Stromal upregulation of lateral epithelial adhesions : gene expression analysis of signalling pathways in prostate epithelium

BACKGROUND: Stromal signalling increases the lateral cell adhesions of prostate epithelial cells grown in 3D culture. The aim of this study was to use microarray analysis to identify significant epithelial signalling pathways and genes in this process. METHODS: Microarray analysis was used to identify genes that were differentially expressed when epithelial cells were grown in 3D Matrigel culture with stromal co-culture compared to without stroma. Two culture models were employed: primary epithelial cells (ten samples) and an epithelial cell line (three experiments). A separate microarray analysis was performed on each model system and then compared to identify tissue-relevant genes in a cell line model. RESULTS: TGF beta signalling was significantly ranked for both model systems and in both models the TGF beta signalling gene SOX4 was significantly down regulated. Analysis of all differentially expressed genes to identify genes that were common to both models found several morphology related gene clusters; actin binding (DIAPH2, FHOD3, ABLIM1, TMOD4, MYH10), GTPase activator activity (BCR, MYH10), cytoskeleton (MAP2, MYH10, TMOD4, FHOD3), protein binding (ITGA6, CD44), proteinaceous extracellular matrix (NID2, CILP2), ion channel/ ion transporter activity (CACNA1C, CACNB2, KCNH2, SLC8A1, SLC39A9) and genes associated with developmental pathways (POFUT1, FZD2, HOXA5, IRX2, FGF11, SOX4, SMARCC1). CONCLUSIONS: In 3D prostate cultures, stromal cells increase lateral epithelial cell adhesions. We show that this morphological effect is associated with gene expression changes to TGF beta signalling, cytoskeleton and anion activity.

A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in multiple sclerosis

Background Several lines of evidence suggests that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but a complete mapping the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors which may be involved in one subtype may not be in others. We investigated the possibility that this network could be mapped using microarray technologies and modern bioinformatics methods on a dataset from whole blood in 99 untreated MS patients (36 Relapse Remitting MS, 43 Primary Progressive MS, and 20 Secondary Progressive MS) and 45 age-matched healthy controls, Methodology/Principal Findings We have used two different analytical methodologies: a differential expression analysis and a differential co-expression analysis, which have converged on a significant number of regulatory motifs that seem to be statistically overrepresented in genes which are either differentially expressed (or differentially co-expressed) in cases and controls (e.g. V$KROX_Q6, p-value < 3.31E-6; V$CREBP1_Q2, p-value < 9.93E-6, V$YY1_02, p-value < 1.65E-5). Conclusions/significance: Our analysis uncovered a network of transcription factors that potentially dysregulate several genes in MS or one or more of its disease subtypes. Analysing the published literature we have found that these transcription factors are involved in the early T-lymphocyte specification and commitment as well as in oligodendrocytes dedifferentiation and development. The most significant transcription factors motifs were for the Early Growth response EGR/KROX family, ATF2, YY1 (Yin and Yang 1), E2F-1/DP-1 and E2F-4/DP-2 heterodimers, SOX5, and CREB and ATF families.

Design, construction, and analysis of cell line arrays and tissue microarrays for gene expression analysis

Cell line array (CMA) and tissue microarray (TMA) technologies are high-throughput methods for analysing both the abundance and distribution of gene expression in a panel of cell lines or multiple tissue specimens in an efficient and cost-effective manner. The process is based on Kononen's method of extracting a cylindrical core of paraffin-embedded donor tissue and inserting it into a recipient paraffin block. Donor tissue from surgically resected paraffin-embedded tissue blocks, frozen needle biopsies or cell line pellets can all be arrayed in the recipient block. The representative area of interest is identified and circled on a haematoxylin and eosin (H&E)-stained section of the donor block. Using a predesigned map showing a precise spacing pattern, a high density array of up to 1,000 cores of cell pellets and/or donor tissue can be embedded into the recipient block using a tissue arrayer from Beecher Instruments. Depending on the depth of the cell line/tissue removed from the donor block 100-300 consecutive sections can be cut from each CMA/TMA block. Sections can be stained for in situ detection of protein, DNA or RNA targets using immunohistochemistry (IHC), fluorescent in situ hybridisation (FISH) or mRNA in situ hybridisation (RNA-ISH), respectively. This chapter provides detailed methods for CMA/TMA design, construction and analysis with in-depth notes on all technical aspects including tips to deal with common pitfalls the user may encounter. © Springer Science+Business Media, LLC 2011.

Gene expression analysis of diagnostic biopsies predicts pathological response to neoadjuvant chemoradiotherapy of esophageal cancer

OBJECTIVE: This study explored gene expression differences in predicting response to chemoradiotherapy in esophageal cancer. PURPOSE:: A major pathological response to neoadjuvant chemoradiation is observed in about 40% of esophageal cancer patients and is associated with favorable outcomes. However, patients with tumors of similar histology, differentiation, and stage can have vastly different responses to the same neoadjuvant therapy. This dichotomy may be due to differences in the molecular genetic environment of the tumor cells. BACKGROUND DATA: Diagnostic biopsies were obtained from a training cohort of esophageal cancer patients (13), and extracted RNA was hybridized to genome expression microarrays. The resulting gene expression data was verified by qRT-PCR. In a larger, independent validation cohort (27), we examined differential gene expression by qRT-PCR. The ability of differentially-regulated genes to predict response to therapy was assessed in a multivariate leave-one-out cross-validation model. RESULTS: Although 411 genes were differentially expressed between normal and tumor tissue, only 103 genes were altered between responder and non-responder tumor; and 67 genes differentially expressed >2-fold. These included genes previously reported in esophageal cancer and a number of novel genes. In the validation cohort, 8 of 12 selected genes were significantly different between the response groups. In the predictive model, 5 of 8 genes could predict response to therapy with 95% accuracy in a subset (74%) of patients. CONCLUSIONS: This study has identified a gene microarray pattern and a set of genes associated with response to neoadjuvant chemoradiation in esophageal cancer. The potential of these genes as biomarkers of response to treatment warrants further investigation. Copyright © 2009 by Lippincott Williams & Wilkins.

Validation of β-actin used as endogenous control for gene expression analysis in mechanobiology studies : amendments

We write in response to the letter by Liu et al. [1] commenting on our article, ‘‘Mesenchymal Stem Cells Regulate Angiogenesis According to Their Mechanical Environment’’ [2]. The study by Liu et al. demonstrates that the commonly used endogeneous reference gene (ERG), b-actin, is upregulated by mechanical loading, indicating a potential bias in the determined target gene expression when normalizing to b-actin, such as in our report on unchanged vascular endothelial growth factor (VEGF) and hypoxia-inducible factors (HIF)-1a mRNA levels in mechanically loaded mesenchymal stem cells (MSCs).

Genome-Wide Gene Expression Analysis Reveals a Dynamic Interplay between Luteotropic and Luteolytic Factors in the Regulation of Corpus Luteum Function in the Bonnet Monkey (Macaca radiata)

Although LH is essential for survival and function of the corpus luteum (CL) in higher primates, luteolysis occurs during nonfertile cycles without a discernible decrease in circulating LH levels. Using genome-wide expression analysis, several experiments were performed to examine the processes of luteolysis and rescue of luteal function in monkeys. Induced luteolysis with GnRH receptor antagonist (Cetrorelix) resulted in differential regulation of 3949 genes, whereas replacement with exogenous LH (Cetrorelix plus LH) led to regulation of 4434 genes (1563 down-regulation and 2871 up-regulation). A model system for prostaglandin (PG) F-2 alpha-induced luteolysis in the monkey was standardized and demonstrated that PGF(2 alpha) regulated expression of 2290 genes in the CL. Analysis of the LH-regulated luteal transcriptome revealed that 120 genes were regulated in an antagonistic fashion by PGF(2 alpha). Based on the microarray data, 25 genes were selected for validation by real-time RT-PCR analysis, and expression of these genes was also examined in the CL throughout the luteal phase and from monkeys treated with human chorionic gonadotropin (hCG) to mimic early pregnancy. The results indicated changes in expression of genes favorable to PGF(2 alpha) action during the late to very late luteal phase, and expressions of many of these genes were regulated in an opposite manner by exogenous hCG treatment. Collectively, the findings suggest that curtailment of expression of downstream LH-target genes possibly through PGF(2 alpha) action on the CL is among the mechanisms underlying cross talk between the luteotropic and luteolytic signaling pathways that result in the cessation of luteal function, but hCG is likely to abrogate the PGF(2 alpha)-responsive gene expression changes resulting in luteal rescue crucial for the maintenance of early pregnancy. (Endocrinology 150: 1473-1484, 2009)

Cloning, characterization, and gene expression analysis of a novel cadmium metallothionein gene in Tetrahymena pigmentosa

A novel cadmium-inducible metallothionein (MT) gene (Tpig-MT1) was cloned and sequenced from the ciliate Tetrahymena pigmentosa. The number of deduced amino acids is 118. The polypeptide possesses CCC and CC clusters characteristic of typical Tetrahymena Cd-inducible MTs. The structure of Tpig-MT1 is different from the reported Cd-MT in T. pyriformis, T. thermophila and T. pigmentosa. Tpig-MT1 contains two intragenic tandem repeats with 72.9% identity described as Tpig-MT1 (repeat A1) and Tpig-MT1 (repeat A2). The transcriptional response of Tpig-MT1 gene to different heavy metals (Cd, Cu, Zn, Hg, Pb) and oxidative stress (H2O2) was measured using real-time quantitative PCR. The results showed that the gene was quickly induced (1 h) by the five heavy metals and the order of expression level was Hg>Pb>Cd>Cu>Zn. The induction effect of H2O2 was 5-fold after about 15 min, but soon decreased to a non-significant level (30 min). The genetic diversity of Tetrahymena MT genes is discussed in relation to the unique structure of the Tpig-MT1 gene and other reported Cd-MT isoforms. (C) 2008 Elsevier B.V. All rights reserved.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

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.

Differential gene expression analysis of iodide-treated rat thyroid follicular cell line PCCl3

The inhibitory effect of supraphysiological iodide concentrations on thyroid hormone synthesis (Wolff - Chaikoff effect) and on thyrocyte proliferation is largely known as iodine autoregulation. However, the molecular mechanisms by which iodide modulates thyroid function remain unclear. In this paper, we analyze the transcriptome profile of the rat follicular cell lineage PCCl3 under untreated and treated conditions with 10 (- 3) M sodium iodide (NaI). Serial analysis of gene expression (SAGE) revealed 84 transcripts differentially expressed in response to iodide (p <= 0.001). We also showed that iodide excess inhibits the expression of essential genes for thyroid differentiation: Tshr, Nis, Tg, and Tpo. Relative expression of 14 of 20 transcripts selected by SAGE was confirmed by real-time PCR. Considering the key role of iodide organification in thyroid physiology, we also observed that both the oxidized form of iodide and iodide per se are responsible for gene expression modulation in response to iodide excess. (c) 2008 Elsevier Inc. All rights reserved.