Molecular characterization of acute leukemias by use of microarray technology

Gene expression profiling unveils the temporal dynamics of CIGB-300-regulated transcriptome in AML cell lines

BACKGROUND

Protein kinase CK2 activity is implicated in the pathogenesis of various hematological malignancies like Acute Myeloid Leukemia (AML) that remains challenging concerning treatment. This kinase has emerged as an attractive molecular target in therapeutic. Antitumoral peptide CIGB-300 blocks CK2 phospho-acceptor sites on their substrates but it also binds to CK2α catalytic subunit. Previous proteomic and phosphoproteomic experiments showed molecular and cellular processes with relevance for the peptide action in diverse AML backgrounds but earlier transcriptional level events might also support the CIGB-300 anti-leukemic effect. Here we used a Clariom S HT assay for gene expression profiling to study the molecular events supporting the anti-leukemic effect of CIGB-300 peptide on HL-60 and OCI-AML3 cell lines.

RESULTS

We found 183 and 802 genes appeared significantly modulated in HL-60 cells at 30 min and 3 h of incubation with CIGB-300 for p < 0.01 and FC >  = │1.5│, respectively; while 221 and 332 genes appeared modulated in OCI-AML3 cells. Importantly, functional enrichment analysis evidenced that genes and transcription factors related to apoptosis, cell cycle, leukocyte differentiation, signaling by cytokines/interleukins, and NF-kB, TNF signaling pathways were significantly represented in AML cells transcriptomic profiles. The influence of CIGB-300 on these biological processes and pathways is dependent on the cellular background, in the first place, and treatment duration. Of note, the impact of the peptide on NF-kB signaling was corroborated by the quantification of selected NF-kB target genes, as well as the measurement of p50 binding activity and soluble TNF-α induction. Quantification of CSF1/M-CSF and CDKN1A/P21 by qPCR supports peptide effects on differentiation and cell cycle.

CONCLUSIONS

We explored for the first time the temporal dynamics of the gene expression profile regulated by CIGB-300 which, along with the antiproliferative mechanism, can stimulate immune responses by increasing immunomodulatory cytokines. We provided fresh molecular clues concerning the antiproliferative effect of CIGB-300 in two relevant AML backgrounds.

Scalable Prediction of Acute Myeloid Leukemia Using High-Dimensional Machine Learning and Blood Transcriptomics

Acute myeloid leukemia (AML) is a severe, mostly fatal hematopoietic malignancy. We were interested in whether transcriptomic-based machine learning could predict AML status without requiring expert input. Using 12,029 samples from 105 different studies, we present a large-scale study of machine learning-based prediction of AML in which we address key questions relating to the combination of machine learning and transcriptomics and their practical use. We find data-driven, high-dimensional approaches—in which multivariate signatures are learned directly from genome-wide data with no prior knowledge—to be accurate and robust. Importantly, these approaches are highly scalable with low marginal cost, essentially matching human expert annotation in a near-automated workflow. Our results support the notion that transcriptomics combined with machine learning could be used as part of an integrated -omics approach wherein risk prediction, differential diagnosis, and subclassification of AML are achieved by genomics while diagnosis could be assisted by transcriptomic-based machine learning.

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Study presents one of the largest transcriptomics datasets to date for AML prediction

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Effective classifiers can be obtained by high-dimensional machine learning

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Accuracy increases with dataset size

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Includes challenging scenarios such as cross-study and cross-technology

Mutant CEBPA directly drives the expression of the targetable tumor-promoting factor CD73 in AML

The key myeloid transcription factor (TF), CEBPA, is frequently mutated in acute myeloid leukemia (AML), but the direct molecular effects of this leukemic driver mutation remain elusive. To investigate CEBPA mutant AML, we performed microscale, in vivo chromatin immunoprecipitation sequencing and identified a set of aberrantly activated enhancers, exclusively occupied by the leukemia-associated CEBPA-p30 isoform. Comparing gene expression changes in human CEBPA mutant AML and the corresponding Cebpa ^Lp30 mouse model, we identified Nt5e, encoding CD73, as a cross-species AML gene with an upstream leukemic enhancer physically and functionally linked to the gene. Increased expression of CD73, mediated by the CEBPA-p30 isoform, sustained leukemic growth via the CD73/A2AR axis. Notably, targeting of this pathway enhanced survival of AML-transplanted mice. Our data thus indicate a first-in-class link between a cancer driver mutation in a TF and a druggable, direct transcriptional target.

The impact of RNA sequence library construction protocols on transcriptomic profiling of leukemia

Background

RNA sequencing (RNA-seq) has become an indispensable tool to identify disease associated transcriptional profiles and determine the molecular underpinnings of diseases. However, the broad adaptation of the methodology into the clinic is still hampered by inconsistent results from different RNA-seq protocols and involves further evaluation of its analytical reliability using patient samples. Here, we applied two commonly used RNA-seq library preparation protocols to samples from acute leukemia patients to understand how poly-A-tailed mRNA selection (PA) and ribo-depletion (RD) based RNA-seq library preparation protocols affect gene fusion detection, variant calling, and gene expression profiling.

Results

Overall, the protocols produced similar results with consistent outcomes. Nevertheless, the PA protocol was more efficient in quantifying expression of leukemia marker genes and showed better performance in the expression-based classification of leukemia. Independent qRT-PCR experiments verified that the PA protocol better represented total RNA compared to the RD protocol. In contrast, the RD protocol detected a higher number of non-coding RNA features and had better alignment efficiency. The RD protocol also recovered more known fusion-gene events, although variability was seen in fusion gene predictions.

Conclusion

The overall findings provide a framework for the use of RNA-seq in a precision medicine setting with limited number of samples and suggest that selection of the library preparation protocol should be based on the objectives of the analysis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4039-1) contains supplementary material, which is available to authorized users.

Systematic analysis of hematopoietic gene expression profiles for prognostic prediction in acute myeloid leukemia

Acute myeloid leukemia (AML) is a hematopoietic disorder initiated by the leukemogenic transformation of myeloid cells into leukemia stem cells (LSCs). Preexisting gene expression programs in LSCs can be used to assess their transcriptional similarity to hematopoietic cell types. While this relationship has previously been examined on a small scale, an analysis that systematically investigates this relationship throughout the hematopoietic hierarchy has yet to be implemented. We developed an integrative approach to assess the similarity between AML patient tumor profiles and a collection of 232 murine hematopoietic gene expression profiles compiled by the Immunological Genome Project. The resulting lineage similarity scores (LSS) were correlated with patient survival to assess the relationship between hematopoietic similarity and patient prognosis. This analysis demonstrated that patient tumor similarity to immature hematopoietic cell types correlated with poor survival. As a proof of concept, we highlighted one cell type identified by our analysis, the short-term reconstituting stem cell, whose LSSs were significantly correlated with patient prognosis across multiple datasets, and showed distinct patterns in patients stratified by traditional clinical variables. Finally, we validated our use of murine profiles by demonstrating similar results when applying our method to human profiles.

[Microarrays as biomarkers in trauma]

BACKGROUND

The traditional hypothesis-driven scientific approach cannot so far sufficiently elucidate complex pathophysiologies, such as posttraumatic systemic inflammation and subsequent multiple organ failure. This complex system includes different biological and functional levels, the genome, the transcriptome, the proteome, the biome (cells), the organs and finally the whole organism.

METHODS

Microarray techniques enable a simultaneous search for these different biological levels and their functional relationships on a large scale and to discover new functional pathways and networks and potentially new biomarkers for different pathologies. Microarray technologies lead to a new paradigm in science, the hypothesis-generating approach.

AIM

This article reviews important microarray findings in trauma and systemic inflammation research and discusses potentials and limitations of these biotechnological screening methods.

Acute Leukemia Subclassification: A Marker Protein Expression Perspective

Improved leukemia classification and tailoring of therapy have greatly improved patient outcome particularly for children with acute leukemia (AL). Using immunophenotyping, molecular genetics and cytogenetics the low hanging fruits of biomedical research have been successfully incorporated in routine diagnosis of leukemia subclasses. Future improvements in the classification and understanding of leukemia biology will very likely be more slow and laborious. Recently, gene expression profiling has provided a framework for the global molecular analysis of hematological cancers, and high throughput proteomic analysis of leukemia samples is on the way. Here we consider classification of acute leukemia samples by flow cytometry using the marker proteins of immunophenotyping as a component of the proteome. Marker protein expressions are converted into quantitative expression values and subjected to computational analysis. Quantitative multivariate analysis from panels of marker proteins has demonstrated that marker protein expression profiles can distinguish MLLre from non-MLLre ALL cases and also allow to specifically distinguish MLL/AF4 cases. Potentially, these quantitative expression analyses can be used in clinical diagnosis. Immunophenotypic data collection using flow cytometry is a fast and relatively easily accessible technology that has already been implemented in most centers for leukemia diagnosis and the translation into quantitative expression data sets is a matter of flow cytometer settings and output calibration. However, before application in clinical diagnostics can occur it is crucial that quantitative immunophenotypic data set analysis is validated in independent experiments and in large data sets.

Heat shock protein 90 is critical for regulation of phenotype and functional activity of human T lymphocytes and NK cells

The 90-kDa heat shock protein (Hsp90) has become an important therapeutic target with ongoing evaluation in a number of malignancies. Although Hsp90 inhibitors have a high therapeutic index with limited effects on normal cells, they have been described to inhibit dendritic cell function. However, its effect on human immune effector cells may have significant clinical implications, but remains unexplored. In this study, we have evaluated the effects of Hsp90 inhibition on human T lymphocyte and NK cells, including their Ag expression, activation, proliferation, and functional activities. These studies demonstrate that Hsp90 inhibition irreversibly downregulates cell surface expression of critical Ags (CD3, CD4, CD8), the costimulatory molecule (CD28, CD40L), and αβ receptors on T lymphocytes, as well as activating receptors (CD2, CD11a, CD94, NKp30, NKp44, NKp46, KARp50.3) on NK cells. Hsp90 inhibition significantly reduced CD4 protein expression on T lymphocytes at both the cell surface and intracellular level, which was shown to be associated with aberrant regulation of Src-kinase p56(Lck). Downregulation of the Ags triggered by Hsp90 inhibition on CD3(+) T lymphocytes, both in CD4(+) and CD8(+) T cell subsets, was associated with a disruption in their cellular activation, proliferation, and/or IFN-γ production, when the inhibition occurred either in activated or inactivated cells. In addition, downregulation of key activating receptors on NK cells following Hsp90 inhibition resulted in decreased cytotoxicity against tumor cells. Therefore, these observations demonstrate the need to closely monitor immune function in patients being treated with a Hsp90 inhibitor and may provide a potential therapeutic application in autoimmune diseases.

Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia: accurate results can be obtained even with suboptimal samples

Background

Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified.

Methods

Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n = 101) and/or poor quality control criteria (n = 10) (test set).

Results

With 10-marker classifiers, all training set samples as well as 97 of the 101 test samples with a low blast load, and all 10 samples with poor quality control criteria were correctly classified. Regarding test set samples, the overall error rate of the class prediction was below 4 percent, even though the leukemic blast load was as low as 2%. Sensitivity, specificity, negative and positive predictive values of the class assignments ranged from 91% to 100%. Of note, for acute promyelocytic leukemia and leukemias with t(8;21) or inv(16), the confidence level of the class assignment was influenced by the leukemic blast load.

Conclusion

Gene expression profiling and a supervised method requiring 10-marker classifiers enable the identification of favorable cytogenetic risk acute myeloid leukemia even when samples contain low leukemic blast loads or display poor quality control criterion.

Evaluation of gene expression signatures predictive of cytogenetic and molecular subtypes of pediatric acute myeloid leukemia

BACKGROUND

Pediatric acute myeloid leukemia is a heterogeneous disease characterized by non-random genetic aberrations related to outcome. The genetic subtype is currently detected by different diagnostic procedures which differ in success rate and/or specificity.

DESIGN AND METHODS

We examined the potential of gene expression profiles to classify pediatric acute myeloid leukemia. Gene expression microarray data of 237 children with acute myeloid leukemia were collected and a double-loop cross validation approach was used to generate a subtype-predictive gene expression profile in the discovery cohort (n=157) which was then tested for its true predictive value in the independent validation cohort (n=80). The classifier consisted of 75 probe sets, representing the top 15 discriminating probe sets for MLL-rearranged, t(8;21)(q22;q22), inv(16)(p13q22), t(15;17)(q21;q22) and t(7;12)(q36;p13)-positive acute myeloid leukemia.

RESULTS

These cytogenetic subtypes represent approximately 40% of cases of pediatric acute myeloid leukemia and were predicted with 92% and 99% accuracy in the discovery and independent validation cohort, respectively. However, for NPM1, CEBPA, MLL(-PTD), FLT3(-ITD), KIT, PTPN11 and N/K-RAS gene expression signatures had limited predictive value. This may be caused by a limited frequency of these mutations and by underlying cytogenetics. This latter is exemplified by the fact that different gene expression signatures were discovered for FLT3-ITD in patients with normal cytogenetics and in those with t(15;17)(q21;q22)-positive acute myeloid leukemia, which pointed to HOXB-upregulation being specific for FLT3-ITD(+) cytogenetically normal acute myeloid leukemia.

CONCLUSIONS

In conclusion, gene expression profiling correctly predicted the most prevalent cytogenetic subtypes of pediatric acute myeloid leukemia with high accuracy. In clinical practice, this gene expression signature may replace multiple diagnostic tests for approximately 40% of pediatric acute myeloid leukemia cases whereas only for the remaining cases (predicted as 'acute myeloid leukemia-other') are additional tests indicated. Moreover, the discriminative genes reveal new insights into the biology of acute myeloid leukemia subtypes that warrants follow-up as potential targets for new therapies.

Clinical utility of microarray-based gene expression profiling in the diagnosis and subclassification of leukemia: report from the International Microarray Innovations in Leukemia Study Group

PURPOSE

The Microarray Innovations in Leukemia study assessed the clinical utility of gene expression profiling as a single test to subtype leukemias into conventional categories of myeloid and lymphoid malignancies.

METHODS

The investigation was performed in 11 laboratories across three continents and included 3,334 patients. An exploratory retrospective stage I study was designed for biomarker discovery and generated whole-genome expression profiles from 2,143 patients with leukemias and myelodysplastic syndromes. The gene expression profiling-based diagnostic accuracy was further validated in a prospective second study stage of an independent cohort of 1,191 patients.

RESULTS

On the basis of 2,096 samples, the stage I study achieved 92.2% classification accuracy for all 18 distinct classes investigated (median specificity of 99.7%). In a second cohort of 1,152 prospectively collected patients, a classification scheme reached 95.6% median sensitivity and 99.8% median specificity for 14 standard subtypes of acute leukemia (eight acute lymphoblastic leukemia and six acute myeloid leukemia classes, n = 693). In 29 (57%) of 51 discrepant cases, the microarray results had outperformed routine diagnostic methods.

CONCLUSION

Gene expression profiling is a robust technology for the diagnosis of hematologic malignancies with high accuracy. It may complement current diagnostic algorithms and could offer a reliable platform for patients who lack access to today's state-of-the-art diagnostic work-up. Our comprehensive gene expression data set will be submitted to the public domain to foster research focusing on the molecular understanding of leukemias.

Integrative meta-analysis of differential gene expression in acute myeloid leukemia

Background

Acute myeloid leukemia (AML) is a heterogeneous disease with an overall poor prognosis. Gene expression profiling studies of patients with AML has provided key insights into disease pathogenesis while exposing potential diagnostic and prognostic markers and therapeutic targets. A systematic comparison of the large body of gene expression profiling studies in AML has the potential to test the extensibility of conclusions based on single studies and provide further insights into AML.

Methodology/Principal Findings

In this study, we systematically compared 25 published reports of gene expression profiling in AML. There were a total of 4,918 reported genes of which one third were reported in more than one study. We found that only a minority of reported prognostically-associated genes (9.6%) were replicated in at least one other study. In a combined analysis, we comprehensively identified both gene sets and functional gene categories and pathways that exhibited significant differential regulation in distinct prognostic categories, including many previously unreported associations.

Conclusions/Significance

We developed a novel approach for granular, cross-study analysis of gene-by-gene data and their relationships with established prognostic features and patient outcome. We identified many robust novel prognostic molecular features in AML that were undetected in prior studies, and which provide insights into AML pathogenesis with potential diagnostic, prognostic, and therapeutic implications. Our database and integrative analysis are available online (http://gat.stamlab.org).

Genes predictive of outcome and novel molecular classification schemes in adult acute myeloid leukemia

The pretreatment karyotype of leukemic blasts is currently the key determinant in therapy decision making in acute myeloid leukemia (AML). The World Health Organization (WHO) has recognized this important information by including, besides clinical, cytological, cytochemical, and immunophenotypical features, recurrent cytogenetic abnormalities in its classification (Table 1). However, although the WHO defines important biologically and clinically relevant entities, the prognostic value of some of the well-defined cytogenetic subgroups is partially masked in the WHO classification. Moreover, in the recent past a number of novel molecular aberrations with marked prognostic value, which are not yet incorporated in the WHO classifications have been identified. These molecular abnormalities include mutations (e.g., in FLT3, c-KIT, and NPM1), partial duplications (e.g., of MLL and FLT3), and abnormal expression of pathogenetic genes (e.g., EVI1, WT1, BCL2, MDR1, BAALC, and ERG). In addition, novel molecular approaches in genomics, like monitoring the expression levels of thousands of genes in parallel using DNA microarray technology, open possibilities for further refinement of prognostication of AML. Gene expression profiling in AML is already well established and has proven to be valuable to recognize various cytogenetic subtypes, discover novel AML subclasses, and predict clinical outcome. The current advances made in molecular understanding of AML will ultimately lead to a further refinement of prognostics of AML.

Pharmacogenomics in acute myeloid leukemia

Acute myeloid leukemia (AML) in adults is a heterogeneous malignant pathology with a globally unfavorable prognosis. The classification of AML allows identification of subgroups with favorable prognosis. However, besides these specific subgroups, most patients will have an intermediate or unfavorable prognosis often resulting in induction failure, probably due to drug resistance of the leukemic blasts, and more frequently resulting in early relapse after achieving complete remission. This unfavorable situation leads to a strong need to develop new diagnostic and therapeutic options. However, development of these therapies and their efficient use requires a better understanding of the biology and the molecular pathogenesis of AML. Pharmacogenomics focuses on the genetic variation of drug-metabolizing enzymes, targets and transporters, and how these genetic variations interact to produce specific drug-related phenotypes. Potential genetic markers may serve to functionally subclassify patients by their disease and therefore influence the nature and intensity of treatment. This review summarizes important aspects of and recent advances in the field of pharmacogenomics in AML.

2-D PAGE-based comparison of proteasome inhibitor bortezomib in sensitive and resistant mantle cell lymphoma

Although gene expression following bortezomib treatment has been previously explored, direct effects of bortezomib-induced proteasome inhibition on protein level has not been analyzed so far. Using 2-D PAGE in five mantle cell lymphoma cell lines, we screened for cellular protein level alterations following treatment with 25 nM bortezomib for up to 4 h. Using MS, we identified 38 of the 41 most prominent reliably detected protein spots. Twenty-one were affected in all cell lines, whereas the remaining 20 protein spots were exclusively altered in sensitive cell lines. Western blot analysis was performed for 17 of the 38 identified proteins and 70.6% of the observed protein level alterations in 2-D gels was verified. All cell lines exhibited alterations of the cellular protein levels of heat shock-induced protein species (HSPA9, HSP7C, HSPA5, HSPD1), whereas sensitive cell lines also displayed altered cellular protein levels of energy metabolism (ATP5B, AK5, TPI1, ENO-1, ALDOC, GAPDH), RNA and transcriptional regulation (HNRPL, SFRS12) and cell division (NEBL, ACTB, SMC1A, C20orf23) as well as tumor suppressor genes (ENO-1, FH). These proteins clustered in a tight interaction network centered on the major cellular checkpoints TP53. The results were confirmed in primary mantle cell lymphoma, thus confirming the critical role of these candidate proteins of proteasome inhibition.

Perspectives of gene expression profiling for diagnosis and therapy in haematological malignancies

Considering the heterogeneity of leukaemias and the widening spectrum of therapeutic strategies, novel diagnostic methods are urgently needed for haematological malignancies. For a decade, gene expression profiling (GEP) has been applied in leukaemia research. Thus, various studies demonstrated worldwide that the majority of genetically defined leukaemia subtypes are accurately predictable by GEP, for example, with respect to reciprocal rearrangements in acute myeloid leukaemia (AML). Moreover, novel prognostically relevant gene classifiers were developed as, for example, in normal karyotype AML. Considering the lymphatic malignancies, GEP studies defined novel clinically relevant subtypes in diffuse large B cell lymphoma (DLBCL), and improved the discrimination of Burkitt lymphoma and DLBCL cases, overcoming considerable overlaps of these entities that exist from morphological and genetic perspectives. Treatment-specific sensitivity assays are being developed for targeted drugs such as farnesyl transferase inhibitors in AML or imatinib in BCR-ABL1 positive acute lymphoblastic leukaemia (ALL). Irrespectively of these proceedings, an introduction of the microarray technology in haematological practice requires diagnostic algorithms and strategies for interaction with currently established diagnostic techniques. Large multicentre studies such as the MILE Study (Microarray Innovations in LEukemia) aim at translating this methodology into clinical routine workflows and to catalyze this process.

High throughput digital quantification of mRNA abundance in primary human acute myeloid leukemia samples

Acute promyelocytic leukemia (APL) is characterized by the t(15;17) chromosomal translocation, which results in fusion of the retinoic acid receptor alpha (RARA) gene to another gene, most commonly promyelocytic leukemia (PML). The resulting fusion protein, PML-RARA, initiates APL, which is a subtype (M3) of acute myeloid leukemia (AML). In this report, we identify a gene expression signature that is specific to M3 samples; it was not found in other AML subtypes and did not simply represent the normal gene expression pattern of primary promyelocytes. To validate this signature for a large number of genes, we tested a recently developed high throughput digital technology (NanoString nCounter). Nearly all of the genes tested demonstrated highly significant concordance with our microarray data (P < 0.05). The validated gene signature reliably identified M3 samples in 2 other AML datasets, and the validated genes were substantially enriched in our mouse model of APL, but not in a cell line that inducibly expressed PML-RARA. These results demonstrate that nCounter is a highly reproducible, customizable system for mRNA quantification using limited amounts of clinical material, which provides a valuable tool for biomarker measurement in low-abundance patient samples.

Peroxiredoxin IV protects cells from radiation-induced apoptosis in head-and-neck squamous cell carcinoma

PURPOSE

Human peroxiredoxins (Prxs) are known as a family of thiol-specific antioxidant enzymes, among which Prx-I and -II play an important role in protecting cells from irradiation-induced cell death. It is not known whether Prx-IV also protects cells from ionizing radiation (IR).

METHODS AND MATERIALS

To evaluate the protective role of Prx-IV in IR, we transfected full-length Prx-IV cDNA into AMC-HN3 cells, which weakly express endogenous Prx-IV, and knocked down the expression of Prx-IV with siRNA methods using AMC-HN7 cells, which express high levels of endogenous Prx-IV. Radiosensitivity profiles in these cells were evaluated using clonogenic assay, FACS analysis, cell viability, and TUNEL assay.

RESULTS

Three Prx-IV expressing clones were isolated. Prx-IV regulated intracellular reactive oxygen species (ROS) levels and made cells more resistant to IR-induced apoptosis. Furthermore, the knockdown of Prx-IV with siRNA made cells more sensitive to IR-induced apoptosis.

CONCLUSION

The results of these studies suggest that Prx-IV may play an important role in protecting cells from IR-induced apoptosis in head-and-neck squamous cell carcinoma.

Current status of gene expression profiling in the diagnosis and management of acute leukaemia

Gene expression profiling (GEP) enables the simultaneous investigation of the expression of tens of thousands of genes and was successfully introduced in leukaemia research a decade ago. Aiming to better understand the diversity of genetic aberrations in acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL), pioneer studies investigated and confirmed the predictability of many cytogenetic and molecular subclasses in AML and ALL. In addition, GEP can define new prognostic subclasses within distinct leukaemia subgroups, as illustrated in AML with normal karyotype. Another approach is the development of treatment-specific sensitivity assays, which might contribute to targeted therapy studies. Finally, GEP might enable the detection of new molecular targets for therapy in patients with acute leukaemia. Meanwhile, large multicentre studies, e.g. the Microarray Innovations in LEukaemia (MILE) study, prepare for a standardised introduction of GEP in leukaemia diagnostic algorithms, aiming to translate this novel methodology into clinical routine for the benefit of patients with the complex disorders of AML and ALL.

AML with translocation t(8;16)(p11;p13) demonstrates unique cytomorphological, cytogenetic, molecular and prognostic features

Balanced chromosomal rearrangements define distinct entities in acute myeloid leukemia (AML). Here, we present 13 AML cases with t(8;16)(p11;p13) with observed low incidence (13/6124 patients), but more frequent presentation in therapy-related AML than in de novo AML (7/438 versus 6/5686, P=0.00001). Prognosis was poor with median overall survival of 4.7 months. Cytomorphology was characterized by parallel positive myeloperoxidase and non-specific esterase staining, therefore, French-American-British (FAB)-classification was impossible and origin of the AML with t(8;16) from an early stem cell with myeloid and monoblastic potential is hypothesized. Erythrophagocytosis was observed in 7/13 cases. Using gene expression profiling on 407 cases, patients with t(8;16) were compared to AML FAB subtypes with normal karyotype. Principal component analyses demonstrated that AML with t(8;16) were distinct from FAB subtypes M1, M4, M5a/b. When further compared to AML showing balanced rearrangements, that is, current WHO categories t(15;17), t(8;21), inv(16) and t(11q23)/MLL, AML with t(8;16) cases were clustered close to t(11q23)/MLL sharing commonly expressed genes. Subsequently, a pairwise comparison discriminated AML with t(8;16) from AML with t(11q23)/MLL, thus defining a highly unique signature for AML with t(8;16). In conclusion, AML with t(8;16) demonstrates unique cytomorphological, cytogenetic, molecular and prognostic features and is a specific subtype of AML.

Integration of genomic and gene expression data of childhood ALL without known aberrations identifies subgroups with specific genetic hallmarks

Pediatric acute lymphoblastic leukemia (ALL) comprises genetically distinct subtypes. However, 25% of cases still lack defined genetic hallmarks. To identify genomic aberrancies in childhood ALL patients nonclassifiable by conventional methods, we performed a single nucleotide polymorphisms (SNP) array-based genomic analysis of leukemic cells from 29 cases. The vast majority of cases analyzed (19/24, 79%) showed genomic abnormalities; at least one of them affected either genes involved in cell cycle regulation or in B-cell development. The most relevant abnormalities were CDKN2A/9p21 deletions (7/24, 29%), ETV6 (TEL)/12p13 deletions (3/24, 12%), and intrachromosomal amplifications of chromosome 21 (iAMP21) (3/24, 12%). To identify variation in expression of genes directly or indirectly affected by recurrent genomic alterations, we integrated genomic and gene expression data generated by microarray analyses of the same samples. SMAD1 emerged as a down-regulated gene in CDKN2A homozygous deleted cases compared with nondeleted. The JAG1 gene, encoding the Jagged 1 ligand of the Notch receptor, was among a list of differentially expressed (up-regulated) genes in ETV6-deleted cases. Our findings demonstrate that integration of genomic analysis and gene expression profiling can identify genetic lesions undetected by routine methods and potential novel pathways involved in B-progenitor ALL pathogenesis.

Discussion of the applicability of microarrays: profiling of leukemias

Leukemias are classified according to clinical, morphologic, and immunologic phenotypes, caused by specific genetic aberrations in association to distinct prognostic profiles. Usually the subtypes are defined using complementary laboratory methods, such as multiparameter flow cytometry, cytogenetics in combination with fluorescence in situ hybridization, and molecular methods such as the polymerase chain reaction. The genetic variations of the different subtypes lead to distinct changes also in gene expression, which is comprehensively analysed by DNA microarrays. Thus, first gene expression profiling studies showed that analysis with whole-genome DNA microarrays leads to a prediction accuracy of 95.6% with respect to the classical methods, and even allowed a further distinction of subtypes. It is expected that diagnostic strategies can be optimized with this new technology and that the understanding of the molecular pathogenesis of leukemias will be significantly improved. This could also lead to the identification of new targets for future drugs.

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.

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 r² correlation analyses demonstrated that microarray analysis can be performed with remarkably high intra-laboratory reproducibility and with comparable quality and reliability.

Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling

We examined the gene expression profiles of two independent cohorts of patients with acute myeloid leukemia [n=247 and n=214 (younger than or equal to 60 years)] to study the applicability of gene expression profiling as a single assay in prediction of acute myeloid leukemia-specific molecular subtypes. The favorable cytogenetic acute myeloid leukemia subtypes, i.e., acute myeloid leukemia with t(8;21), t(15;17) or inv(16), were predicted with maximum accuracy (positive and negative predictive value: 100%). Mutations in NPM1 and CEBPA were predicted less accurately (positive predictive value: 66% and 100%, and negative predictive value: 99% and 97% respectively). Various other characteristic molecular acute myeloid leukemia subtypes, i.e., mutant FLT3 and RAS, abnormalities involving 11q23, -5/5q-, -7/7q-, abnormalities involving 3q (abn3q) and t(9;22), could not be correctly predicted using gene expression profiling. In conclusion, gene expression profiling allows accurate prediction of certain acute myeloid leukemia subtypes, e.g. those characterized by expression of chimeric transcription factors. However, detection of mutations affecting signaling molecules and numerical abnormalities still requires alternative molecular methods.

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

BACKGROUND

Gene expression profiling has the potential to offer consistent, objective diagnostic test results once a standardized protocol has been established. We investigated the robustness, precision, and reproducibility of microarray technology.

METHODS

One hundred sixty individual patient samples representing 11 subtypes of acute and chronic leukemias, myelodysplastic syndromes, and nonleukemia as a control group were centrally collected and diagnosed as part of the daily routine in the Munich Leukemia Laboratory. The custom AmpliChip Leukemia research microarray was used for technical analyses of quadruplicate mononuclear cell lysates in 4 different laboratories in Germany (D), Austria (A), and Switzerland (CH) (the DACH study).

RESULTS

Total-RNA preparations were successfully performed in 637 (99.5%) of 640 cases. Mean differences between pairs of laboratories in the total-RNA yield from the same sample ranged from 0.02 mug to 1.03 mug. Further processing produced 622 successful in vitro transcription reactions (97.6%); the mean differences between laboratories in the cRNA yield from the same sample ranged from 0.40 mug to 6.18 mug. After hybridization to microarrays, a mean of 47.6%, 46.5%, 46.2%, and 46.4% of probe sets were detected as present for the 4 laboratories, with mean signal-intensity scaling factors of 3.1, 3.7, 4.0, and 4.2, respectively. In unsupervised hierarchical cluster and principal component analyses, replicates from the same patient always clustered closely together, with no indications of any association between gene expression profiles due to different operators or laboratories.

CONCLUSIONS

Microarray analysis can be performed with high interlaboratory reproducibility and with comparable quality and high technical precision across laboratories.

Cytogenetic and molecular study of the PRDX4 gene in a t(X;18)(p22;q23): a cautionary tale

The PRDX4 gene located at Xp22 encodes for a member of the peroxiredoxin gene family. Genes within this family exhibit thioredoxin-dependent peroxidase activity and have been implicated in cellular functioning, including proliferation and differentiation. Recently, PRDX4 has been identified as a partner gene in a t(X;21) translocation in a patient with acute myeloid leukemia. To determine whether PRDX4 was involved in other translocations, leukemia cells from 15 patients with Xp22 abnormalities were screened for involvement of the gene using fluorescence in situ hybridization (FISH). One sample from a 41-year-old woman with acute lymphoblastic leukemia showed three signals when hybridized with the PRDX4 probe. Cytogenetic analysis of the sample had identified a t(X;18)(p22;q23). Assuming that the three signals indicated a break within the PRDX4 gene, we performed FISH experiments and successfully narrowed the breakpoint on chromosome 18 to a 50-kb region. Subsequent analysis using spectral karyotyping showed that the leukemic cells had undergone multiple rearrangements and that a third X chromosome was present, albeit rearranged. Additional FISH experiments revealed that the third PRDX4 signal was the result of a third copy of the gene. Analysis of the other rearrangements has helped to characterize the multiple abnormalities within the leukemic cells. The findings underscore the importance of using multiple techniques when analyzing complex chromosomal rearrangements in malignant cells.

Proteome- and microarray-based expression analysis of lymphoma cell lines identifies a p53-centered cluster of differentially expressed proteins in mantle cell and follicular lymphoma

We used a standardized electrophoresis protocol to identify differentially expressed proteins based on a sample pooling approach comparing three follicular lymphoma and three mantle cell lymphoma-derived cell lines. One hundred and seventy-five consistently differentially expressed proteins were identified out of more than 1600 protein spots per gel. Of these 175 protein spots, 38 of the 41 most highly expressed proteins were identified by MS analysis (MALDI-TOF), involving different cellular programs such as DNA repair (Rad50), cell cycle control (Mad1L1), transcription (SAFB), and apoptosis (Luca-15 protein). Expression data were confirmed by Western blot analysis of identified proteins and 2-D gel hybridization of proteins with known overexpression (G1/S-specific cyclin-D1, apoptosis regulator Bcl-2). Comparison of proteome analysis to RNA expression array data revealed only a modest correlation of RNA and protein level emphasizing the relevance of post-translational regulation in lymphomagenesis (p = 0.36). Most interestingly, additional data bank search identified 13 out of 17 referenced proteins (76%) as members of a TP53-dependent network of cell regulation.

High expression of connective tissue growth factor in pre-B acute lymphoblastic leukaemia

In recent years microarrays have been used extensively to characterize gene expression in acute lymphoblastic leukaemia (ALL). Few studies, however, have analysed normal haematopoietic cell populations to identify altered gene expression in ALL. We used oligonucleotide microarrays to compare the gene expression profile of paediatric precursor-B (pre-B) ALL specimens with two control cell populations, normal CD34(+) and CD19(+)IgM(-) cells, to focus on genes linked to leukemogenesis. A set of eight genes was identified with a ninefold higher average expression in ALL specimens compared with control cells. All of these genes were significantly deregulated in an independent cohort of 101 ALL specimens. One gene, connective tissue growth factor (CTGF, also known as CCN2), had exceptionally high expression, which was confirmed in three independent leukaemia studies. Further analysis of CTGF expression in ALL revealed exclusive expression in B-lineage, not T-lineage, ALL. Within B-lineage ALL approximately 75% of specimens were consistently positive for CTGF expression, however, specimens containing the E2A-PBX1 translocation showed low or no expression. Protein studies using Western blot analysis demonstrated the presence of CTGF in ALL cell-conditioned media. These findings indicate that CTGF is secreted by pre-B ALL cells and may play a role in the pathophysiology of this disease.

New data on robustness of gene expression signatures in leukemia: comparison of three distinct total RNA preparation procedures

BACKGROUND

Microarray gene expression (MAGE) signatures allow insights into the transcriptional processes of leukemias and may evolve as a molecular diagnostic test. Introduction of MAGE into clinical practice of leukemia diagnosis will require comprehensive assessment of variation due to the methodologies. Here we systematically assessed the impact of three different total RNA isolation procedures on variation in expression data: method A: lysis of mononuclear cells, followed by lysate homogenization and RNA extraction; method B: organic solvent based RNA isolation, and method C: organic solvent based RNA isolation followed by purification.

RESULTS

We analyzed 27 pediatric acute leukemias representing nine distinct subtypes and show that method A yields better RNA quality, was associated with more differentially expressed genes between leukemia subtypes, demonstrated the lowest degree of variation between experiments, was more reproducible, and was characterized with a higher precision in technical replicates. Unsupervised and supervised analyses grouped leukemias according to lineage and clinical features in all three methods, thus underlining the robustness of MAGE to identify leukemia specific signatures.

CONCLUSION

The signatures in the different subtypes of leukemias, regardless of the different extraction methods used, account for the biggest source of variation in the data. Lysis of mononuclear cells, followed by lysate homogenization and RNA extraction represents the optimum method for robust gene expression data and is thus recommended for obtaining robust classification results in microarray studies in acute leukemias.

Phenotypic and Functional Effects of Heat Shock Protein 90 Inhibition on Dendritic Cell

The 90-kDa heat shock protein (Hsp90) plays an important role in conformational regulation of cellular proteins and thereby cellular signaling and function. As Hsp90 is considered a key component of immune function and its inhibition has become an important target for cancer therapy, we here evaluated the role of Hsp90 in human dendritic cell (DC) phenotype and function. Hsp90 inhibition significantly decreased cell surface expression of costimulatory (CD40, CD80, CD86), maturation (CD83), and MHC (HLA-A, B, C and HLA-DP, DQ, DR) markers in immature DC and mature DC and was associated with down-regulation of both RNA and intracellular protein expression. Importantly, Hsp90 inhibition significantly inhibited DC function. It decreased Ag uptake, processing, and presentation by immature DC, leading to reduced T cell proliferation in response to tetanus toxoid as a recall Ag. It also decreased the ability of mature DC to present Ag to T cells and secrete IL-12 as well as induce IFN-gamma secretion by allogeneic T cells. These data therefore demonstrate that Hsp90-mediated protein folding is required for DC function and, conversely, Hsp90 inhibition disrupts the DC function of significant relevance in the setting of clinical trials evaluating novel Hsp90 inhibitor therapy in cancer.

Identification of genomic classifiers that distinguish induction failure in T-lineage acute lymphoblastic leukemia: a report from the Children's Oncology Group

The clinical and cytogenetic features associated with T-cell acute lymphoblastic leukemia (T-ALL) are not predictive of early treatment failure. Based on the hypothesis that microarrays might identify patients who fail therapy, we used the Affymetrix U133 Plus 2.0 chip and prediction analysis of microarrays (PAM) to profile 50 newly diagnosed patients who were treated in the Children's Oncology Group (COG) T-ALL Study 9404. We identified a 116-member genomic classifier that could accurately distinguish all 6 induction failure (IF) cases from 44 patients who achieved remission; network analyses suggest a prominent role for genes mediating cellular quiescence. Seven genes were similarly upregulated in both the genomic classifier for IF patients and T-ALL cell lines having acquired resistance to neoplastic agents, identifying potential target genes for further study in drug resistance. We tested whether our classifier could predict IF within 42 patient samples obtained from COG 8704 and, using PAM to define a smaller classifier for the U133A chip, correctly identified the single IF case and patients with persistently circulating blasts. Genetic profiling may identify T-ALL patients who are likely to fail induction and for whom alternate treatment strategies might be beneficial.

Significance of gene expression analysis in uveal melanoma in comparison to standard risk factors for risk assessment of subsequent metastases

PURPOSE

This study was undertaken to identify and compare the prognostic value of gene expression, chromosomal, and clinico-pathological data for the prediction of subsequent metastases in patients with primary uveal melanoma.

PATIENTS AND METHODS

For comparison of different sets of predictor variables diagonal linear discriminant analysis was used. Chromosomal events were assessed by comparative genomic hybridization and gene expression profiling by microarray. Twenty-eight patients with a median follow-up of 68 months were analyzed, of whom 12 had developed subsequent metastases.

RESULTS

Diagonal linear discriminant analysis with crossvalidation of gene expression data detected 42 genes as differentially expressed in metastasizing vsnon-metastasizing uveal melanomas in all 28 cases. Comparing quantitative scores of discriminant analysis, grouping precision was significant better with gene expression profiling compared to comparative genomic hybridization (P=0.01) and to clinical data (P=0.001). Two published gene lists associated with monosomy 3 and metastatic tumor growth were used as classifier for discriminant analysis and yielded superior classification in patients with and without subsequent metastases than chromosomal or clinico-pathological data.

CONCLUSION

In our patient cohort gene expression profiling of primary uveal melanoma tissue was superior to clinical-pathological and chromosomal analysis to assess for the risk of subsequent metastases.

Insight into the molecular pathogenesis of myeloid malignancies

PURPOSE OF REVIEW

Molecular mutations play an increasing role for classification, prognostication, and therapeutic strategies in acute myeloid leukemia and myelodysplastic syndrome. Due to the rapid expansion of known molecular markers, this paper aims to outline some of the recent progress to improve understanding of the pathogenesis in these myeloid malignancies.

RECENT FINDINGS

Novel concepts conceive myelodysplastic syndrome and acute myeloid leukemia as endpoints of a continuous process of leukemogenesis, which is characterized by the interaction of mutations interfering with transcription and differentiation with activating mutations enhancing proliferation. The detection of novel molecular mutations such as NPM1 widened the spectrum of molecular markers in acute myeloid leukemia. Finally, attention focusses on detailed subtyping of already known molecular markers.

SUMMARY

The fast progress in the molecular characterization of acute myeloid leukemia and myelodysplastic syndrome in recent years provides the basis for an optimization of therapeutic concepts. The introduction of new methods such as gene expression profiling catalyzes this process.

Polychromatic flow cytometry: a rapid method for the reduction and analysis of complex multiparameter data

BACKGROUND

Recent advances in flow cytometry have resulted in the development of reliable techniques for performing polychromatic (5-17 color) flow cytometry analysis. However, the data reduction and analysis involved in the resolution of hundreds of possible cellular subphenotypes identified, using a single polychromatic flow cytometry staining panel, presents a major obstacle to the successful application of this technology.

METHODS

To generate two distinct collections of T cell populations with differentially expressed surface markers, cryopreserved lymph node cells from 5 melanoma patients vaccinated with the modified gp100(209-2M) melanoma peptide were stimulated with cognate peptide and cultured in either IL-21 + low-dose IL-2 or IL-15 + low-dose IL-2. In vitro stimulated (IVS) cells were interrogated using 8-color flow cytometry. Data were analyzed using Winlist Hyperlog and FCOM software, and 32 T cell subsets were resolved for each culture condition. Hierarchical clustering analysis was applied to the relative percentages of each subphenotype for both IVS conditions to determine if unique cell surface marker expression signatures were produced for each IVS culture.

RESULTS

Sequential data analysis using Hyperlog and FCOM demonstrated that lymphocytes cultured in IL-21 + IL-2 had a distinctively different set of subphenotype signatures compared to cells grown in IL-15 + IL-2 for all 5 patients. Importantly, subsequent cluster analysis of all 32 subphenotype frequencies in each IVS test condition for all 5 patients reproducibly demonstrated that cellular subphenotypes produced after IL-21 + IL-2 IVS partitioned separately from subphenotypes produced by IL-15 + IL-2 IVS.

CONCLUSIONS

The integrated sequential use of Hyperlog and FCOM software with cluster analysis algorithms for the reduction and analysis of polychromatic flow cytometry data produces an effective, rapid technique for the assessment of complex patterns of subphenotype expression between and within multiple test samples. This approach to data analysis may enhance the use of polychromatic flow cytometry for both research and clinical applications.

Differential gene expression patterns and interaction networks in BCR-ABL-positive and -negative adult acute lymphoblastic leukemias

PURPOSE

To identify gene expression patterns and interaction networks related to BCR-ABL status and clinical outcome in adults with acute lymphoblastic leukemia (ALL).

PATIENTS AND METHODS

DNA microarrays were used to profile a set of 54 adult ALL specimens from the Medical Research Council UKALL XII/Eastern Cooperative Oncology Group E2993 trial (21 p185BCR-ABL-positive, 16 p210BCR-ABL-positive and 17 BCR-ABL-negative specimens).

RESULTS

Using supervised and unsupervised analysis tools, we detected significant transcriptomic changes in BCR-ABL-positive versus -negative specimens, and assessed their validity in an independent cohort of 128 adult ALL specimens. This set of 271 differentially expressed genes (including GAB1, CIITA, XBP1, CD83, SERPINB9, PTP4A3, NOV, LOX, CTNND1, BAALC, and RAB21) is enriched for genes involved in cell death, cellular growth and proliferation, and hematologic system development and function. Network analysis demonstrated complex interaction patterns of these genes, and identified FYN and IL15 as the hubs of the top-scoring network. Within the BCR-ABL-positive subgroups, we identified genes overexpressed (PILRB, STS-1, SPRY1) or underexpressed (TSPAN16, ADAMTSL4) in p185BCR-ABL-positive ALL relative to p210BCR-ABL-positive ALL. Finally, we constructed a gene expression- and interaction-based outcome predictor consisting of 27 genes (including GRB2, GAB1, GLI1, IRS1, RUNX2, and SPP1), which correlated with overall survival in BCR-ABL-positive adult ALL (P = .0001), independent of age (P = .25) and WBC count at presentation (P = .003).

CONCLUSION

We identified prominent molecular features of BCR-ABL-positive adult ALL, which may be useful for developing novel therapeutic targets and prognostic markers in this disease.

Diagnostic pathways in acute leukemias: a proposal for a multimodal approach

Acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) each represent a heterogeneous complex of disorders, which result from diverse mechanisms of leukemogenesis. Modern therapeutic concepts are based on individual risk stratification at diagnosis and during follow-up. For some leukemia subtypes such as AML M3/M3v with t(15;17)/PML-RARA or Philadelphia-positive ALL targeted therapy options are available. Thus, optimal therapeutic conditions are based on exact classification of the acute leukemia subtype at diagnosis and are guided by exact and sensitive quantification of minimal residual disease during complete hematologic remission. Today, a multimodal diagnostic approach combining cytomorphology, multiparameter flow cytometry, chromosome banding analysis, accompanied by diverse fluorescence in situ hybridization techniques, and molecular analyses is needed to meet these requirements. As the diagnostic process becomes more demanding with respect to experience of personnel, time, and costs due to the expansion of methods, algorithms, which guide the diagnostic procedure from basic to more specific methods and which lead finally to a synopsis of the respective results, are essential for modern diagnostics and therapeutic concepts.

Proteomics-based strategy to identify biomarkers and pharmacological targets in leukemias with t(4;11) translocations

Translocations and other aberrations involving the MLL (mixed lineage leukemia) gene result in aggressive forms of leukemias. Heterogeneity in partner genes, in chromosomal breakpoints, in MLL itself, and in the different partner genes results in heterogeneous fusion transcripts that can be alternatively spliced, which complicates deciphering a unifying mechanism of leukemogenesis. However, recent microarray studies completed with clinical leukemia specimens have uncovered several distinct mRNA signatures within MLL leukemia that differ from other types of leukemia. A global proteomics strategy using MV4-11 and RS4:11 cells in culture was employed to investigate possible protein signatures common to different MLL leukemias and to identify disease biomarkers and protein targets for pharmacological intervention. Initial proteomics screening experiments with two-dimensional differential in-gel electrophoresis revealed heat shock protein 90 alpha (HSP90alpha) as a potential target for pharmacological inhibition and nucleoside diphosphate kinase (nm23) as a biomarker for measuring treatment efficacy. Using a modified stable isotope labeling of amino acids in cell culture (SILAC) approach, coupled with two-dimensional liquid chromatography tandem mass spectrometry (2D-LC-MS/MS), changes in abundance for over 500 proteins were measured. In addition, decreased expression of the novel biomarker nm23 was observed during HSP90 inhibition with 17-allylamino-17-demethoxygeldanamycin (17-AAG) in the MV4-11 cell line. The present study validates the use of a global proteomics strategy to uncover novel biomarkers and pharmacological targets for leukemias with MLL translocations. Additionally, several proteins were found to be expressed in concordance with microarray studies of mRNA expression in specimens from patients showing the value in comparing mRNA transcript and proteomic profiles. This work represents one of the most comprehensive proteomics screens of MLL leukemias that have been conducted to date.

Use of nanotechnology for the development of novel cancer biomarkers

Novel nanotechnologies can complement and augment existing genomic and proteomic techniques employed to analyze variations across different tumor types, thus offering the potential to distinguish between normal and malignant cells. Sensitive biosensors constructed out of nanoscale components (e.g., nanocantilevers, nanowires and nanochannels) can recognize genetic and molecular events and have reporting capabilities, thereby offering the potential to detect rare molecular signals associated with malignancy. Such signals may then be collected for analysis by nanoscale harvesters that selectively isolate cancer-related molecules from tissues. Another area with near-term potential for the early detection of cancer is the identification of mutations and genomic instability.

Gene expression profiling for the diagnosis of acute leukaemia

An optimised diagnostic setting in acute leukaemias combines cytomorphology and cytochemistry, multiparameter immunophenotyping, cytogenetics, fluorescence in situ hybridisation, and polymerase chain reaction (PCR)-based assays. This allows classification and definition of biologically defined and prognostically relevant subtypes, and allows directed treatment in some sub-entities. Over the last years the microarray technology has helped to quantify simultaneously the expression status of ten thousands of genes in single experiments. This novel approach will hopefully become an essential tool for the molecular classification of acute leukaemias in the near future. It can be anticipated that new biologically defined and clinically relevant subtypes of leukaemia will be identified based on their unique gene expression profiles. This method may therefore guide therapeutic decisions and should be investigated in a diagnostic setting in parallel to established standard methods.

Diagnostic applications of microarrays

Microarrays were designed to monitor the expression of many genes in parallel, providing substantially more information than Northern blots or reverse transcription polymerase chain reaction analysing one or few genes at a time. The large sequencing projects provided the content for detailed expression studies under a variety of stimuli and conditions. The human genome project identified around 30 000 human genes. Estimated number of protein products is, however, 10-30 times higher, mainly due to the alternative splicing and post-translational modifications. The identification of gene functions requires both genomic and proteomic approaches, including protein microarrays, and numerous current microarray projects focus on deciphering gene expression patterns under a variety of conditions. Establishing the key genes and gene products for particular conditions opens the way for diagnostic applications using multiparameter, high-throughput assays. This format can also accommodate existing blood screening assays, potentially providing a single testing platform. This review considers the progress in diagnostic microarrays in a wider context of in vitro diagnostics field.

Commonly dysregulated genes in murine APL cells

To identify genes that are commonly dysregulated in a murine model of acute promyelocytic leukemia (APL), we first defined gene expression patterns during normal murine myeloid development; serial gene expression profiling studies were performed with primary murine hematopoietic progenitors that were induced to undergo myeloid maturation in vitro with G-CSF. Many genes were reproducibly expressed in restricted developmental "windows," suggesting a structured hierarchy of expression that is relevant for the induction of developmental fates and/or differentiated cell functions. We compared the normal myeloid developmental transcriptome with that of APL cells derived from mice expressing PML-RARalpha under control of the murine cathepsin G locus. While many promyelocyte-specific genes were highly expressed in all APL samples, 116 genes were reproducibly dysregulated in many independent APL samples, including Fos, Jun, Egr1, Tnf, and Vcam1. However, this set of commonly dysregulated genes was expressed normally in preleukemic, early myeloid cells from the same mouse model, suggesting that dysregulation occurs as a "downstream" event during disease progression. These studies suggest that the genetic events that lead to APL progression may converge on common pathways that are important for leukemia pathogenesis.

Common gene expression signatures in t(8;21)- and inv(16)-acute myeloid leukaemia

Human acute myeloid leukaemia (AML) involving a core-binding factor (CBF) transcription factor is called CBF leukaemia. In these leukaemias, AML1 (RUNX1, PEBP2alphaB, CBFalpha2)-MTG8 (ETO) and CBFbeta (PEBP2beta)-MYH11 chimaeric proteins are generated by t(8;21) and inv(16) respectively. We analysed gene expression profiles of leukaemic cells by microarray, and selected genes whose expression appeared to be modulated in association with t(8;21) and inv(16). In a pair-wise comparison, 15% of t(8;21)-associated transcripts exhibited high or low expression in inv(16)-AML, and 26% of inv(16)-associated transcripts did so equivalently in t(8;21)-AML. These common elements in gene expression profiles between t(8;21)- and inv(16)-AML probably reflect the situation that AML1-MTG8 and CBFbeta-MYH11 chimaeric proteins affect a common set of target genes in CBF leukaemic cells. On the other hand, 38% of t(8;21)-associated and 24% of inv(16)-associated transcripts were regulated in t(8;21)- and inv(16)-specific manners. These distinct features of t(8;21)- and inv(16)-associated genes correlate with the bimodular structures of the chimaeric proteins (CBF-related AML1 and CBFbeta portions, and CBF-unrelated MTG8 and MYH11 portions).