A quantitative analysis of heterogeneities and hallmarks in acute myelogenous leukaemia.

Acute myelogenous leukaemia (AML) is associated with risk factors that are largely unknown and with a heterogeneous response to treatment. Here, we provide a comprehensive quantitative understanding of AML proteomic heterogeneities and hallmarks by using the AML Proteome Atlas, a proteomics database that we have newly derived from MetaGalaxy analyses, for the proteomic profiling of 205 patients with AML and 111 leukaemia cell lines. The analysis of the dataset revealed 154 functional patterns based on common molecular pathways, 11 constellations of correlated functional patterns and 13 signatures that stratify the outcomes of patients. We find limited overlap between proteomics data and both cytogenetics and genetic mutations. Moreover, leukaemia cell lines show limited proteomic similarities with cells from patients with AML, suggesting that a deeper focus on patient-derived samples is needed to gain disease-relevant insights. The AML Proteome Atlas provides a knowledge base for proteomic patterns in AML, a guide to leukaemia cell line selection, and a broadly applicable computational approach for quantifying the heterogeneities of protein expression and proteomic hallmarks in AML.

BCL-2 family proteins as 5-Azacytidine-sensitizing targets and determinants of response in myeloid malignancies.

Synergistic molecular vulnerabilities enhancing hypomethylating agents in myeloid malignancies have remained elusive. RNA-interference drug modifier screens identified antiapoptotic BCL-2 family members as potent 5-Azacytidine-sensitizing targets. In further dissecting BCL-XL, BCL-2 and MCL-1 contribution to 5-Azacytidine activity, siRNA silencing of BCL-XL and MCL-1, but not BCL-2, exhibited variable synergy with 5-Azacytidine in vitro. The BCL-XL, BCL-2 and BCL-w inhibitor ABT-737 sensitized most cell lines more potently compared with the selective BCL-2 inhibitor ABT-199, which synergized with 5-Azacytidine mostly at higher doses. Ex vivo, ABT-737 enhanced 5-Azacytidine activity across primary AML, MDS and MPN specimens. Protein levels of BCL-XL, BCL-2 and MCL-1 in 577 AML patient samples showed overlapping expression across AML FAB subtypes and heterogeneous expression within subtypes, further supporting a concept of dual/multiple BCL-2 family member targeting consistent with RNAi and pharmacologic results. Consequently, silencing of MCL-1 and BCL-XL increased the activity of ABT-199. Functional interrogation of BCL-2 family proteins by BH3 profiling performed on patient samples significantly discriminated clinical response versus resistance to 5-Azacytidine-based therapies. On the basis of these results, we propose a clinical trial of navitoclax (clinical-grade ABT-737) combined with 5-Azacytidine in myeloid malignancies, as well as to prospectively validate BH3 profiling in predicting 5-Azacytidine response.

Low expression of PP2A regulatory subunit B55α is associated with T308 phosphorylation of AKT and shorter complete remission duration in acute myeloid leukemia patients.

The regulation of protein kinase B (AKT) is a dynamic process that depends on the balance between phosphorylation by upstream kinases for activation and inactivation by dephosphorylation by protein phosphatases. Phosphorylated AKT is commonly found in acute myeloid leukemia (AML) and confers an unfavorable prognosis. Understanding the relative importance of upstream kinases and AKT phosphatase in the activation of AKT is relevant for the therapeutic targeting of this signaling axis in AML. The B55α subunit of protein phosphatase 2A (PP2A) has been implicated in AKT dephosphorylation, but its role in regulating AKT in AML is unknown. We examined B55α protein expression in blast cells derived from 511 AML patients using reverse phase protein analysis. B55α protein expression was lower in AML cells compared with normal CD34+ cells. B55α protein levels negatively correlated with threonine 308 phosphorylation levels. Low levels of B55α were associated with shorter complete remission duration, demonstrating that decreased expression is an adverse prognostic factor in AML. These findings suggest that decreased B55α expression in AML is at least partially responsible for increased AKT signaling in AML and suggests that therapeutic targeting of PP2A could counteract this.

Differences in gene expression between B-cell chronic lymphocytic leukemia and normal B cells: a meta-analysis of three microarray studies.

MOTIVATION: A major focus of current cancer research is to identify genes that can be used as markers for prognosis and diagnosis, and as targets for therapy. Microarray technology has been applied extensively for this purpose, even though it has been reported that the agreement between microarray platforms is poor. A critical question is: how can we best combine the measurements of matched genes across microarray platforms to develop diagnostic and prognostic tools related to the underlying biology? RESULTS: We introduce a statistical approach within a Bayesian framework to combine the microarray data on matched genes from three investigations of gene expression profiling of B-cell chronic lymphocytic leukemia (CLL) and normal B cells (NBC) using three different microarray platforms, oligonucleotide arrays, cDNA arrays printed on glass slides and cDNA arrays printed on nylon membranes. Using this approach, we identified a number of genes that were consistently differentially expressed between CLL and NBC samples.

RNA amplification strategies for cDNA microarray experiments.

The biological materials available for cDNA microarray studies are often limiting. Thus, protocols have been developed to amplify RNAs isolated from limited amounts of tissues or cells. RNA amplification by in vitro transcription is the most widely used among the available amplification protocols. Two means of generating a dsDNA template for the RNA polymerase are a combination of reverse transcription with conventional second-strand cDNA synthesis and a combination of the switch mechanism at the 5' end of RNA templates (SMART) with reverse transcription, followed by PCR. To date, there has been no systematic comparison of the efficiency of the two amplification strategies. In this study, we performed and analyzed a set of six microarray experiments involving the use of a "regular" (unamplified) microarray experimental protocol and two different RNA amplification protocols. Based on their ability to identify differentially expressed genes and assuming that the results from the regular protocol are correct, our analyses demonstrated that both amplification protocols achieved reproducible and reliable results. From the same amount of starting material, our results also indicated that more amplified RNA can be obtained using conventional second-strand cDNA synthesis than from the combination of SMART and PCR. When the critical issue is the amount of starting RNA, we recommend the conventional second-strand cDNA synthesis as the preferred amplification method.

Sources of nonlinearity in cDNA microarray expression measurements.

BACKGROUND: A key assumption in the analysis of microarray data is that the quantified signal intensities are linearly related to the expression levels of the corresponding genes. To test this assumption, we experimentally examined the relationship between signal and expression for the two types of microarrays we most commonly encounter: radioactively labeled cDNAs on nylon membranes and fluorescently labeled cDNAs on glass slides. RESULTS: We uncovered two sources of nonlinearity. The first, which led to discrepancies in analysis affecting the fluorescent signals, was signal quenching associated with excessive dye concentrations. The second, affecting the radioactive signals, was a nonlinear transformation of the raw data introduced by the scanner. Correction for this transformation was made by some, but not all, image-quantification software packages. CONCLUSIONS: The second type of nonlinearity is more troublesome, because it could not have been predicted a priori. Both types of nonlinearities were detected by simple dilution series, which we recommend as a quality-control step.

Identifying differentially expressed genes in cDNA microarray experiments.

A major goal of microarray experiments is to determine which genes are differentially expressed between samples. Differential expression has been assessed by taking ratios of expression levels of different samples at a spot on the array and flagging spots (genes) where the magnitude of the fold difference exceeds some threshold. More recent work has attempted to incorporate the fact that the variability of these ratios is not constant. Most methods are variants of Student's t-test. These variants standardize the ratios by dividing by an estimate of the standard deviation of that ratio; spots with large standardized values are flagged. Estimating these standard deviations requires replication of the measurements, either within a slide or between slides, or the use of a model describing what the standard deviation should be. Starting from considerations of the kinetics driving microarray hybridization, we derive models for the intensity of a replicated spot, when replication is performed within and between arrays. Replication within slides leads to a beta-binomial model, and replication between slides leads to a gamma-Poisson model. These models predict how the variance of a log ratio changes with the total intensity of the signal at the spot, independent of the identity of the gene. Ratios for genes with a small amount of total signal are highly variable, whereas ratios for genes with a large amount of total signal are fairly stable. Log ratios are scaled by the standard deviations given by these functions, giving model-based versions of Studentization. An example is given.

Microarrays: handling the deluge of data and extracting reliable information.

Application of powerful, high-throughput genomics technologies is becoming more common and these technologies are evolving at a rapid pace. Genomics facilities are being established in major research institutions to produce inexpensive, customized cDNA microarrays that are accessible to researchers in a broad range of fields. These high-throughput platforms have generated a massive onslaught of data, which threatens to overwhelm researchers. Although microarrays show great promise, the technology has not matured to the point of consistently generating robust and reliable data when used in the average laboratory. This article addresses several aspects related to the handling of the deluge of microarray data and extracting reliable information from these data. We review the essential elements of data acquisition, data processing and data analysis, and briefly discuss issues related to the quality, validation and storage of data. Our goal is to point out some of the problems that must be overcome before this promising technology can achieve its full potential.

Cancer genomics: promises and complexities.

The impending final deciphering of the complete human genome, coupled with the advancement of high-throughput technologies, is positioned to bring about a fundamental transformation in cancer research. The era of molecular biology is transforming into the era of genomic biology, with an unprecedented promise of understanding multifactorial diseases and of identifying specific targets that can be used to develop patient-tailored therapies. Although the genomic approach is in an early phase of its development and its tools need to be honed, the application of genomic technologies to cancer research has already generated exciting results both in target identification and in disease classification. In this article, we review some of the developments pertinent to cancer research, discuss potentially problematic areas associated with them, and comment on future trends and issues.

Blood use during extracorporeal membrane oxygenation.

An analysis of the transfusion records of 91 neonatal patients subjected to extracorporeal membrane oxygenation (ECMO) is reported. Mean daily blood usage was 250 mL of red cells (RBCs), 80 mL of fresh-frozen plasma, and 2 units of platelets. Average time on ECMO was 4.6 days. Group O or ABO type-specific RBCs and group AB or ABO type-specific plasma products and platelets were transfused. RBCs were not washed, and neither RBCs nor other components were tested for anticytomegalovirus (CMV) or irradiated. No cases of posttransfusion CMV infection or graft-versus-host disease were observed. Hemolysis in eight patients was traced to occlusions in the ECMO circuit. All but three patients survived ECMO. Contrary to a previous report, an active ECMO program for neonatal patients imposes a minimal burden on the hospital transfusion service.