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.

p53 pathway dysfunction is highly prevalent in acute myeloid leukemia independent of TP53 mutational status.

TP53 mutations are associated with the lowest survival rates in acute myeloid leukemia (AML). In addition to mutations, loss of p53 function can arise via aberrant expression of proteins that regulate p53 stability and function. We examined a large AML cohort using proteomics, mutational profiling and network analyses, and showed that (1) p53 stabilization is universal in mutant TP53 samples, it is frequent in samples with wild-type TP53, and in both cases portends an equally dismal prognosis; (2) the p53 negative regulator Mdm2 is frequently overexpressed in samples retaining wild-type TP53 alleles, coupled with absence of p21 expression and dismal prognosis similar to that of cases with p53 stabilization; (3) AML samples display unique patterns of p53 pathway protein expression, which segregate prognostic groups with distinct cure rates; (4) such patterns of protein activation unveil potential AML vulnerabilities that can be therapeutically exploited.

Expression profiling stratifies mesothelioma tumors and signifies deregulation of spindle checkpoint pathway and microtubule network with therapeutic implications.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a lethal neoplasm exhibiting resistance to most treatment regimens and requires effective therapeutic options. Though an effective strategy in many cancer, targeted therapy is relatively unexplored in MPM because the therapeutically important oncogenic pathways and networks in MPM are largely unknown. MATERIALS AND METHODS: We carried out gene expression microarray profiling of 53 surgically resected MPMs tumors along with paired normal tissue. We also carried out whole transcriptomic sequence (RNA-seq) analysis on eight tumor specimens. Taqman-based quantitative Reverse-transcription polymerase chain reaction (qRT-PCR), western analysis and immunohistochemistry (IHC) analysis of mitotic arrest deficient-like 1 (MAD2L1) was carried out on tissue specimens. Cell viability assays of MPM cell lines were carried out to assess sensitivity to specific small molecule inhibitors. RESULTS: Bioinformatics analysis of the microarray data followed by pathway analysis revealed that the mitotic spindle assembly checkpoint (MSAC) pathway was most significantly altered in MPM tumors with upregulation of 18 component genes, including MAD2L1 gene. We validated the microarray data for MAD2L1 expression using quantitative qRT-PCR and western blot analysis on tissue lysates. Additionally, we analyzed expression of the MAD2L1 protein by IHC using an independent tissue microarray set of 80 MPM tissue samples. Robust clustering of gene expression data revealed three novel subgroups of tumors, with unique expression profiles, and showed differential expression of MSAC pathway genes. Network analysis of the microarray data showed the cytoskeleton/spindle microtubules network was the second-most significantly affected network. We also demonstrate that a nontaxane small molecule inhibitor, epothilone B, targeting the microtubules have great efficacy in decreasing viability of 14 MPM cell lines. CONCLUSIONS: Overall, our findings show that MPM tumors have significant deregulation of the MSAC pathway and the microtubule network, it can be classified into three novel molecular subgroups of potential therapeutic importance and epothilone B is a promising therapeutic agent for MPM.

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.

HOX expression patterns identify a common signature for favorable AML.

Deregulated HOX expression, by chromosomal translocations and myeloid-lymphoid leukemia (MLL) rearrangements, is causal in some types of leukemia. Using real-time reverse transcription-PCR, we examined the expression of 43 clustered HOX, polycomb, MLL and FLT3 genes in 119 newly diagnosed adult acute myeloid leukemias (AMLs) selected from all major cytogenetic groups. Downregulated HOX expression was a consistent feature of favorable AMLs and, among these cases, inv(16) cases had a distinct expression profile. Using a 17-gene predictor in 44 additional samples, we observed a 94.7% specificity for classifying favorable vs intermediate/unfavorable cytogenetic groups. Among other AMLs, HOX overexpression was associated with nucleophosmin (NPM) mutations and we also identified a phenotypically similar subset with wt-NPM. In many unfavorable and other intermediate cytogenetic AMLs, HOX levels resembled those in normal CD34+ cells, except that the homogeneity characteristic of normal samples was not present. We also observed that HOXA9 levels were significantly inversely correlated with survival and that BMI-1 was overexpressed in cases with 11q23 rearrangements, suggesting that p19(ARF) suppression may be involved in MLL-associated leukemia. These results underscore the close relationship between HOX expression patterns and certain forms of AML and emphasize the need to determine whether these differences play a role in the disease process.

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.

Sequence verification as quality-control step for production of cDNA microarrays.

To generate cDNA arrays in our core laboratory, we amplified about 2300 PCR products from a human, sequence-verified cDNA clone library. As a quality-control step, we sequenced the PCR products immediately before printing. The sequence information was used to search the GenBank database to confirm the identities. Although these clones were previously sequence verified by the company, we found that only 79% of the clones matched the original database after handling. Our experience strongly indicates the necessity to sequence verify the clones at the final stage before printing on microarray slides and to modify the gene list accordingly.

The accuracy of predictions about progress of patients on a stroke unit.

The aim of the study was to check the accuracy of predictions about the factors which affect the progress, in physical abilities and activities of daily living, of patients admitted to a stroke unit. A series of 60 patients admitted consecutively to a stroke unit were assessed on tests of motor, functional and cognitive abilities at admission. On the basis of these assessments predictions were made about the abilities of the patients at discharge. Patients were assessed for level of motor abilities and activities of daily living at discharge and the accuracy of the predictions checked. Predictions were found to be significantly correlated with outcome but the relationships were not so close as to be useful for the clinical management of individual patients.

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.