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 r(2) correlation analyses demonstrated that microarray analysis can be performed with remarkably high intra-laboratory reproducibility and with comparable quality and reliability.

Regulation of erythropoietin gene expression depends on two different oxygen-sensing mechanisms

Erythropoietin (Epo), a glycoprotein hormone produced principally in the fetal kidney and in the adult liver in response to hypoxia, is the prime regulator of growth and differentiation in erythroid progenitor cells. The regulation of Epo gene expression is not fully understood, but two mechanisms have been proposed. One involves the participation of a heme protein capable of reversible oxygenation and the other depends on the intracellular concentration of reactive oxygen species (ROS), assumed to be a function of pO2. We have investigated the production of Epo in response to three stimuli, hypoxia, cobalt chloride, and the iron chelator desferrioxamine, in Hep3B cells. As expected, hypoxia caused a marked rise in Epo production. When the cells were exposed to the paired stimuli of hypoxia and cobalt no further increase was found. In contrast, chelation of iron under hypoxic conditions markedly enhanced Epo production, suggesting that the two stimuli act by separate pathways. The addition of carbon monoxide inhibited hypoxia-induced Epo production, independent of desferrioxamine concentration. Taken together these data support the concept that pO2 and ROS are sensed independently.

Localization of erythropoietin gene expression in proximal renal tubular cells detected by digoxigenin-labelled oligonucleotide probes

Erythropoietin (EPO) is the main humoral stimulus of erythropoiesis. In adult mammals, the kidney releases EPO in response to hypoxic stress. Conflicting data have suggested either renal tubular or peritubular cell origins of EPO synthesis in vivo. In situ hybridization studies were performed to define further the kidney cell type(s) capable of increasing EPO gene expression during hypoxic stimulation. EPO gene expression was stimulated in mice exposed to acute hypobaric hypoxia. Kidneys from hypoxic and control normoxic mice were obtained. Six digoxigenin-labelled oligonucleotide probes complementary to EPO exon sequences were utilized for in situ hybridization for EPO messenger RNA. Positive hybridization signals were identified in some proximal tubular cells, confined to the inner third of the renal cortex of hypoxic mouse kidney.

Oxidised, glycated LDL selectively influences tissue inhibitor of metalloproteinase-3 gene expression and protein production in human retinal capillary pericytes

Aims/hypothesis: Matrix metalloproteinases (MMPs) and their natural inhibitors, tissue inhibitor of metalloproteinases (TIMPs), regulate important biological processes including the homeostasis of the extracellular matrix, proteolysis of cell surface proteins, proteinase zymogen activation, angiogenesis and inflammation. Studies have shown that their balance is altered in retinal microvascular tissues in diabetes. Since LDLs modified by oxidation/glycation are implicated in the pathogenesis of diabetic vascular complications, we examined the effects of modified LDL on the gene expression and protein production of MMPs and TIMPs in retinal pericytes. Methods: Quiescent human retinal pericytes were exposed to native LDL (N-LDL), glycated LDL (G-LDL) and heavily oxidised and glycated LDL (HOG-LDL) for 24 h. We studied the expression of the genes encoding MMPs and TIMPs mRNAs by analysis of microarray data and quantitative PCR, and protein levels by immunoblotting and ELISA. Results: Microarray analysis showed that MMP1, MMP2, MMP11, MMP14 and MMP25 and TIMP1, TIMP2, TIMP3 and TIMP4 were expressed in pericytes. Of these, only TIMP3 mRNA showed altered regulation, being expressed at significantly lower levels in response to HOG- vs N-LDL. Quantitative PCR and immunoblotting of cell/matrix proteins confirmed the reduction in TIMP3 mRNA and protein in response to HOG-LDL. In contrast to cellular TIMP3 protein, analysis of secreted TIMP1, TIMP2, MMP1 and collagenase activity indicated no changes in their production in response to modified LDL. Combined treatment with N- and HOG-LDL restored TIMP3 mRNA expression to a level comparable with that after N-LDL alone. Conclusions/interpretation: Among the genes encoding for MMPs and TIMPs expressed in retinal pericytes, TIMP3 is uniquely regulated by HOG-LDL. Reduced TIMP3 expression might contribute to microvascular abnormalities in diabetic retinopathy. © 2007 Springer-Verlag.

Identification of Gene Expression-Based Prognostic Markers in the Hematopoietic Stem Cells of Patients With Myelodysplastic Syndromes

The diagnosis of patients with myelodysplastic syndromes (MDS) is largely dependent on morphologic examination of bone marrow aspirates. Several criteria that form the basis of the classifications and scoring systems most commonly used in clinical practice are affected by operator-dependent variation. To identify standardized molecular markers that would allow prediction of prognosis, we have used gene expression profiling (GEP) data on CD34+ cells from patients with MDS to determine the relationship between gene expression levels and prognosis.

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

Cytosolic phospholipase A2 gene expression in rat mesangial cells is regulated post-transcriptionally

Cytosolic phospholipase A2 (cPLA2) is thought to be the rate-limiting enzyme in the arachidonic acid/eicosanoid cascade. The ability of various agonists to increase steady-state cPLA2 mRNA levels has previously been reported. The current study delineates the contributions of transcriptional and post-transcriptional processes to the regulation of cPLA2 gene expression in response to a variety of agonists in cultured rat glomerular mesangial cells. Epidermal growth factor, platelet-derived growth factor, serum and phorbol myristate acetate all increase the half-life of cPLA2 mRNA transcripts, indicating a role for post-transcriptional modulation of gene expression. The presence of three ATTTA motifs in the 3' untranslated region (3'UTR) of the rat cPLA2 cDNA is ascertained. Heterologous expression of chimeric constructs with different 3'UTRs ligated into the 3' end of the luciferase coding region reveals that the presence of the cPLA2 3'UTR results in reduced luciferase activity compared with constructs without the cPLA2 3'UTR. Furthermore, the luciferase activity in the constructs with the cPLA2 3'UTR is increased in response to the same agonists which stabilize endogenous cPLA2 mRNA. A negligible effect of these agonists on transcriptional control of cPLA2 is evident using promoter-reporter constructs expressed in transient and stable transfectants. Taken together, these results indicate predominant post-transcriptional regulation of cPLA2 mRNA levels.

Convergent genetic and expression data implicate immunity in Alzheimer's disease

Background: Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis.

Methods: The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain.

Results: ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 X 10(-12) after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 X 10(-11)), cholesterol transport (P = 2.96 X 10(-9)), and proteasome-ubiquitin activity (P = 1.34 X 10(-6)). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002-.05).

Conclusions: The immime response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics. (C) 2015 Published by Elsevier Inc. on behalf of The Alzheimer's Association.

Characterization of a reference material for BCR-ABL (M-BCR) mRNA quantitation by real-time amplification assays:towards new standards for gene expression measurements

Monitoring of BCR-ABL transcripts has become established practice in the management of chronic myeloid leukemia. However, nucleic acid amplification techniques are prone to variations which limit the reliability of real-time quantitative PCR (RQ-PCR) for clinical decision making, highlighting the need for standardization of assays and reporting of minimal residual disease (MRD) data. We evaluated a lyophilized preparation of a leukemic cell line (K562) as a potential quality control reagent. This was found to be relatively stable, yielding comparable respective levels of ABL, GUS and BCR-ABL transcripts as determined by RQ-PCR before and after accelerated degradation experiments as well as following 5 years storage at -20 degrees C. Vials of freeze-dried cells were sent at ambient temperature to 22 laboratories on four continents, with RQ-PCR analyses detecting BCR-ABL transcripts at levels comparable to those observed in primary patient samples. Our results suggest that freeze-dried cells can be used as quality control reagents with a range of analytical instrumentations and could enable the development of urgently needed international standards simulating clinically relevant levels of MRD.

Histone deacetylase inhibitors suppress thymidylate synthase gene expression and synergize with the fluoropyrimidines in colon cancer cells

Despite recent therapeutic advances, the response rates to chemotherapy for patients with metastatic colon cancer remain at approximately 50% with the fluoropyrimidine, 5-fluorouracil (5-FU), continuing to serve as the foundation chemotherapeutic agent for the treatment of this disease. Previous studies have demonstrated that overexpression of thymidylate synthase (TS) is a key determinant of resistance to 5-FU-based chemotherapy. Therefore, there is a significant need to develop alternative therapeutic strategies to overcome TS-mediated resistance. In this study, we demonstrate that the histone deacetylase inhibitors (HDACi) vorinostat and LBH589 significantly downregulate TS gene expression in a panel of colon cancer cell lines. Downregulation of TS was independent of p53, p21 and HDAC2 expression and was achievable in vivo as demonstrated by mouse xenograft models. We provide evidence that HDACi treatment leads to a potent transcriptional repression of the TS gene. Combination of the fluoropyrimidines 5-FU or FUdR with both vorinostat and LBH589 enhanced cell cycle arrest and growth inhibition. Importantly, the downstream effects of TS inhibition were significantly enhanced by this combination including the inhibition of acute TS induction and the enhanced accumulation of the cytotoxic nucleotide intermediate dUTP. These data demonstrate that HDACi repress TS expression at the level of transcription and provides the first evidence suggesting a direct mechanistic link between TS downregulation and the synergistic interaction observed between HDACi and 5-FU. This study provides rationale for the continued clinical evaluation of HDACi in combination with 5-FU-based therapies as a strategy to overcome TS-mediated resistance.

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics

Background: Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. Results: We describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts.Conclusions: QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions.

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.

Molecular characterization of Gla-rich protein (GRP) gene expression and function

Gla-rich protein (GRP) is a vitamin K-dependent protein related to bone and cartilage recently described. This protein is characterized by a large number of Gla (γ-carboxyglutamic acid) residues being the protein with the highest Gla content of any known protein. It was found in a widely variety of tissues but highest levels was found in skeletal and cartilaginous tissues. This small secreted protein was also expressed and accumulated in soft tissues and it was clearly associated with calcification pathologies in the same tissues. Although the biological importance of GRP remains to be elucidated, it was suggested a physiological role in cartilage development and calcification process during vertebrate skeleton formation. Using zebrafish, an accepted model to study skeletal development, we have described two grp paralog genes, grp1 and grp2, which exhibited distinct patterns of expression, suggesting different regulatory pathways for each gene. Gene synteny analysis showed that grp2 gene is more closely related to tetrapod grp, although grp1 gene was proposed to be the vertebrate ortholog by sequence comparison. In addition, we identified a functional promoter of grp2 gene and using a functional approach we confirmed the involvement of transcription factors from Sox family (Sox9b and Sox10) in the regulation of grp2 expression. In an effort to provide more information about the function of grp isoforms, we generated two zebrafish transgenic lines capable to overexpress conditionally grp genes and possible roles in the skeleton development were studied. To better understand GRP function a mammalian system was used and the analysis of knockout mice showed that GRP is involved in chondrocyte maturation and the absence of GRP is associated to proteoglycans loss in calcified articular cartilage. In addition, we detected differences in chondrogenesis markers in articular chondrocyte primary culture. Overall, our data suggest a main role for GRP on chondrocyte differentiation.

An atlas of human gene expression from massively parallel signature sequencing (MPSS).

We have used massively parallel signature sequencing (MPSS) to sample the transcriptomes of 32 normal human tissues to an unprecedented depth, thus documenting the patterns of expression of almost 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences in gene expression between cell and tissue types are largely determined by transcripts derived from a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little more than half of all known human genes seems to account for both the common requirements and the specific functions of the tissues sampled. A classification of tissues based on patterns of gene expression largely reproduces classifications based on anatomical and biochemical properties. The unbiased sampling of the human transcriptome achieved by MPSS supports the idea that most human genes have been mapped, if not functionally characterized. This data set should prove useful for the identification of tissue-specific genes, for the study of global changes induced by pathological conditions, and for the definition of a minimal set of genes necessary for basic cell maintenance. The data are available on the Web at http://mpss.licr.org and http://sgb.lynxgen.com.

Impact of a cis-associated gene expression SNP on chromosome 20q11.22 on bipolar disorder susceptibility, hippocampal structure and cognitive performance.

BackgroundBipolar disorder is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for bipolar disorder in the expression quantitative trait loci (eQTL) in the brain.AimsWe sought to assess the impact of eQTL variants on bipolar disorder risk by combining data from both bipolar disorder genome-wide association studies (GWAS) and brain eQTL.MethodTo detect single nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with bipolar disorder, we jointly analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (n = 5775) and cognitive performance (n = 342) among healthy individuals.ResultsIntegrative analysis revealed a significant association between a brain eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes factor = 5.48; bipolar disorder P = 5.85×10(-5)). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and bipolar disorder susceptibility (P = 3.54×10(-8)). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy individuals.ConclusionsOur findings suggest that 20q11.22 is likely a risk region for bipolar disorder; they also highlight the informative value of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex disorders, such as bipolar disorder.