HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics

BACKGROUND: Accurate interpretation of data obtained by unsupervised analysis of large scale expression profiling studies is currently frequently performed by visually combining sample-gene heatmaps and sample characteristics. This method is not optimal for comparing individual samples or groups of samples. Here, we describe an approach to visually integrate the results of unsupervised and supervised cluster analysis using a correlation plot and additional sample metadata. RESULTS: We have developed a tool called the HeatMapper that provides such visualizations in a dynamic and flexible manner and is available from . CONCLUSION: The HeatMapper allows an accessible and comprehensive visualization of the results of gene expression profiling and cluster analysis

Epigenetics as a mechanism driving polygenic clinical drug resistance

Aberrant methylation of CpG islands located at or near gene promoters is associated with inactivation of gene expression during tumour development. It is increasingly recognised that such epimutations may occur at a much higher frequency than gene mutation and therefore have a greater impact on selection of subpopulations of cells during tumour progression or acquisition of resistance to anticancer drugs. Although laboratory-based models of acquired resistance to anticancer agents tend to focus on specific genes or biochemical pathways, such 'one gene : one outcome' models may be an oversimplification of acquired resistance to treatment of cancer patients. Instead, clinical drug resistance may be due to changes in expression of a large number of genes that have a cumulative impact on chemosensitivity. Aberrant CpG island methylation of multiple genes occurring in a nonrandom manner during tumour development and during the acquisition of drug resistance provides a mechanism whereby expression of multiple genes could be affected simultaneously resulting in polygenic clinical drug resistance. If simultaneous epigenetic regulation of multiple genes is indeed a major driving force behind acquired resistance of patients' tumour to anticancer agents, this has important implications for biomarker studies of clinical outcome following chemotherapy and for clinical approaches designed to circumvent or modulate drug resistance

Determinants of potential drug–drug interaction associated dispensing in community pharmacies in the Netherlands

OBJECTIVE: There are many drug–drug interactions (D–DI) of which some may cause severe adverse patient outcomes. Dispensing interacting drug combinations should be avoided when the risks are higher than the benefits. The objective of this study was to identify determinants of dispensing undesirable interacting drug combinations by community pharmacies in the Netherlands. METHODS: A total of 256 Dutch community pharmacies were selected, based on the dispensing of 11 undesirable interacting drug combinations between January 1st, 2001 and October 31st, 2002. These pharmacies were sent a questionnaire by the Inspectorate for Health Care (IHC) concerning their process and structure characteristics. MAIN OUTCOME MEASURE: The number of times the 11 undesirable interacting drug combinations were dispensed. RESULTS: Two hundred and forty-six questionnaires (response rate 96.1%) were completed. Dispensing determinants were only found for the D–DI between macrolide antibiotics and digoxin but not for the other 10 D–DIs. Pharmacies using different medication surveillance systems differed in the dispensing of this interacting drug combination, and pharmacies, which were part of a health care centre dispensed this interacting drug combination more often. CONCLUSION: Medication surveillance in Dutch community pharmacies seems to be effective. Although for most D–DIs no determinants were found, process and structure characteristics may have consequences for the dispensing of undesirable interacting drug combinations

A one-mutation mathematical model can explain the age incidence of acute myeloid leukemia with mutated nucleophosmin (NPM1).

Acute myeloid leukemia with mutated NPM1 gene and aberrant cytoplasmic expression of nucleophosmin (NPMc(+) acute myeloid leukemia) shows distinctive biological and clinical features. Experimental evidence of the oncogenic potential of the nucleophosmin mutant is, however, still lacking, and it is unclear whether other genetic lesion(s), e.g. FLT3 internal tandem duplication, cooperate with NPM1 mutations in acute myeloid leukemia development. An analysis of age-specific incidence, together with mathematical modeling of acute myeloid leukemia epidemiology, can help to uncover the number of genetic events needed to cause leukemia. We collected data on age at diagnosis of acute myeloid leukemia patients from five European Centers in Germany, The Netherlands and Italy, and determined the age-specific incidence of AML with mutated NPM1 (a total of 1,444 cases) for each country. Linear regression of the curves representing age-specific rates of diagnosis per year showed similar slopes of about 4 on a double logarithmic scale. We then adapted a previously designed mathematical model of hematopoietic tumorigenesis to analyze the age incidence of acute myeloid leukemia with mutated NPM1 and found that a one-mutation model can explain the incidence curve of this leukemia entity. This model fits with the hypothesis that NPMc(+) acute myeloid leukemia arises from an NPM1 mutation with haploinsufficiency of the wild-type NPM1 allele

The Antioxidant Protein Peroxiredoxin 4 Is Epigenetically Down Regulated in Acute Promyelocytic Leukemia

The antioxidant peroxiredoxin (PRDX) protein family comprises 6 members, which are implicated in a variety of cellular responses, including growth factor signal transduction. PRDX4 resides in the endoplasmic reticulum (ER), where it locally controls oxidative stress by reducing H2O2levels. We recently provided evidence for a regulatory function of PRDX4 in signal transduction from a myeloid growth factor receptor, the granulocyte colony-stimulating factor receptor (G-CSFR). Upon activation, the ligand-induced G-CSFR undergoes endocytosis and routes via the early endosomes where it physically interacts with ER-resident PRDX4. PRDX4 negatively regulates G-CSFR mediated signaling. Here, we investigated whether PRDX4 is affected in acute myeloid leukemia (AML); genomic alterations and expression levels of PRDX4 were investigated. We show that genomic abnormalities involving PRDX4 are rare in AML. However, we find a strong reduction in PRDX4 expression levels in acute promyelocytic leukemia (APL) compared to normal promyelocytes and different molecular subtypes of AML. Subsequently, the possible role of DNA methylation and histone modifications in silencing of PRDX4 in APLs was investigated. We show that the reduced expression is not due to methylation of the CpG island in the promoter region of PRDX4 but correlates with increased trimethylation of histone 3 lysine residue 27 (H3K27me3) and lysine residue 4 (H3K4me3) at the transcriptional start site (TSS) of PRDX4, indicative of a bivalent histone code involved in transcriptional silencing. These findings suggest that the control of G-CSF responses by the antioxidant protein PRDX4 may be perturbed in APL

Gene expression signatures in childhood acute leukemias are largely unique and distinct from those of normal tissues and other malignancies

<p>Abstract</p> <p>Background</p> <p>Childhood leukemia is characterized by the presence of balanced chromosomal translocations or by other structural or numerical chromosomal changes. It is well know that leukemias with specific molecular abnormalities display profoundly different global gene expression profiles. However, it is largely unknown whether such subtype-specific leukemic signatures are unique or if they are active also in non-hematopoietic normal tissues or in other human cancer types.</p> <p>Methods</p> <p>Using gene set enrichment analysis, we systematically explored whether the transcriptional programs in childhood acute lymphoblastic leukemia (ALL) and myeloid leukemia (AML) were significantly similar to those in different flow-sorted subpopulations of normal hematopoietic cells (n = 8), normal non-hematopoietic tissues (n = 22) or human cancer tissues (n = 13).</p> <p>Results</p> <p>This study revealed that e.g., the t(12;21) [<it>ETV6-RUNX1</it>] subtype of ALL and the t(15;17) [<it>PML-RARA</it>] subtype of AML had transcriptional programs similar to those in normal Pro-B cells and promyelocytes, respectively. Moreover, the 11q23/<it>MLL </it>subtype of ALL showed similarities with non-hematopoietic tissues. Strikingly however, most of the transcriptional programs in the other leukemic subtypes lacked significant similarity to ~100 gene sets derived from normal and malignant tissues.</p> <p>Conclusions</p> <p>This study demonstrates, for the first time, that the expression profiles of childhood leukemia are largely unique, with limited similarities to transcriptional programs active in normal hematopoietic cells, non-hematopoietic normal tissues or the most common forms of human cancer. In addition to providing important pathogenetic insights, these findings should facilitate the identification of candidate genes or transcriptional programs that can be used as unique targets in leukemia.</p

Randomization in Laboratory Procedure Is Key to Obtaining Reproducible Microarray Results

The quality of gene expression microarray data has improved dramatically since the first arrays were introduced in the late 1990s. However, the reproducibility of data generated at multiple laboratory sites remains a matter of concern, especially for scientists who are attempting to combine and analyze data from public repositories. We have carried out a study in which a common set of RNA samples was assayed five times in four different laboratories using Affymetrix GeneChip arrays. We observed dramatic differences in the results across laboratories and identified batch effects in array processing as one of the primary causes for these differences. When batch processing of samples is confounded with experimental factors of interest it is not possible to separate their effects, and lists of differentially expressed genes may include many artifacts. This study demonstrates the substantial impact of sample processing on microarray analysis results and underscores the need for randomization in the laboratory as a means to avoid confounding of biological factors with procedural effects

Randomization in Laboratory Procedure Is Key to Obtaining Reproducible Microarray Results

The quality of gene expression microarray data has improved dramatically since the first arrays were introduced in the late 1990s. However, the reproducibility of data generated at multiple laboratory sites remains a matter of concern, especially for scientists who are attempting to combine and analyze data from public repositories. We have carried out a study in which a common set of RNA samples was assayed five times in four different laboratories using Affymetrix GeneChip arrays. We observed dramatic differences in the results across laboratories and identified batch effects in array processing as one of the primary causes for these differences. When batch processing of samples is confounded with experimental factors of interest it is not possible to separate their effects, and lists of differentially expressed genes may include many artifacts. This study demonstrates the substantial impact of sample processing on microarray analysis results and underscores the need for randomization in the laboratory as a means to avoid confounding of biological factors with procedural effects

Autocrine Activation of the MET Receptor Tyrosine Kinase in Acute Myeloid Leukemia

Although the treatment of acute myeloid leukemia (AML) has improved significantly, more than half of all patients develop disease that is refractory to intensive chemotherapy. Functional genomics approaches offer a means to discover specific molecules mediating aberrant growth and survival of cancer cells. Thus, using a loss-of-function RNA interference genomic screen, we identified aberrant expression of the hepatocyte growth factor (HGF) as a critical factor in AML pathogenesis. We found HGF expression leading to autocrine activation of its receptor tyrosine kinase, MET, in nearly half of the AML cell lines and clinical samples studied. Genetic depletion of HGF or MET potently inhibited the growth and survival of HGF-expressing AML cells. However, leukemic cells treated with the specific MET kinase inhibitor crizotinib developed resistance due to compensatory upregulation of HGF expression, leading to restoration of MET signaling. In cases of AML where MET is coactivated with other tyrosine kinases, such as fibroblast growth factor receptor 1 (FGFR1), concomitant inhibition of FGFR1 and MET blocked compensatory HGF upregulation, resulting in sustained logarithmic cell kill both in vitro and in xenograft models in vivo. Our results demonstrate widespread dependence of AML cells on autocrine activation of MET, as well as the importance of compensatory upregulation of HGF expression in maintaining leukemogenic signaling by this receptor. We anticipate that these findings will lead to the design of additional strategies to block adaptive cellular responses that drive compensatory ligand expression as an essential component of the targeted inhibition of oncogenic receptors in human cancers