A1; those that distinguished the GSTM1 null genotype from non-null genotype included NBS1 and PRKR. In an unsupervised approach, the gene expression profiles using the entire array delineated two major clusters of patients. The only germline genotype frequency that differed between the two clusters was UGT1A1 (P=0.002; Fisher's exact test). Although their expression is limited to specific tissues, both GSTM1 and UGT1A1 are involved in the conjugation (and thus transport, excretion and lipophilicity) of a broad range of endobiotics and xenobiotics, which could plausibly have consequences for gene expression in different tissues.

Gene expression profile reveals deregulation of genes with relevant functions in the different subclasses of acute myeloid leukemia

Bone marrow samples from 43 adult patients with de novo diagnosed acute myeloid leukemia (AML)--10 acute promyelocytic leukemias (APL) with t(15;17), four AML with inv(16), seven monocytic leukemias and 22 nonmonocytic leukemias--were analyzed using high-density oligonucleotide microarrays. Hierarchical clustering analysis segregated APL, AML with inv(16), monocytic leukemias and the remaining AML into separate groups. A set of only 21 genes was able to assign AML to one of these three classes: APL, inv(16) and other AML subtype without a specific translocation. Quantitative RT-PCR performed for 18 out of these predictor genes confirmed microarray results. APL expressed high levels of FGF13 and FGFR1 as well as two potent angiogenic factors, HGF and VEGF. AML with inv(16) showed an upregulation of MYH11 and a downregulation of a gene encoding a core-binding factor protein, RUNX3. Genes involved in cell adhesion represented the most altered functional category in monocytic leukemias. Two major groups emerged from the remaining 22 AML: cluster A with 10 samples and cluster B with 12. All the eight leukemias that were either refractory to treatment or that relapsed afterwards were assigned to cluster B. In the latter cluster, CD34 upregulation and serine proteases downregulation is consistent with a maturation arrest and lack of granulocytic differentiation.

Identification of new classes among acute myelogenous leukaemias with normal karyotype using gene expression profiling

Conventional cytogenetic analysis currently stratifies acute myelogenous leukaemia (AML) into prognostically relevant groups. However, approximately 50% of adult AMLs have normal cytogenetics (NC-AMLs), and represent a heterogeneous and poorly understood group. We analysed gene expression in 55 AML samples including 53 cases from adult patients with NC-AML (n = 36), trisomy 8, t(15;17), t(8;21), t(11;19), 7q deletion, and two cell lines using 9000-gene DNA microarrays. Global hierarchical clustering showed that NC-AMLs are a heterogeneous group. Supervised analysis distinguished two subgroups of NC-AML: one subgroup constituted a homogeneous NC cluster ('pure NC-AML'), and the other NC-AMLs were close to the AML cases with translocations ('translocation like'). Gene expression signatures were also derived for patients with trisomy 8, as well as FLT3 and MLL gene duplications. Importantly, samples from 24 NC-AML patients who could be evaluated for clinical outcome were analysed. In all, 43 genes that discriminated two classes of patients with significantly different prognosis were identified. The poor prognosis class contained a majority of 'pure NC-AMLs', whereas the 'translocation-like' AMLs were in the good prognosis class. Discriminator genes included genes involved in drug resistance (TOP2B), protein transport (MTX2, SLC35A2), and cell signalling (MAPK1, PRKAB2). Our results demonstrate the transcriptional heterogeneity of NC-AMLs, and suggest the existence of 'translocation-like' NC-AMLs and of a gene expression signature that may predict response to chemotherapy.

C-type lectin-like molecule-1: a novel myeloid cell surface marker associated with acute myeloid leukemia

Acute myeloid leukemia (AML) has a poor prognosis due to treatment-resistant relapses. A humanized anti-CD33 antibody (Mylotarg) showed a limited response rate in relapsed AML. To discover novel AML antibody targets, we selected a panel of single chain Fv fragments using phage display technology combined with flow cytometry on AML tumor samples. One selected single chain Fv fragment broadly reacted with AML samples and with myeloid cell lineages within peripheral blood. Expression cloning identified the antigen recognized as C-type lectin-like molecule-1 (CLL-1), a previously undescribed transmembrane glycoprotein. CLL-1 expression was analyzed with a human anti-CLL-1 antibody that was generated from the single chain Fv fragment. CLL-1 is restricted to the hematopoietic lineage, in particular to myeloid cells present in peripheral blood and bone marrow. CLL-1 is absent on uncommitted CD34(+)/CD38(-) or CD34(+)/CD33(-) stem cells and present on subsets of CD34(+)/CD38(+) or CD34(+)/CD33(+) progenitor cells. CLL-1 is not expressed in any other tissue. In contrast, analysis of primary AMLs demonstrated CLL-1 expression in 92% (68 of 74) of the samples. As an AML marker, CLL-1 was able to complement CD33, because 67% (8 of 12) of the CD33(-) AMLs expressed CLL-1. CLL-1 showed variable expression (10-60%) in CD34(+) cells in chronic myelogenous leukemia and myelodysplastic syndrome but was absent in 12 of 13 cases of acute lymphoblastic leukemia. The AML reactivity combined with the restricted expression on normal cells identifies CLL-1 as a novel potential target for AML treatment.

Gene expression profiling in acute myeloid leukemia

PURPOSE OF REVIEW

This review deals with the emerging promises of gene expression profiling (GEP) and the currently accumulating knowledge about the classification and the discovery of novel disease entities in clinical acute myeloid leukemia (AML).

RECENT FINDINGS

Gene expression profiling studies in AML have shown that known and novel classes of disease can be recognized by unsupervised analyses. Prognostically informative molecular signatures can be deduced. Supervised analyses show that particular clinically relevant subsets of AML can be predicted with high accuracy with minimal sets of genes.

SUMMARY

The AML GEP studies published to date show a remarkable level of concordance in findings, especially for similar GEP platforms. This confirms the robustness of the methodology and the promise for future applicability of GEP in clinical diagnostics. For the time being, certain technical hurdles remain to be overcome. These relate, for instance, to the conversion of data between different GEP platforms, the effect of differences between various statistical clustering methods, and the still incomplete understanding of the effect of biologic (eg, morphology) and genetic factors on the expression signature. GEP analyses, perhaps in combination with high-throughput mutation analysis and proteomic approaches, may ultimately result in the establishment of a comprehensive diagnostic approach that will yield a key to the precise pathobiologic nature of AML.

AML M3 and AML M3 variant each have a distinct gene expression signature but also share patterns different from other genetically defined AML subtypes

Acute promyelocytic leukemia (APL) with t(15;17) appears in two phenotypes: AML M3, with abnormal promyelocytes showing heavy granulation and bundles of Auer rods, and AML M3 variant (M3v), with non- or hypogranular cytoplasm and a bilobed nucleus. We investigated the global gene expression profiles of 35 APL patients (19 AML M3, 16 AML M3v) by using high-density DNA-oligonucleotide microarrays. First, an unsupervised approach clearly separated APL samples from other AMLs characterized genetically as t(8;21) (n = 35), inv(16) (n = 35), or t(11q23)/MLL (n = 35) or as having a normal karyotype (n = 50). Second, we found genes with functional relevance for blood coagulation that were differentially expressed between APL and other AMLs. Furthermore, a supervised pairwise comparison between M3 and M3v revealed differential expression of genes that encode for biological functions and pathways such as granulation and maturation of hematologic cells, explaining morphologic and clinical differences. Discrimination between M3 and M3v based on gene signatures showed a median classification accuracy of 90% by use of 10-fold CV and support vector machines. Additional molecular mutations such as FLT3-LM, which were significantly more frequent in M3v than in M3 (P < 0.0001), may partly contribute to the different phenotypes. However, linear regression analysis demonstrated that genes differentially expressed between M3 and M3v did not correlate with FLT3-LM.

Expression profiling of murine acute promyelocytic leukemia cells reveals multiple model-dependent progression signatures

Leukemia results from the expansion of self-renewing hematopoietic cells that are thought to contain mutations that contribute to disease initiation and progression. Studies of the gene expression profiles of human acute myeloid leukemia samples has allowed their classification based on the presence of translocations and French-American-British subtypes, but it is not yet clear whether their molecular signatures reflect the initiating mutations or mutations acquired during progression. To begin to address this question, we examined the expression profiles of normal murine promyelocyte-enriched samples, nontransformed murine promyelocytes expressing human promyelocytic leukemia-retinoic acid receptor alpha (PML-RARalpha) fusion gene, and primary acute promyelocytic leukemia cells. The expression profile of nontransformed cells expressing PML-RARalpha was remarkably similar to that of wild-type promyelocytes. In contrast, the expression profiles of fully transformed cells from three acute promyelocytic leukemia model systems were all different, suggesting that the expression signature of acute promyelocytic leukemia cells reflects the genetic changes that contributed to progression. To further evaluate these progression events, we compared two high-penetrance acute promyelocytic leukemia models that both commonly acquire an interstitial deletion of chromosome 2 during progression. The two models exhibited distinct gene expression profiles, suggesting that the dominant molecular signatures of murine acute promyelocytic leukemia can be influenced by several independent progression events.

DNA Microarrays in the Diagnosis and Management of Acute Lymphoblastic Leukemia

The significant progress in the treatment of acute lymphoblastic leukemia (ALL) experienced over the last 3 decades has been driven mainly by the empirical combination of antileukemic drugs in highly intensive therapies. Further progress in the management of ALL is currently limited, however, by our incomplete understanding of the molecular pathways involved in leukemia pathogenesis and by the lack of useful prognostic markers for most patients. The recent development of microarray technology, which allows the simultaneous analysis of gene expression levels for thousands of transcripts, has accelerated significantly the rate of progress in our understanding of the molecular basis of ALL. During the last few years, analysis of ALL samples with DNA arrays has facilitated the recognition of molecularly distinct leukemia groups, advanced our knowledge of the mechanisms of sensitivity and resistance to chemotherapy, generated novel prognostic prediction tools, and identified new targets for the development of molecularly tailored antileukemic agents. Thus, the introduction of microarray gene expression profiling has opened the opportunity for accelerated progress in the diagnosis and therapy of ALL, which will ultimately result in the development of novel highly effective and less toxic treatments for this disease.

Gene expression profiling of pediatric acute myelogenous leukemia

Contemporary treatment of pediatric acute myeloid leukemia (AML) requires the assignment of patients to specific risk groups. To explore whether expression profiling of leukemic blasts could accurately distinguish between the known risk groups of AML, we analyzed 130 pediatric and 20 adult AML diagnostic bone marrow or peripheral blood samples using the Affymetrix U133A microarray. Class discriminating genes were identified for each of the major prognostic subtypes of pediatric AML, including t(15;17)[PML-RARα], t(8;21)[AML1-ETO], inv16 [CBFβ-MYH11], MLL chimeric fusion genes, and cases classified as FAB-M7. When subsets of these genes were used in supervised learning algorithms, an overall classification accuracy of more than 93% was achieved. Moreover, we were able to use the expression signatures generated from the pediatric samples to accurately classify adult de novo AMLs with the same genetic lesions. The class discriminating genes also provided novel insights into the molecular pathobiology of these leukemias. Finally, using a combined pediatric data set of 130 AMLs and 137 acute lymphoblastic leukemias, we identified an expression signature for cases with MLL chimeric fusion genes irrespective of lineage. Surprisingly, AMLs containing partial tandem duplications of MLL failed to cluster with MLL chimeric fusion gene cases, suggesting a significant difference in their underlying mechanism of transformation.

PRDX4, a member of the peroxiredoxin family, is fused to AML1 (RUNX1) in an acute myeloid leukemia patient with a t(X;21)(p22;q22)

The AML1 gene (also known as RUNX1) at 21q22 codes for core binding factor (CBF) alpha, which forms a heterodimer with CBF beta that acts as a transcriptional activating factor. CBF is a critical regulator in the generation and differentiation of definitive hematopoietic stem cells and is frequently disrupted in leukemia through chromosome translocations. We cloned a novel AML1 partner gene, PRDX4, in an X;21 translocation in a 74-year-old male patient diagnosed with acute myeloid leukemia-M2. Chromosome analysis detected a t(X;21)(p22;q22) as the sole abnormality in bone marrow samples. The involvement of AML1 was confirmed by fluorescence in situ hybridization studies. Using 3' RACE-PCR, we cloned a fusion between exon 5 of AML1 and exon 2 of PRDX4. RT-PCR confirmed the fusion and detected another fusion between exon 6 of AML1 and exon 2 of PRDX4, indicating alternative splicing of exon 6 of AML1 in the fusion transcripts. PRDX4 is one of six peroxiredoxin-family genes that are highly conserved in eukaryotes and prokaryotes and are ubiquitously expressed. Peroxiredoxin genes exhibit thioredoxin-dependent peroxidase activity and have been implicated in a number of other cellular functions such as cell proliferation and differentiation. PRDX4 plays a regulatory role in the activation of the transcription factor NF-kappaB and is significantly down-regulated in acute promyelocytic leukemia. This is the first example of antioxidant enzyme involvement in a chromosome translocation in leukemia.

Unanswered questions in acute myeloid leukaemia

Acute myeloid leukaemia (AML) is a heterogeneous disease that presents with a range of morphological, cytogenetic, immunophenotypic, and biomolecular features. Over the past 20 years, application of new cytogenetic and molecular techniques has greatly improved knowledge of the pathophysiology of AML, resulting in new potential therapeutic applications. However, the results of current therapy are still unsatisfactory, especially in patients who have adverse prognostic factors at the time of diagnosis. Furthermore, some pivotal questions about the procedures of induction and postinduction therapy of AML remain unanswered, and substantial controversy exists on the optimum therapeutic approach for the disorder.

Mechanism of leukemogenesis by the inv(16) chimeric gene CBFB/PEBP2B-MHY11

Inv(16)(p13q22) is associated with acute myeloid leukemia subtype M4Eo that is characterized by the presence of myelomonocytic blasts and atypical eosinophils. This chromosomal rearrangement results in the fusion of CBFB and MYH11 genes. CBF beta normally interacts with RUNX1 to form a transcriptionally active nuclear complex. The MYH11 gene encodes the smooth muscle myosin heavy chain. The CBF beta-SMMHC fusion protein is capable of binding to RUNX1 and form dimers and multimers through its myosin tail. Previous results from transgenic mouse models show that Cbfb-MYH11 is able to inhibit dominantly Runx1 function in hematopoiesis, and is a key player in the pathogenesis of leukemia. In recent years, molecular and cellular biological studies have led to the proposal of several models to explain the function of CBF beta-SMMHC. In this review, we will first focus our attention on the molecular mechanisms proposed in the recent publications. We will next examine recent gene expression profiling studies on inv(16) leukemia cells. Finally, we will describe a recent study from one of our labs on the identification of cooperating genes for leukemogenesis with CBFB-MYH11.

Gene expression profiling in childhood acute leukemia: progress and perspectives

Recent advances in treatment have transformed childhood acute leukemias into curable diseases. However, 20% to 40% of acute leukemia patients still experience a relapse. Microarrays typically contain thousands of oligonucleotides or complementary DNAs and are rapidly becoming important research tools for the identification of novel classifications of leukemias and lymphomas. Microarray-based identification of several translocations has been performed in acute lymphoblastic leukemia (ALL), leading to the discovery of t(1;19), t(12;21), and 11q23 translocations, and in acute myeloid leukemia (AML), finding t(8;21), inv(16), and t(15;17). Correlations between gene expression profiles and clinical features have been reported in ALL and AML. Recently, it was reported that gene expression profiling can be used to predict the prognosis of childhood acute leukemia. In this report, the recent progress in microarray analysis of childhood acute leukemia is reviewed. Gene expression profiling provides new insights into the biological mechanisms of leukemogenesis and the prognosis of childhood acute leukemia.

Prenatal origin of chromosomal translocations in acute childhood leukemia: implications and future directions

We, and others, have demonstrated an in utero origin for translocations associated with childhood leukemia, with latency periods in some cases exceeding 10 years. The mechanism of generation of most of the translocations is thought to be aberrant repair following abortive apoptosis, rather than V(D)J recombination or exposure to topoisomerase II inhibitors. Folate supplementation may prevent some of the chromosome breakage leading to translocation formation. Translocations t(8;21) and t(12;21) have been shown to occur in the normal population (before birth) at a frequency that is 100-fold greater than the risk of developing the corresponding leukemia. In most instances, additional genetic changes are required for progression to leukemia. Tyrosine kinase receptor (RTK) mutations, which give cells a survival/proliferative advantage, are proposed to act cooperatively with fusion genes, leading to transformation. However, translocations and cooperating RTK mutations have not been identified for all leukemia subtypes, particularly in acute myeloid leukemia. The core binding transcriptional pathway is frequently targeted by translocation in utero. We propose that this pathway is highly sensitive during fetal hematopoiesis and may be targeted by mechanisms other than translocation. For each leukemia subtype it is important to characterize the corresponding leukemic stem cell, which is thought to be the initial target for translocation. This would help to elucidate the molecular pathways involved in the progression from preleukemic clone harboring a translocation to fully disseminated leukemia.

Gene Expression Profiling as a Diagnostic Tool in Acute Myeloid Leukemia

The standard methods for establishing the diagnosis of acute leukemias are cytomorphology and cytochemistry in combination with multiparameter immunophenotyping. Cytogenetics, fluorescence in situ hybridization, and PCR-based assays add important information regarding biologically defined and prognostically relevant subgroups, and allow a comprehensive diagnosis of well-defined subentities. In the clinical setting, a better understanding of the clinical course of distinct, biologically defined disease subtypes is the basis for a selection of disease-specific therapeutic approaches. As knowledge of deregulated pathways in leukemia increases and accelerates the development of new therapeutics, a detailed and comprehensive diagnostic tool is required. Microarray technology, which quantifies gene expression intensities of thousands of genes in a single analysis, has the potential to become an essential tool for the molecular classification of leukemias. It may, therefore, be used as a routine method for diagnostic purposes in the near future. Furthermore, gene expression profiling may also lead to the detection of new biologically defined and clinically relevant subtypes in leukemia and guide therapeutic decision-making in the future.

Pediatric acute lymphoblastic leukemia (ALL) gene expression signatures classify an independent cohort of adult ALL patients

Recent reports support a possible future application of gene expression profiling for the diagnosis of leukemias. However, the robustness of subtype-specific gene expression signatures has to be proven on independent patient samples. Here, we present gene expression data of 34 adult acute lymphoblastic leukemia (ALL) patients (Affymetrix U133A microarrays). Support Vector Machines (SVMs) were applied to stratify our samples based on given gene lists reported to predict MLL, BCR-ABL, and T-ALL, as well as MLL and non-MLL gene rearrangement positive pediatric ALL. In addition, seven other B-precursor ALL cases not bearing t(9;22) or t(11q23)/MLL chromosomal aberrations were analyzed. Using top differentially expressed genes, hierarchical cluster and principal component analyses demonstrate that the genetically more heterogeneous B-precursor ALL samples intercalate with BCR-ABL-positive cases, but were clearly distinct from T-ALL and MLL profiles. Similar expression signatures were observed for both heterogeneous B-precursor ALL and for BCR-ABL-positive cases. As an unrelated laboratory, we demonstrate that gene signatures defined for childhood ALL were also capable of stratifying distinct subtypes in our cohort of adult ALL patients. As such, previously reported gene expression patterns identified by microarray technology are validated and confirmed on truly independent leukemia patient samples.

Gene expression profiling as a tool for the diagnosis of acute leukemias

The standard methods to diagnose leukemia are cytomorphology and, in some cases, histology, which both are supplemented by cytochemistry and multiparameter immunophenotyping. Cytogenetics, fluorescence in situ hybridisation (FISH), and polymerase chain reaction (PCR) assays add important information and allow comprehensive diagnosis of well-defined subentities today. In the clinic, better understanding of the course of distinct, biologically defined disease subtypes is the basis for a selection of specific therapeutic approaches. As knowledge on deregulated pathways in leukemia accelerates the development of new therapeutics, a detailed and comprehensive diagnostic tool is required. The microarray technology that quantifies gene expression intensities of thousands of genes in a single analysis has the potential to become essential for the molecular classification of leukemias. Microarrays may be used routinely for diagnostic purposes in the near future. Gene expression profiling should also lead to the detection of new biological and clinically relevant subtypes in leukemia and therefore guide therapeutic decisions.

Pediatric acute lymphoblastic leukemia

The outcome for children with acute lymphoblastic leukemia (ALL) has improved dramatically with current therapy resulting in an event free survival exceeding 75% for most patients. However significant challenges remain including developing better methods to predict which patients can be cured with less toxic treatment and which ones will benefit from augmented therapy. In addition, 25% of patients fail therapy and novel treatments that are focused on undermining specifically the leukemic process are needed urgently. In Section I, Dr. Carroll reviews current approaches to risk classification and proposes a system that incorporates well-established clinical parameters, genetic lesions of the blast as well as early response parameters. He then provides an overview of emerging technologies in genomics and proteomics and how they might lead to more rational, biologically based classification systems. In Section II, Drs. Mary Relling and Stella Davies describe emerging findings that relate to host features that influence outcome, the role of inherited germline variation. They highlight technical breakthroughs in assessing germline differences among patients. Polymorphisms of drug metabolizing genes have been shown to influence toxicity and the best example is the gene thiopurine methyltransferase (TPMT) a key enzyme in the metabolism of 6-mercaptopurine. Polymorphisms are associated with decreased activity that is also associated with increased toxicity. The role of polymorphisms in other genes whose products play an important role in drug metabolism as well as cytokine genes are discussed. In Sections III and IV, Drs. James Downing and Cheryl Willman review their findings using gene expression profiling to classify ALL. Both authors outline challenges in applying this methodology to analysis of clinical samples. Dr. Willman describes her laboratory's examination of infant leukemia and precursor B-ALL where unsupervised approaches have led to the identification of inherent biologic groups not predicted by conventional morphologic, immunophenotypic and cytogenetic variables. Dr. Downing describes his results from a pediatric ALL expression database using over 327 diagnostic samples, with 80% of the dataset consisting of samples from patients treated on a single institutional protocol. Seven distinct leukemia subtypes were identified representing known leukemia subtypes including: BCR-ABL, E2A-PBX1, TEL-AML1, rearrangements in the MLL gene, hyperdiploid karyotype (i.e., > 50 chromosomes), and T-ALL as well as a new leukemia subtype. A subset of genes have been identified whose expression appears to be predictive of outcome but independent verification is needed before this type of analysis can be integrated into treatment assignment. Chemotherapeutic agents kill cancer cells by activating apoptosis, or programmed cell death. In Section V, Dr. John Reed describes major apoptotic pathways and the specific role of key proteins in this response. The expression level of some of these proteins, such as BCL2, BAX, and caspase 3, has been shown to be predictive of ultimate outcome in hematopoietic tumors. New therapeutic approaches that modulate the apoptotic pathway are now available and Dr. Reed highlights those that may be applicable to the treatment of childhood ALL.