Expression profiling in spondyloarthropathy synovial biopsies highlights changes in expression of inflammatory genes in conjunction with tissue remodelling genes

Background: In the spondyloarthropathies, the underlying molecular and cellular pathways driving disease are poorly understood. By undertaking a study in knee synovial biopsies from spondyloarthropathy (SpA) and ankylosing spondylitis (AS) patients we aimed to elucidate dysregulated genes and pathways. Methods RNA was extracted from six SpA, two AS, three osteoarthritis (OA) and four normal control knee synovial biopsies. Whole genome expression profiling was undertaken using the Illumina DASL system, which assays 24000 cDNA probes. Differentially expressed candidate genes were then validated using quantitative PCR and immunohistochemistry. Results: Four hundred and sixteen differentially expressed genes were identified that clearly delineated between AS/SpA and control groups. Pathway analysis showed altered gene-expression in oxidoreductase activity, B-cell associated, matrix catabolic, and metabolic pathways. Altered «myogene» profiling was also identified. The inflammatory mediator, MMP3, was strongly upregulated (5-fold) in AS/SpA samples and the Wnt pathway inhibitors DKK3 (2.7-fold) and Kremen1 (1.5-fold) were downregulated. Conclusions: Altered expression profiling in SpA and AS samples demonstrates that disease pathogenesis is associated with both systemic inflammation as well as local tissue alterations that may underlie tissue damaging modelling and remodelling outcomes. This supports the hypothesis that initial systemic inflammation in spondyloarthropathies transfers to and persists in the local joint environment, and might subsequently mediate changes in genes directly involved in the destructive tissue remodelling.

Gene expression profiling reveals a downregulation in immune-associated genes in patients with AS

Objective: To identify differentially expressed genes in peripheral blood mononuclear cells (PBMCs) from patients with ankylosing spondylitis (AS) compared with healthy individuals. Methods: RNA was extracted from PBMCs collected from 18 patients with active disease and 18 gender-matched and age-matched controls. Expression profiles of these cells were determined using microarray. Candidate genes with differential expressions were confirmed in the same samples using quantitative reverse transcription-PCR (qRT-PCR). These genes were then validated in a different sample cohort of 35 patients with AS and 18 controls by qRT-PCR. Results: Microarray analysis identified 452 genes detected with 485 probes which were differentially expressed between patients with AS and controls. Underexpression of NR4A2, tumour necrosis factor AIP3 (TNFAIP3) and CD69 was confirmed. These genes were further validated in a different sample group in which the patients with AS had a wider range of disease activity. Predictive algorithms were also developed from the expression data using receiver-operating characteristic curves, which demonstrated that the three candidate genes have ∼80% power to predict AS according to their expression levels. Conclusions: The findings show differences in global gene expression patterns between patients with AS and controls, suggesting an immunosuppressive phenotype in the patients. Furthermore, downregulated expression of three immune-related genes was confirmed. These candidate genes were also shown to be strong predictive markers for AS.

Whole blood transcriptional profiling in ankylosing spondylitis identifies novel candidate genes that might contribute to the inflammatory and tissue-destructive disease aspects

Introduction: A number of genetic-association studies have identified genes contributing to ankylosing spondylitis (AS) susceptibility but such approaches provide little information as to the gene activity changes occurring during the disease process. Transcriptional profiling generates a 'snapshot' of the sampled cells' activity and thus can provide insights into the molecular processes driving the disease process. We undertook a whole-genome microarray approach to identify candidate genes associated with AS and validated these gene-expression changes in a larger sample cohort. Methods: A total of 18 active AS patients, classified according to the New York criteria, and 18 gender- and age-matched controls were profiled using Illumina HT-12 whole-genome expression BeadChips which carry cDNAs for 48,000 genes and transcripts. Class comparison analysis identified a number of differentially expressed candidate genes. These candidate genes were then validated in a larger cohort using qPCR-based TaqMan low density arrays (TLDAs). Results: A total of 239 probes corresponding to 221 genes were identified as being significantly different between patients and controls with a P-value <0.0005 (80% confidence level of false discovery rate). Forty-seven genes were then selected for validation studies, using the TLDAs. Thirteen of these genes were validated in the second patient cohort with 12 downregulated 1.3- to 2-fold and only 1 upregulated (1.6-fold). Among a number of identified genes with well-documented inflammatory roles we also validated genes that might be of great interest to the understanding of AS progression such as SPOCK2 (osteonectin) and EP300, which modulate cartilage and bone metabolism. Conclusions: We have validated a gene expression signature for AS from whole blood and identified strong candidate genes that may play roles in both the inflammatory and joint destruction aspects of the disease.

Expression Profiling of Nucleotide Metabolism-Related Genes in Human Breast Cancer Cells After Treatment with 5-Fluorouracil

5-Fluorouracil (5-FU) is one of the most widely used drugs for treatment of cancers, including breast cancer that exhibits its anticancer activity by inhibiting DNA synthesis and also incorporated into DNA and RNA. The objective of this investigation was to find out the total nucleotide metabolism genes regulated by 5-FU in breast cancer cell line. The breast cancer cell line MCF-7 was treated with the drug 5-FU. To analyze the expression of genes, we have conducted the experiment using 1.7k and 19k human microarray slide and confirmed the expression of genes by semiquantitative reverse transcription-polymerase chain reaction. The expression of 44 genes involved in the nucleotide metabolism pathway was quantified. Of these 44 genes analyzed, transcription of 6 genes were upregulated and 9 genes were downregulated. Earlier studies revealed that the transcription of genes for key enzymes like thymidylate synthase, thymidinekinase, and dihydropyrimidine dehydrogenase are regulated by 5-FU. This study identified some novel genes like thioredoxin reductase, ectonucleotide triphosphate dephosphorylase, and CTP synthase are regulated by 5-FU. The data also reveal large-scale perturbation in transcription of genes not involved directly in the known mechanism of action of 5-FU.

Gene expression profiling of cuticular proteins across the moult cycle of the crab Portunus pelagicus

Background: Crustaceans represent an attractive model to study biomineralization and cuticle matrix formation, as these events are precisely timed to occur at certain stages of the moult cycle. Moulting, the process by which crustaceans shed their exoskeleton, involves the partial breakdown of the old exoskeleton and the synthesis of a new cuticle. This cuticle is subdivided into layers, some of which become calcified while others remain uncalcified. The cuticle matrix consists of many different proteins that confer the physical properties, such as pliability, of the exoskeleton. Results: We have used a custom cDNA microarray chip, developed for the blue swimmer crab Portunus pelagicus, to generate expression profiles of genes involved in exoskeletal formation across the moult cycle. A total of 21 distinct moult-cycle related differentially expressed transcripts representing crustacean cuticular proteins were isolated. Of these, 13 contained copies of the cuticle_1 domain previously isolated from calcified regions of the crustacean exoskeleton, four transcripts contained a chitin_bind_4 domain (RR consensus sequence) associated with both the calcified and un-calcified cuticle of crustaceans, and four transcripts contained an unannotated domain (PfamB_109992) previously isolated from C. pagurus. Additionally, cryptocyanin, a hemolymph protein involved in cuticle synthesis and structural integrity, also displays differential expression related to the moult cycle. Moult stage-specific expression analysis of these transcripts revealed that differential gene expression occurs both among transcripts containing the same domain and among transcripts containing different domains. Conclusion: The large variety of genes associated with cuticle formation, and their differential expression across the crustacean moult cycle, point to the complexity of the processes associated with cuticle formation and hardening. This study provides a molecular entry path into the investigation of the gene networks associated with cuticle formation.

Microarrays in molecular profiling of cancer - focus on head and neck squamous cell carcinoma

Microarrays have a wide range of applications in the biomedical field. From the beginning, arrays have mostly been utilized in cancer research, including classification of tumors into different subgroups and identification of clinical associations. In the microarray format, a collection of small features, such as different oligonucleotides, is attached to a solid support. The advantage of microarray technology is the ability to simultaneously measure changes in the levels of multiple biomolecules. Because many diseases, including cancer, are complex, involving an interplay between various genes and environmental factors, the detection of only a single marker molecule is usually insufficient for determining disease status. Thus, a technique that simultaneously collects information on multiple molecules allows better insights into a complex disease. Since microarrays can be custom-manufactured or obtained from a number of commercial providers, understanding data quality and comparability between different platforms is important to enable the use of the technology to areas beyond basic research. When standardized, integrated array data could ultimately help to offer a complete profile of the disease, illuminating mechanisms and genes behind disorders as well as facilitating disease diagnostics. In the first part of this work, we aimed to elucidate the comparability of gene expression measurements from different oligonucleotide and cDNA microarray platforms. We compared three different gene expression microarrays; one was a commercial oligonucleotide microarray and the others commercial and custom-made cDNA microarrays. The filtered gene expression data from the commercial platforms correlated better across experiments (r=0.78-0.86) than the expression data between the custom-made and either of the two commercial platforms (r=0.62-0.76). Although the results from different platforms correlated reasonably well, combining and comparing the measurements were not straightforward. The clone errors on the custom-made array and annotation and technical differences between the platforms introduced variability in the data. In conclusion, the different gene expression microarray platforms provided results sufficiently concordant for the research setting, but the variability represents a challenge for developing diagnostic applications for the microarrays. In the second part of the work, we performed an integrated high-resolution microarray analysis of gene copy number and expression in 38 laryngeal and oral tongue squamous cell carcinoma cell lines and primary tumors. Our aim was to pinpoint genes for which expression was impacted by changes in copy number. The data revealed that especially amplifications had a clear impact on gene expression. Across the genome, 14-32% of genes in the highly amplified regions (copy number ratio >2.5) had associated overexpression. The impact of decreased copy number on gene underexpression was less clear. Using statistical analysis across the samples, we systematically identified hundreds of genes for which an increased copy number was associated with increased expression. For example, our data implied that FADD and PPFIA1 were frequently overexpressed at the 11q13 amplicon in HNSCC. The 11q13 amplicon, including known oncogenes such as CCND1 and CTTN, is well-characterized in different type of cancers, but the roles of FADD and PPFIA1 remain obscure. Taken together, the integrated microarray analysis revealed a number of known as well as novel target genes in altered regions in HNSCC. The identified genes provide a basis for functional validation and may eventually lead to the identification of novel candidates for targeted therapy in HNSCC.

Genomic and functional profiling of gastric cancer

Helicobacter pylori infection is a risk factor for gastric cancer, which is a major health issue worldwide. Gastric cancer has a poor prognosis due to the unnoticeable progression of the disease and surgery is the only available treatment in gastric cancer. Therefore, gastric cancer patients would greatly benefit from identifying biomarker genes that would improve diagnostic and prognostic prediction and provide targets for molecular therapies. DNA copy number amplifications are the hallmarks of cancers in various anatomical locations. Mechanisms of amplification predict that DNA double-strand breaks occur at the margins of the amplified region. The first objective of this thesis was to identify the genes that were differentially expressed in H. pylori infection as well as the transcription factors and signal transduction pathways that were associated with the gene expression changes. The second objective was to identify putative biomarker genes in gastric cancer with correlated expression and copy number, and the last objective was to characterize cancers based on DNA copy number amplifications. DNA microarrays, an in vitro model and real-time polymerase chain reaction were used to measure gene expression changes in H. pylori infected AGS cells. In order to identify the transcription factors and signal transduction pathways that were activated after H. pylori infection, gene expression profiling data from the H. pylori experiments and a bioinformatics approach accompanied by experimental validation were used. Genome-wide expression and copy number microarray analysis of clinical gastric cancer samples and immunohistochemistry on tissue microarray were used to identify putative gastric cancer genes. Data mining and machine learning techniques were applied to study amplifications in a cross-section of cancers. FOS and various stress response genes were regulated by H. pylori infection. H. pylori regulated genes were enriched in the chromosomal regions that are frequently changed in gastric cancer, suggesting that molecular pathways of gastric cancer and premalignant H. pylori infection that induces gastritis are interconnected. 16 transcription factors were identified as being associated with H. pylori infection induced changes in gene expression. NF-κB transcription factor and p50 and p65 subunits were verified using elecrophoretic mobility shift assays. ERBB2 and other genes located in 17q12- q21 were found to be up-regulated in association with copy number amplification in gastric cancer. Cancers with similar cell type and origin clustered together based on the genomic localization of the amplifications. Cancer genes and large genes were co-localized with amplified regions and fragile sites, telomeres, centromeres and light chromosome bands were enriched at the amplification boundaries. H. pylori activated transcription factors and signal transduction pathways function in cellular mechanisms that might be capable of promoting carcinogenesis of the stomach. Intestinal and diffuse type gastric cancers showed distinct molecular genetic profiles. Integration of gene expression and copy number microarray data allowed the identification of genes that might be involved in gastric carcinogenesis and have clinical relevance. Gene amplifications were demonstrated to be non-random genomic instabilities. Cell lineage, properties of precursor stem cells, tissue microenvironment and genomic map localization of specific oncogenes define the site specificity of DNA amplifications, whereas labile genomic features define the structures of amplicons. These conclusions suggest that the definition of genomic changes in cancer is based on the interplay between the cancer cell and the tumor microenvironment.

Gene Expression Profiling of the Cephalothorax and Eyestalk in Penaeus Monodon during Ovarian Maturation.

In crustaceans, a range of physiological processes involved in ovarian maturation occurs in organs of the cephalothorax including the hepatopancrease, mandibular and Y-organ. Additionally, reproduction is regulated by neuropeptide hormones and other proteins released from secretory sites within the eyestalk. Reproductive dysfunction in captive-reared prawns, Penaeus monodon, is believed to be due to deficiencies in these factors. In this study, we investigated the expression of gene transcripts in the cephalothorax and eyestalk from wild-caught and captive-reared animals throughout ovarian maturation using custom oligonucleotide microarray screening. We have isolated numerous transcripts that appear to be differentially expressed throughout ovarian maturation and between wild-caught and captive-reared animals. In the cephalothorax, differentially expressed genes included the 1,3-beta-D-glucan-binding high-density lipoprotein, 2/3-oxoacyl-CoA thiolase and vitellogenin. In the eyestalk, these include gene transcripts that encode a protein that modulates G-protein coupled receptor activity and another that encodes an architectural transcription factor. Each may regulate the expression of reproductive neuropeptides, such as the crustacean hyperglycaemic hormone and molt-inhibiting hormone. We could not identify differentially expressed transcripts encoding known reproductive neuropeptides in the eyestalk of either wild-caught or captive-reared prawns at any ovarian maturation stage, however, this result may be attributed to low relative expression levels of these transcripts. In summary, this study provides a foundation for the study of target genes involved in regulating penaeid reproduction.

Genomic Profiling of Gastric Cancer

Gastric cancer is the fourth most common cancer and the second most common cause of cancer-related death worldwide. Due to lack of early symptoms, gastric cancer is characterized by late stage diagnosis and unsatisfactory options for curative treatment. Several genomic alterations have been identified in gastric cancer, but the major factors contributing to initiation and progression of gastric cancer remain poorly known. Gene copy number alterations play a key role in the development of gastric cancer, and a change in gene copy number is one of the fundamental mechanisms for a cancer cell to control the expression of potential oncogenes and tumor suppressor genes. This thesis aims at clarifying the complex genomic alterations of gastric cancer to identify novel molecular biomarkers for diagnostic purposes as well as for targeted treatment. To highlight genes of potential biological and clinical relevance, we carried out a systematic microarray-based survey of gene expression and copy number levels in primary gastric tumors and gastric cancer cell lines. Results were validated using immunohistochemistry, real-time qRT-PCR, and affinity capture-based transcript (TRAC) assay. Altogether 192 clinical gastric tissue samples and 7 gastric cancer cell lines were included in this study. Multiple chromosomal regions with recurrent copy number alterations were detected. The most frequent chromosomal alterations included gains at 7q, 8q, 17q, 19q, and 20q and losses at 9p, 18q, and 21q. Distinctive patterns of copy number alterations were detected for different histological subtypes (intestinal and diffuse) and for cancers located in different parts of the stomach. The impact of copy number alterations on gene expression was significant, as 6-10% of genes located in the regions of gains and losses also showed concomitant alterations in their expression. By combining the information from the DNA- and RNA-level analyses many novel gastric cancer-related genes, such as ALPK2, ENAH, HHIPL2, and OSMR, were identified. Independent genome-wide gene expression analysis of Finnish and Japanese gastric tumors revealed an additional set of genes that was differentially expressed in cancerous gastric tissues compared with normal tissue. Overexpression of one of these genes, CXCL1, was associated with an improved survival of gastric cancer. Thus, using an integrative microarray analysis, several novel genes were identified that may be critically important for gastric carcinogenesis. Further studies of these genes may lead to novel biomarkers for gastric cancer diagnosis and targeted therapy.

Microbial identification by detection of ligation probes on DNA microarray

Microbes in natural and artificial environments as well as in the human body are a key part of the functional properties of these complex systems. The presence or absence of certain microbial taxa is a correlate of functional status like risk of disease or course of metabolic processes of a microbial community. As microbes are highly diverse and mostly notcultivable, molecular markers like gene sequences are a potential basis for detection and identification of key types. The goal of this thesis was to study molecular methods for identification of microbial DNA in order to develop a tool for analysis of environmental and clinical DNA samples. Particular emphasis was placed on specificity of detection which is a major challenge when analyzing complex microbial communities. The approach taken in this study was the application and optimization of enzymatic ligation of DNA probes coupled with microarray read-out for high-throughput microbial profiling. The results show that fungal phylotypes and human papillomavirus genotypes could be accurately identified from pools of PCR amplicons generated from purified sample DNA. Approximately 1 ng/μl of sample DNA was needed for representative PCR amplification as measured by comparisons between clone sequencing and microarray. A minimum of 0,25 amol/μl of PCR amplicons was detectable from amongst 5 ng/μl of background DNA, suggesting that the detection limit of the test comprising of ligation reaction followed by microarray read-out was approximately 0,04%. Detection from sample DNA directly was shown to be feasible with probes forming a circular molecule upon ligation followed by PCR amplification of the probe. In this approach, the minimum detectable relative amount of target genome was found to be 1% of all genomes in the sample as estimated from 454 deep sequencing results. Signal-to-noise of contact printed microarrays could be improved by using an internal microarray hybridization control oligonucleotide probe together with a computational algorithm. The algorithm was based on identification of a bias in the microarray data and correction of the bias as shown by simulated and real data. The results further suggest semiquantitative detection to be possible by ligation detection, allowing estimation of target abundance in a sample. However, in practise, comprehensive sequence information of full length rRNA genes is needed to support probe design with complex samples. This study shows that DNA microarray has the potential for an accurate microbial diagnostic platform to take advantage of increasing sequence data and to replace traditional, less efficient methods that still dominate routine testing in laboratories. The data suggests that ligation reaction based microarray assay can be optimized to a degree that allows good signal-tonoise and semiquantitative detection.

Gene Expression Profiling of Preovulatory Follicle in the Buffalo Cow: Effects of Increased IGF-I Concentration on Periovulatory Events

The preovulatory follicle in response to gonadotropin surge undergoes dramatic biochemical, and morphological changes orchestrated by expression changes in hundreds of genes. Employing well characterized bovine preovulatory follicle model, granulosa cells (GCs) and follicle wall were collected from the preovulatory follicle before, 1, 10 and 22 h post peak LH surge. Microarray analysis performed on GCs revealed that 450 and 111 genes were differentially expressed at 1 and 22 h post peak LH surge, respectively. For validation, qPCR and immunocytochemistry analyses were carried out for some of the differentially expressed genes. Expression analysis of many of these genes showed distinct expression patterns in GCs and the follicle wall. To study molecular functions and genetic networks, microarray data was analyzed using Ingenuity Pathway Analysis which revealed majority of the differentially expressed genes to cluster within processes like steroidogenesis, cell survival and cell differentiation. In the ovarian follicle, IGF-I is established to be an important regulator of the above mentioned molecular functions. Thus, further experiments were conducted to verify the effects of increased intrafollicular IGF-I levels on the expression of genes associated with the above mentioned processes. For this purpose, buffalo cows were administered with exogenous bGH to transiently increase circulating and intrafollicular concentrations of IGF-I. The results indicated that increased intrafollicular concentrations of IGF-I caused changes in expression of genes associated with steroidogenesis (StAR, SRF) and apoptosis (BCL-2, FKHR, PAWR). These results taken together suggest that onset of gonadotropin surge triggers activation of various biological pathways and that the effects of growth factors and peptides on gonadotropin actions could be examined during preovulatory follicle development.

Profiling of Luteal Transcriptome during Prostaglandin F2-Alpha Treatment in Buffalo Cows: Analysis of Signaling Pathways Associated with Luteolysis

In several species including the buffalo cow, prostaglandin (PG) F-2 alpha is the key molecule responsible for regression of corpus luteum (CL). Experiments were carried out to characterize gene expression changes in the CL tissue at various time points after administration of luteolytic dose of PGF(2 alpha) in buffalo cows. Circulating progesterone levels decreased within 1 h of PGF(2 alpha) treatment and evidence of apoptosis was demonstrable at 18 h post treatment. Microarray analysis indicated expression changes in several of immediate early genes and transcription factors within 3 h of treatment. Also, changes in expression of genes associated with cell to cell signaling, cytokine signaling, steroidogenesis, PG synthesis and apoptosis were observed. Analysis of various components of LH/CGR signaling in CL tissues indicated decreased LH/CGR protein expression, pCREB levels and PKA activity post PGF(2 alpha) treatment. The novel finding of this study is the down regulation of CYP19A1 gene expression accompanied by decrease in expression of E-2 receptors and circulating and intra luteal E-2 post PGF(2 alpha) treatment. Mining of microarray data revealed several differentially expressed E-2 responsive genes. Since CYP19A1 gene expression is low in the bovine CL, mining of microarray data of PGF(2 alpha)-treated macaques, the species with high luteal CYP19A1 expression, showed good correlation between differentially expressed E-2 responsive genes between both the species. Taken together, the results of this study suggest that PGF(2 alpha) interferes with luteotrophic signaling, impairs intraluteal E-2 levels and regulates various signaling pathways before the effects on structural luteolysis are manifest.

SplicerAV: a tool for mining microarray expression data for changes in RNA processing.

BACKGROUND: Over the past two decades more than fifty thousand unique clinical and biological samples have been assayed using the Affymetrix HG-U133 and HG-U95 GeneChip microarray platforms. This substantial repository has been used extensively to characterize changes in gene expression between biological samples, but has not been previously mined en masse for changes in mRNA processing. We explored the possibility of using HG-U133 microarray data to identify changes in alternative mRNA processing in several available archival datasets. RESULTS: Data from these and other gene expression microarrays can now be mined for changes in transcript isoform abundance using a program described here, SplicerAV. Using in vivo and in vitro breast cancer microarray datasets, SplicerAV was able to perform both gene and isoform specific expression profiling within the same microarray dataset. Our reanalysis of Affymetrix U133 plus 2.0 data generated by in vitro over-expression of HRAS, E2F3, beta-catenin (CTNNB1), SRC, and MYC identified several hundred oncogene-induced mRNA isoform changes, one of which recognized a previously unknown mechanism of EGFR family activation. Using clinical data, SplicerAV predicted 241 isoform changes between low and high grade breast tumors; with changes enriched among genes coding for guanyl-nucleotide exchange factors, metalloprotease inhibitors, and mRNA processing factors. Isoform changes in 15 genes were associated with aggressive cancer across the three breast cancer datasets. CONCLUSIONS: Using SplicerAV, we identified several hundred previously uncharacterized isoform changes induced by in vitro oncogene over-expression and revealed a previously unknown mechanism of EGFR activation in human mammary epithelial cells. We analyzed Affymetrix GeneChip data from over 400 human breast tumors in three independent studies, making this the largest clinical dataset analyzed for en masse changes in alternative mRNA processing. The capacity to detect RNA isoform changes in archival microarray data using SplicerAV allowed us to carry out the first analysis of isoform specific mRNA changes directly associated with cancer survival.

permGPU: Using graphics processing units in RNA microarray association studies.

BACKGROUND: Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. RESULTS: We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. CONCLUSIONS: permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.