Differential gene expression profiles of hepatocellular carcinomas associated or not with viral infection

Chronic hepatitis B (HBV) and C (HCV) virus infections are the most important factors associated with hepatocellular carcinoma (HCC), but tumor prognosis remains poor due to the lack of diagnostic biomarkers. In order to identify novel diagnostic markers and therapeutic targets, the gene expression profile associated with viral and non-viral HCC was assessed in 9 tumor samples by oligo-microarrays. The differentially expressed genes were examined using a z-score and KEGG pathway for the search of ontological biological processes. We selected a non-redundant set of 15 genes with the lowest P value for clustering samples into three groups using the non-supervised algorithm k-means. Fisher’s linear discriminant analysis was then applied in an exhaustive search of trios of genes that could be used to build classifiers for class distinction. Different transcriptional levels of genes were identified in HCC of different etiologies and from different HCC samples. When comparing HBV-HCC vs HCV-HCC, HBV-HCC/HCV-HCC vs non-viral (NV)-HCC, HBC-HCC vs NV-HCC, and HCV-HCC vs NV-HCC of the 58 non-redundant differentially expressed genes, only 6 genes (IKBKβ, CREBBP, WNT10B, PRDX6, ITGAV, and IFNAR1) were found to be associated with hepatic carcinogenesis. By combining trios, classifiers could be generated, which correctly classified 100% of the samples. This expression profiling may provide a useful tool for research into the pathophysiology of HCC. A detailed understanding of how these distinct genes are involved in molecular pathways is of fundamental importance to the development of effective HCC chemoprevention and treatment.

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

Identification of a biomarker panel for colorectal cancer diagnosis

Background Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60-mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results After an exhaustive process of pre-processing to ensure data quality--lost values imputation, probes quality, data smoothing and intraclass variability filtering--the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955)

Identification of a biomarker panel for colorectal cancer diagnosis

Background:Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods: A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60-mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results: After an exhaustive process of pre-processing to ensure data quality--lost values imputation, probes quality, data smoothing and intraclass variability filtering--the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions: We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).

Differential gene expression in the developing mouse ureter

In many instances, kidney dysgenesis results as a secondary consequence to defects in the development of the ureter. Through the use of mouse genetics a number of genes associated with such malformations have been identified, however, the cause of many other abnormalities remain unknown. In order to identify novel genes involved in ureter development we compared gene expression in embryonic day (E) 12.5, E15.5 and postnatal day (P) 75 ureters using the Compugen mouse long oligo microarrays. A total of 248 genes were dynamically upregulated and 208 downregulated between E12.5 and P75. At E12.5, when the mouse ureter is comprised of a simple cuboidal epithelium surrounded by ureteric mesenchyme, genes previously reported to be expressed in the ureteric mesenchyme, foxC1 and foxC2 were upregulated. By E15.5 the epithelial layer develops into urothelium, impermeable to urine, and smooth muscle develops for the peristaltic movement of urine towards the bladder. The development of these two cell types coincided with the upregulation of UPIIIa, RAB27b and PPAR gamma reported to be expressed in the urothelium, and several muscle genes, Acta1, Tnnt2, Myocd, and Tpm2. In situ hybridization identified several novel genes with spatial expression within the smooth muscle, Acta1; ureteric mesenchyme and smooth muscle, Thbs2 and Co15a2; and urothelium, Kcnj8 and Adh1. This study marks the first known report defining global gene expression of the developing mouse ureter and will provide insight into the molecular mechanisms underlying kidney and lower urinary tract malformations. (c) 2005 Elsevier B.V. All rights reserved.

Spatial gene expression in the T-stage mouse metanephros

The E11.5 mouse metanephros is comprised of a T-stage ureteric epithelial tubule sub-divided into tip and trunk cells surrounded by metanephric mesenchyme (MM). Tip cells are induced to undergo branching morphogenesis by the MM. In contrast, signals within the mesenchyme surrounding the trunk prevent ectopic branching of this region. In order to identify novel genes involved in the molecular regulation of branching morphogenesis we compared the gene expression profiles of isolated tip, trunk and MM cells using Compugen mouse long oligo microarrays. We identified genes enriched in the tip epithelium, sim-1, Arg2, Tacstd1, Crlf-1 and BMP7; genes enriched in the trunk epithelium, Innp1, Itm2b, Mkrn1, SPARC, Emu2 and Gsta3 and genes spatially restricted to the mesenchyme surrounding the trunk, CSPG2 and CV-2, with overlapping and complimentary expression to BMP4, respectively. This study has identified genes spatially expressed in regions of the developing kidney involved in branching morphogenesis, nephrogenesis and the development of the collecting duct system, calyces, renal pelvis and ureter. (c) 2006 Elsevier B.V. All rights reserved.

Xylella fastidiosa gene expression analysis by DNA microarrays

Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

LATENT RANK CHANGE DETECTION FOR ANALYSIS OF SPLICE-JUNCTION MICROARRAYS WITH NONLINEAR EFFECTS

Alternative splicing of gene transcripts greatly expands the functional capacity of the genome, and certain splice isoforms may indicate specific disease states such as cancer. Splice junction microarrays interrogate thousands of splice junctions, but data analysis is difficult and error prone because of the increased complexity compared to differential gene expression analysis. We present Rank Change Detection (RCD) as a method to identify differential splicing events based upon a straightforward probabilistic model comparing the over-or underrepresentation of two or more competing isoforms. RCD has advantages over commonly used methods because it is robust to false positive errors due to nonlinear trends in microarray measurements. Further, RCD does not depend on prior knowledge of splice isoforms, yet it takes advantage of the inherent structure of mutually exclusive junctions, and it is conceptually generalizable to other types of splicing arrays or RNA-Seq. RCD specifically identifies the biologically important cases when a splice junction becomes more or less prevalent compared to other mutually exclusive junctions. The example data is from different cell lines of glioblastoma tumors assayed with Agilent microarrays.

Effect of the immunosuppressants on hepatocyte proliferation and apoptosis in a young animal model of liver regeneration: An immunohistochemical study using tissue microarrays

Hepatocyte proliferation and apoptosis (programmed cell death) occur during the liver parenchyma regeneration and the liver size modeling is mainly controlled by hepatocyte apoptosis. The purpose of the present study was to verify the influence of immunosuppressant drugs on these phenomena by utilizing tissue microarray techniques. Thirty-six weaning rats (age 21-23 days, weight 30-50 g) were divided into six groups: control, sham, hepatectomy, hepatectomy plus solumedrol, hepatectomy plus CsA, and hepatectomy plus Tac. The animals were killed one day after hepatectomy, and the remnant livers were weighed and harvested for tissue microarray sections. Liver cell proliferation was evaluated by staining for PCNA and apoptosis was detected by the TUNEL method. It was verified that CsA promoted a decrease in the liver weight, Tac and CsA decreased the proliferation index of hepatocytes, and glucocorticoid had no significant effects. The apoptosis index was not altered by hepatectomy or immunosuppressants. Our data indicate that, in the growing rat, CsA and Tac have negative effects on hepatocyte proliferation and have no effect on the hepatocyte apoptosis.

Optical encoding of microbeads for gene screening: alternatives to microarrays

Rapid access to genetic information is central to the revolution presently occurring in the pharmaceutical industry, particularly In relation to novel drug target identification and drug development. Genetic variation, gene expression, gene function and gene structure are just some of the important research areas requiring efficient methods of DNA screening. Here, we highlight state-of-the-art techniques and devices for gene screening that promise cheaper and higher-throughput yields than currently achieved with DNA microarrays. We include an overview of existing and proposed bead-based strategies designed to dramatically increase the number of probes that can be interrogated in one assay. We focus, in particular, on the issue of encoding and/or decoding (bar-coding) large bead-based libraries for HTS.

Application of DNA microarrays to study human alcoholism

An emerging idea is that long-term alcohol abuse results in changes in gene expression in the brain and that these changes are responsible at least partly for alcohol tolerance, dependence and neurotoxicity, The overall goal of our research is to identify genes which are differentia[ly expressed in the brains of well-characterized human alcoholics as compared with non-alcoholics. This should identify as-yet-unknown alcohol-responsive genes, and may well confirm changes in the expression of genes which have been delineated in animal models of alcohol abuse. Cases were carefully selected and samples pooled on the basis of relevant criteria; differential expression was monitored by microarray hybridization. The inherent diversity of human alcoholics can be exploited to identify genes associated with specific pathological processes, as well as to assess the effects of concomitant disease, severity of brain damage, drinking behavior, and factors such as gender and smoking history. initial results show selective changes in gene expression in alcoholics; of particular importance is a coordinated reduction in genes coding for myelin components, Copyright (C) 2001 National Science Council, ROC and S. Karger AG, Basel.

Model-based clustering in gene expression microarrays: An application to breast cancer data

In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

Oligo-Miocene extensional tectonics and fluid flow across the Northern Snake Range detachment system, Nevada

The Northern Snake Range (Nevada) represents a spectacular example of a metamorphic core complex and exposes a complete section from the mylonitic footwall into the hanging wall of a fossil detachment system. Paired geochronological and stable isotopic data of mylonitic quartzite within the detachment footwall reveal that ductile deformation and infiltration of meteoric fluids occurred between 27 and 23 Ma. Ar-40/Ar-39 ages display complex recrystallization-cooling relationships but decrease systematically from 26.9 +/- 0.2 Ma at the top to 21.3 +/- 0.2 Ma at the bottom of footwall mylonite. Hydrogen isotope (delta D) values in white mica are very low (-150 to -145 %) within the top 80-90 m of detachment footwall, in contrast to values obtained from the deeper part of the section where values range from -77 to -64 %, suggesting that time-integrated interaction between rock and meteoric fluid was restricted to the uppermost part of the mylonitic footwall. Pervasive mica-water hydrogen isotope exchange is difficult to reconcile with models of Ar-40 loss during mylonitization solely by volume diffusion. Rather, we interpret the Ar-40/Ar-39 ages of white mica with low-delta D values to date syn-mylonitic hydrogen and argon isotope exchange, and we conclude that the hydrothermal system of the Northern Snake Range was active during late Oligocene (27-23 Ma) and has been exhumed by the combined effects of ductile strain, extensional detachment faulting, and erosion.

A novel reiterated family of transcribed oligo(A)-terminated, interspersed DNA elements in the genome of Trypanosoma cruzi

We report the molecular characterization of a novel reiterated family of transcribed oligo(A)-terminated, interspersed DNA elements in the genome of Trypanosoma cruzi. Steady-state level of transcripts of this sequence family appeared to be developmentally regulated, since only in the replicative forms the parasite showed expression of related sequences with a major band around 3 kb. The presence of frame shifts or premature stop codons predicts that transcripts are not translated. The sequence family also contains truncated forms of retrotransposons elements that may become potential hot spots for retroelement insertion. Sequences homologous to this family are interspersed at many chromosomes including the subtelomeric regions.