Activated oncogenic pathways and therapeutic targets in extranodal nasal-type NK/T cell lymphoma revealed by gene expression profiling

We performed comprehensive genome-wide gene expression profiling (GEP) of extranodal nasal-type natural killer/T-cell lymphoma (NKTL) using formalin-fixed, paraffin-embedded tissue (n = 9) and NK cell lines (n = 5) in comparison with normal NK cells, with the objective of understanding the oncogenic pathways involved in the pathogenesis of NKTL and to identify potential therapeutic targets. Pathway and network analysis of genes differentially expressed between NKTL and normal NK cells revealed significant enrichment for cell cycle-related genes and pathways, such as PLK1, CDK1, and Aurora-A. Furthermore, our results demonstrated a pro-proliferative and anti-apoptotic phenotype in NKTL characterized by activation of Myc and nuclear factor kappa B (NF-kappa B), and deregulation of p53. In corroboration with GEP findings, a significant percentage of NKTLs (n = 33) overexpressed c-Myc (45.4%), p53 (87.9%), and NF-kappa B p50 (67.7%) on immunohistochemistry using a tissue microarray containing 33 NKTL samples. Notably, overexpression of survivin was observed in 97% of cases. Based on our findings, we propose a model of NKTL pathogenesis where deregulation of p53 together with activation of Myc and NF-kappa B, possibly driven by EBV LMP-1, results in the cumulative up-regulation of survivin. Down-regulation of survivin with Terameprocol (EM-1421, a survivin inhibitor) results in reduced cell viability and increased apoptosis in tumour cells, suggesting that targeting survivin may be a potential novel therapeutic strategy in NKTL. Copyright (C) 2011 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Differences in Mucosal Gene Expression in the Colon of Two Inbred Mouse Strains after Colonization with Commensal Gut Bacteria

The host genotype has been proposed to contribute to individually composed bacterial communities in the gut. To provide deeper insight into interactions between gut bacteria and host, we associated germ-free C3H and C57BL/10 mice with intestinal bacteria from a C57BL/10 donor mouse. Analysis of microbiota similarity between the animals with denaturing gradient gel electrophoresis revealed the development of a mouse strain-specific microbiota. Microarray-based gene expression analysis in the colonic mucosa identified 202 genes whose expression differed significantly by a factor of more than 2. Application of bioinformatics tools demonstrated that functional terms including signaling/secretion, lipid degradation/catabolism, guanine nucleotide/guanylate binding and immune response were significantly enriched in differentially expressed genes. We had a closer look at the 56 genes with expression differences of more than 4 and observed a higher expression in C57BL/10 mice of the genes coding for Tlr1 and Ang4 which are involved in the recognition and response to gut bacteria. A higher expression of Pla2g2a was detected in C3H mice. In addition, a number of interferon-inducible genes were higher expressed in C3H than in C57BL/10 mice including Gbp1, Mal, Oasl2, Ifi202b, Rtp4, Ly6g6c, Ifi27l2a, Usp18, Ifit1, Ifi44, and Ly6g indicating that interferons may play an essential role in microbiota regulation. However, genes coding for interferons, their receptors, factors involved in interferon expression regulation or signaling pathways were not differentially expressed between the two mouse strains. Taken together, our study confirms that the host genotype is involved in the establishment of host-specific bacterial communities in the gut. Based on expression differences after colonization with the same bacterial inoculum, we propose that Pla2g2a and interferon-dependent genes may contribute to this phenomenon.

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.

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.

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.

Identification of lactic acid bacteria strains modulating incretin hormone secretion and gene expression in enteroendocrine cells

Glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are incretin hormones released from intestinal enteroendocrine (EE) cells and have well-established glucose-lowering actions. Lactic acid bacteria (LAB) colonise the human intestine, but it is unknown whether LAB and EE cells interact. Acute co-culture of LAB with EE cells showed that certain LAB strains elicit GLP-1 and GIP secretion (13-194-fold) and upregulate their gene expression. LAB-induced incretin hormone secretion did not appear to involve nutrient mechanisms, nor was there any evidence of cytolysis. Instead PCR array studies implicated signalling agents of the toll-like receptor system, e.g. adaptor protein MyD88 was decreased 23-fold and cell surface antigen CD14 was increased 17-fold. Mechanistic studies found that blockade of MyD88 triggered significant GLP-1 secretion. Furthermore, blocking of CD14 completely attenuated LAB-induced secretion. A recent clinical trial clearly shows that LAB have potential for alleviating type 2 diabetes, and further characterisation of this bioactivity is warranted.

IGFBP7 promoter methylation and gene expression analysis in prostate cancer

PURPOSE: IGFBP7 belongs to a family of insulin-like growth factor-1 regulatory binding proteins. IGFBP7 hypermethylation is associated with its down-regulation in various carcinomas. In prostate cancer IGFBP7 down-regulation has been widely reported but to our knowledge the mechanisms behind this event are unknown. We performed a denaturing high performance liquid chromatography screening and validation strategy to profile the methylation status of IGFBP7 in prostate cancer.

MATERIALS AND METHODS: We combined denaturing high performance liquid chromatography and bisulfite sequencing to examine IGFBP7 methylation in a panel of prostate cancer cell lines. Quantitative methylation specific polymerase chain reaction was used to determine methylation levels in prostate tissue specimens of primary prostate cancer, histologically benign prostate adjacent to tumor, high grade prostatic intraepithelial neoplasia and benign prostatic hyperplasia. IGFBP7 gene expression was measured by quantitative methylation specific polymerase chain reaction in cell lines and tissue specimens.

RESULTS: IGFBP7 was methylated in the 4 prostate cancer cell lines DU145, LNCaP, PC-3 and 22RV1. Quantitative methylation specific polymerase chain reaction analysis revealed that promoter methylation was associated with decreased IGFBP7 expression. Quantitative methylation specific polymerase chain reaction showed that IGFBP7 methylation was more frequently detected in prostate cancer (60% (31/52)) and high grade prostatic intraepithelial neoplasia (40% (6/15)) samples compared to histologically benign prostate adjacent to tumor (10%) and benign prostatic hyperplasia (0%) samples.

CONCLUSIONS: To our knowledge this is the first report of aberrant IGFBP7 promoter hypermethylation and concurrent IGFBP7 gene silencing in prostate cancer cell lines. Results demonstrate that CpG methylation of IGFBP7 may represent a novel biomarker of prostate cancer and pre-invasive neoplasms. Thus, future examination of IGFBP7 methylation and expression in a larger patient cohort, including bodily fluids, is justified to further evaluate its role in a diagnostic and prognostic setting.

Integrative analysis of chemo-transcriptomic profiles for drug-feature specific gene expression signatures

One of the major challenges in systems biology is to understand the complex responses of a biological system to external perturbations or internal signalling depending on its biological conditions. Genome-wide transcriptomic profiling of cellular systems under various chemical perturbations allows the manifestation of certain features of the chemicals through their transcriptomic expression profiles. The insights obtained may help to establish the connections between human diseases, associated genes and therapeutic drugs. The main objective of this study was to systematically analyse cellular gene expression data under various drug treatments to elucidate drug-feature specific transcriptomic signatures. We first extracted drug-related information (drug features) from the collected textual description of DrugBank entries using text-mining techniques. A novel statistical method employing orthogonal least square learning was proposed to obtain drug-feature-specific signatures by integrating gene expression with DrugBank data. To obtain robust signatures from noisy input datasets, a stringent ensemble approach was applied with the combination of three techniques: resampling, leave-one-out cross validation, and aggregation. The validation experiments showed that the proposed method has the capacity of extracting biologically meaningful drug-feature-specific gene expression signatures. It was also shown that most of signature genes are connected with common hub genes by regulatory network analysis. The common hub genes were further shown to be related to general drug metabolism by Gene Ontology analysis. Each set of genes has relatively few interactions with other sets, indicating the modular nature of each signature and its drug-feature-specificity. Based on Gene Ontology analysis, we also found that each set of drug feature (DF)-specific genes were indeed enriched in biological processes related to the drug feature. The results of these experiments demonstrated the pot- ntial of the method for predicting certain features of new drugs using their transcriptomic profiles, providing a useful methodological framework and a valuable resource for drug development and characterization.

Meta-analysis of prostate cancer gene expression data identifies a novel discriminatory signature enriched for glycosylating enzymes

BACKGROUND: Tumorigenesis is characterised by changes in transcriptional control. Extensive transcript expression data have been acquired over the last decade and used to classify prostate cancers. Prostate cancer is, however, a heterogeneous multifocal cancer and this poses challenges in identifying robust transcript biomarkers.

METHODS: In this study, we have undertaken a meta-analysis of publicly available transcriptomic data spanning datasets and technologies from the last decade and encompassing laser capture microdissected and macrodissected sample sets.

RESULTS: We identified a 33 gene signature that can discriminate between benign tissue controls and localised prostate cancers irrespective of detection platform or dissection status. These genes were significantly overexpressed in localised prostate cancer versus benign tissue in at least three datasets within the Oncomine Compendium of Expression Array Data. In addition, they were also overexpressed in a recent exon-array dataset as well a prostate cancer RNA-seq dataset generated as part of the The Cancer Genomics Atlas (TCGA) initiative. Biologically, glycosylation was the single enriched process associated with this 33 gene signature, encompassing four glycosylating enzymes. We went on to evaluate the performance of this signature against three individual markers of prostate cancer, v-ets avian erythroblastosis virus E26 oncogene homolog (ERG) expression, prostate specific antigen (PSA) expression and androgen receptor (AR) expression in an additional independent dataset. Our signature had greater discriminatory power than these markers both for localised cancer and metastatic disease relative to benign tissue, or in the case of metastasis, also localised prostate cancer.

CONCLUSION: In conclusion, robust transcript biomarkers are present within datasets assembled over many years and cohorts and our study provides both examples and a strategy for refining and comparing datasets to obtain additional markers as more data are generated.

Association Between Results of a Gene Expression Signature Assay and Recurrence-Free Interval in Patients With Stage II Colon Cancer in Cancer and Leukemia Group B 9581 (Alliance)

PURPOSE: Conventional staging methods are inadequate to identify patients with stage II colon cancer (CC) who are at high risk of recurrence after surgery with curative intent. ColDx is a gene expression, microarray-based assay shown to be independently prognostic for recurrence-free interval (RFI) and overall survival in CC. The objective of this study was to further validate ColDx using formalin-fixed, paraffin-embedded specimens collected as part of the Alliance phase III trial, C9581.

PATIENTS AND METHODS: C9581 evaluated edrecolomab versus observation in patients with stage II CC and reported no survival benefit. Under an initial case-cohort sampling design, a randomly selected subcohort (RS) comprised 514 patients from 901 eligible patients with available tissue. Forty-nine additional patients with recurrence events were included in the analysis. Final analysis comprised 393 patients: 360 RS (58 events) and 33 non-RS events. Risk status was determined for each patient by ColDx. The Self-Prentice method was used to test the association between the resulting ColDx risk score and RFI adjusting for standard prognostic variables.

RESULTS: Fifty-five percent of patients (216 of 393) were classified as high risk. After adjustment for prognostic variables that included mismatch repair (MMR) deficiency, ColDx high-risk patients exhibited significantly worse RFI (multivariable hazard ratio, 2.13; 95% CI, 1.3 to 3.5; P < .01). Age and MMR status were marginally significant. RFI at 5 years for patients classified as high risk was 82% (95% CI, 79% to 85%), compared with 91% (95% CI, 89% to 93%) for patients classified as low risk.

CONCLUSION: ColDx is associated with RFI in the C9581 subsample in the presence of other prognostic factors, including MMR deficiency. ColDx could be incorporated with the traditional clinical markers of risk to refine patient prognosis.

High glucose decreases intracellular glutathione concentrations and upregulates inducible nitric oxide synthase gene expression in intestinal epithelial cells

Diabetes is associated with oxidative stress and increased levels of inflammatory cytokines. The aim of the study was to assess the effects of inflammatory cytokines and oxidative stress associated with raised glucose levels on inducible nitric oxide synthase (iNOS) promoter activity in intestinal epithelial cells. High glucose (25 mmol/l) conditions reduced glutathione (GSH) levels in the human intestinal epithelial cell line, DLD-1. Addition of the antioxidant alpha-lipoic acid resulted in the restoration of GSH levels to normal. Upregulation of basal iNOS promoter activity was observed when cells were incubated in high glucose alone. This effect was significantly reduced by the addition of the antioxidant, alpha-lipoic acid and completely blocked with inhibition of NFkappa B activity. Cytokine stimulation [interleukin-1 beta, tumor necrosis factor-alpha, interferon-gamma] induced iNOS promoter activity in all conditions and this was accompanied by an increase in nitric oxide (NO) production. Inhibition of NFkappa-B activity decreased but did not completely inhibit cytokine-induced iNOS promoter activity and subsequent NO production. In conclusion, high glucose-induced iNOS promoter activity is mediated in part through intracellular GSH and NFkappa-B.