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.

Effects of oxidized and glycated LDL on gene expression in human retinal capillary pericytes

Modified (oxidized and/or glycated) low-density lipoproteins (LDLs) have been implicated in retinal pericyte loss, one of the major pathologic features of early-stage diabetic retinopathy. To delineate underlying molecular mechanisms, the present study was designed to explore the global effects of modified LDL on pericyte gene expression.

TGFβ and CCN2/CTGF mediate actin related gene expression by differential E2F1/CREB activation

CCN2/CTGF is an established effector of TGFß driven responses in diabetic nephropathy. We have identified an interaction between CCN2 and TGFß leading to altered phenotypic differentiation and inhibited cellular migration. Here we determine the gene expression profile associated with this phenotype and define a transcriptional basis for differential actin related gene expression and cytoskeletal function.

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.

Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors

The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I) observational gene expression data: normal environmental condition, (II) interventional gene expression data: growth in rich media, (III) interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

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.

Gene expression in normal Urothelium depends on location within the bladder:A possible link to bladder carcinogenesis

Objectives: Clinical studies have shown that more than 70% of primary bladder tumours arise in the area around the ureteric orifice. In this study a genomic approach was taken to explore the molecular mechanisms that may influence this phenomenon.

Methods: RNA was isolated from each individual normal ureteric orifice and the dome biopsy from 33 male patients. Equal amounts of the pooled ureteric orifice and dome mRNAs were labelled with Cy3 and Cy5, respectively before hybridising to the gene chip (UniGEM 2.0, Incyte Genomics Inc., Wilmington, Delaware, USA). Results: Significant changes (more than a twofold difference) in gene expression were observed in 3.1% (312) of the 10,176 gene array: 211 genes upregulated and 101 downregulated. Analysis of Cdc25B, TK1, PKM, and PDGFra with RT-PCR supported the reliability of the microarray result. Seladin-1 was the most upregulated gene in the ureteric orifice: 8.3-fold on the microarray and 11.4-fold by real time PCR.

Conclusions: Overall, this study suggests significant altered gene expression between these two anatomically distinct areas of the normal human bladder. Of particular note is Seladin-1, whose significance in cancer is yet to be clarified. Further studies of the genes discovered by this work will help clarify which of these differences influence primary bladder carcinogenesis. (c) 2006 European Association of Urology. Published by Elsevier B.V. All rights reserved.