Comparison Of Gene Expression Data Research Articles

Alignment of gene expression profiles from test samples against a reference database: New method for context-specific interpretation of microarray data

BackgroundGene expression microarray data have been organized and made available as public databases, but the utilization of such highly heterogeneous reference datasets in the interpretation of data from individual test samples is not as developed as e.g. in the field of nucleotide sequence comparisons. We have created a rapid and powerful approach for the alignment of microarray gene expression profiles (AGEP) from test samples with those contained in a large annotated public reference database and demonstrate here how this can facilitate interpretation of microarray data from individual samples.MethodsAGEP is based on the calculation of kernel density distributions for the levels of expression of each gene in each reference tissue type and provides a quantitation of the similarity between the test sample and the reference tissue types as well as the identity of the typical and atypical genes in each comparison. As a reference database, we used 1654 samples from 44 normal tissues (extracted from the Genesapiens database).ResultsUsing leave-one-out validation, AGEP correctly defined the tissue of origin for 1521 (93.6%) of all the 1654 samples in the original database. Independent validation of 195 external normal tissue samples resulted in 87% accuracy for the exact tissue type and 97% accuracy with related tissue types. AGEP analysis of 10 Duchenne muscular dystrophy (DMD) samples provided quantitative description of the key pathogenetic events, such as the extent of inflammation, in individual samples and pinpointed tissue-specific genes whose expression changed (SAMD4A) in DMD. AGEP analysis of microarray data from adipocytic differentiation of mesenchymal stem cells and from normal myeloid cell types and leukemias provided quantitative characterization of the transcriptomic changes during normal and abnormal cell differentiation.ConclusionsThe AGEP method is a widely applicable method for the rapid comprehensive interpretation of microarray data, as proven here by the definition of tissue- and disease-specific changes in gene expression as well as during cellular differentiation. The capability to quantitatively compare data from individual samples against a large-scale annotated reference database represents a widely applicable paradigm for the analysis of all types of high-throughput data. AGEP enables systematic and quantitative comparison of gene expression data from test samples against a comprehensive collection of different cell/tissue types previously studied by the entire research community.

Multiplex cDNA quantification method that facilitates the standardization of gene expression data

Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations. These requirements impose limitations on the extensive comparison of gene expression data. Here, we report an effective approach to removing the unfavorable limitations by measuring the absolute amounts of gene expression levels on common DNA microarrays. We have developed a multiplex cDNA quantification method called GEP-DEAN (Gene expression profiling by DCN-encoding-based analysis). The method was validated by using chemically synthesized DNA strands of known quantities and cDNA samples prepared from mouse liver, demonstrating that the absolute amounts of cDNA strands were successfully measured with a sensitivity of 18 zmol in a highly multiplexed manner in 7 h.

Identification of Robust Cardiac Reference Genes in a Mouse Model of Cardiometabolic Disease

Cardiovascular disease is linked to obesity, the metabolic syndrome, and altered 24hour (circadian) rhythms. Although the underlying mechanisms remain undefined, transcriptome analysis in the heart is beginning to provide important insights into the cardiometabolic pathogenesis. The reliability and accuracy of real-time quantitative PCR generated gene expression data is largely dependent on the selection of suitable reference genes (RG), which must be constitutively expressed regardless of cardio-metabolic disease state and time of day. However, many studies do not employ the appropriate selections strategies. In this study we determined the expression stability of seven candidate RGs (GAPDH, YWHAZ, B2M, EIF4A2, ATP5?, ACTB and CYC1) in a mouse model of diet-induced metabolic syndrome in both the day and night, using geNorm qBasePLUS software. RG expression varied in hearts of normal fed versus high fat fed mice, and was also dependant on the time of day. When all experimental variables were considered YWHAZ and ACTB were ranked the most stable and therefore the most suitable genes for generating comparative gene expression data in heart tissue from murine models of cardiometabolic disease. This study provides important information for reference gene selection, and will aid further transcriptome investigations into heart organ function

Abstract 2570: Novel mechanisms of taxane and platinum resistance in esophagogastric cancer cells by gene expression profiling

Abstract BACKGROUND Platinum analogues and taxanes are clinically effective in esophagogastric (EG) cancers and demonstrate significant non-cross resistance. Nevertheless, resistance (primary or acquired) remains a major therapeutic problem. We have developed platinum and docetaxel resistant cell line models and aim to use gene expression profiling for hypothesis generation to identify; predictive biomarkers; novel mechanisms of action and resistance; therapeutic targets and to provide insight into mechanisms of cross resistance. This will inform optimal cytotoxic and targeted therapy combination strategies. METHODS Resistant daughter cell lines were generated from 3 parental EG cancer cell lines (OE33, OE21, AGS) by exposure to increasing concentrations of oxaliplatin, cisplatin and docetaxel for at least 12 months. Cell viability was measured at 72h by the MTT assay. IC50 values were calculated in Prism Software and P<0.05 were statistically significant (Student's t-test). Affymetrix GeneChip Exon 1.0 were used to measure gene expression. Gene expression data were normalized in GeneSpring GX v10.0.1 using RMA for summarisation and baseline transformation of log transformed data to the median. The microarrays passed QC analysis, including hybridisation and labelling controls, Pos_vs_Neg_AUC and all probe Set RLE mean. RESULTS Initial data available compared daughter oxaliplatin resistant OE21ox4 line to OE21wt. Of the 17881 core genes present on the array, 14727 were expressed above background (20th −100th percentile) and of these the expression of 528 transcripts was altered by ≥ 2 fold (3 fold, n=113 and 5 fold, n=26). MMP9 demonstrated the highest change (14.3 fold decrease in resistant cells). Interestingly, ABCC2/ MRP, known to confer resistance to many cytotoxics, including taxanes but not platinums, was reduced by 6.3 fold in resistant cells. Gene ontology analysis identified transcripts whose products are associated with the extracellular region as significantly represented in the 538 entity gene set (P=6.971 × 10−7). Seven biological pathways were significantly altered in oxaliplatin-resistant compared to the sensitive parental OE21 cells (2fold geneset, n=528): alpha VI beta IV integrin (P=0.004), EGFR1 (P=0.003), ID (P=2.41^-4), IL1 (P=0.013), IL2 (P=0.027), IL6 (P=0.021), TCR (P=0.039). The αVIβIV and IL1 pathways were also significantly altered after chemotherapy in a parallel study of serial biopsies from EG cancer patients in our group. CONCLUSION We have a panel of EG cancer cell lines representative of clinical subgroups of the disease and have developed resistant daughter lines to oxaliplatin, cisplatin and docetaxel. A preliminary analysis of the OE21 oesophageal squamous carcinoma cell line and its oxaliplatin resistant daughter line is presented. A comparative gene expression data analysis of the entire panel of cell lines will be presented at the meeting. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2570.

OpenFlyData: An exemplar data web integrating gene expression data on the fruit fly Drosophila melanogaster

Motivation: Integrating heterogeneous data across distributed sources is a major requirement for in silico bioinformatics supporting translational research. For example, genome-scale data on patterns of gene expression in the fruit fly Drosophila melanogaster are widely used in functional genomic studies in many organisms to inform candidate gene selection and validate experimental results. However, current data integration solutions tend to be heavy weight, and require significant initial and ongoing investment of effort. Development of a common Web-based data integration infrastructure (a.k.a. data web), using Semantic Web standards, promises to alleviate these difficulties, but little is known about the feasibility, costs, risks or practical means of migrating to such an infrastructure. Results: We describe the development of OpenFlyData, a proof-of-concept system integrating gene expression data on D. melanogaster, combining Semantic Web standards with light-weight approaches to Web programming based on Web 2.0 design patterns. To support researchers designing and validating functional genomic studies, OpenFlyData includes user-facing search applications providing intuitive access to and comparison of gene expression data from FlyAtlas, the BDGP in situ database, and FlyTED, using data from FlyBase to expand and disambiguate gene names. OpenFlyData’s services are also openly accessible, and are available for reuse by other bioinformaticians and application developers. Semi-automated methods and tools were developed to support labour- and knowledge-intensive tasks involved in deploying SPARQL services. These include methods for generating ontologies and relational-to-RDF mappings for relational databases, which we illustrate using the FlyBase Chado database schema; and methods for mapping gene identifiers between databases. The advantages of using Semantic Web standards for biomedical data integration are discussed, as are open issues. In particular, although the performance of open source SPARQL implementations is sufficient to query gene expression data directly from user-facing applications such as Web-based data fusions (a.k.a. mashups), we found open SPARQL endpoints to be vulnerable to denial-of-service-type problems, which must be mitigated to ensure reliability of services based on this standard. These results are relevant to data integration activities in translational bioinformatics. Availability: The gene expression search applications and SPARQL endpoints developed for OpenFlyData are deployed at http://openflydata.org. FlyUI, a library of JavaScript widgets providing re-usable user-interface components for Drosophila gene expression data, is available at http://flyui.googlecode.com. Software and ontologies to support transformation of data from FlyBase, FlyAtlas, BDGP and FlyTED to RDF are available at http://openflydata.googlecode.com. SPARQLite, an implementation of the SPARQL protocol, is available at http://sparqlite.googlecode.com. All software is provided under the GPL version 3 open source license.

An integrated study of aberrant gene copy number and gene expression in GIST and LMS.

Increased chromosomal instability that alters the gene copy numbers throughout the genome is known to have a role in molecular pathogenesis of tumors. The impact of gene dosage effect to the expression levels of genes in GIST and LMS is unknown. In this paper, we used a combination of array comparative genomic hybridization (aCGH) and gene expression data to gain insights into the interplay of structural and functional changes of the genome in GIST and LMSs. We identified specific target genes that change their expression due to the gene dosage effect. Statistical analysis identified four chromosomal regions, 1p, 14q, 15q, and 22q, where both copy number and mRNA expression were significantly different between the tumor types. Multi-dimensional scaling (MDS) analysis showed that the gene expression profiles of these four regions accurately distinguish GIST and LMS. In addition, the gene dosage sensitive genes in these regions are differently involved in several tumor growth promoting pathways, implying that there are different mechanisms underlying the GIST and LMS carcinogenesis. Integration of aCGH and gene expression data has not only provided insights into how DNA copy number variations affect the gene expression patterns in these cancers, but also proves to be a promising method to choose biologically relevant biomarkers.

Deep SAGE analysis of the Caenorhabditis elegans transcriptome

We employed the Tag-seq technique to generate global transcription profiles for different strains and life stages of the nematode C. elegans. Tag-seq generates cDNA tags as does Serial Analysis of Gene Expression (SAGE), but the method yields a much larger number of tags, generating much larger data sets than SAGE. We examined differences in the performance of SAGE and Tag-seq by comparing gene expression data for 13 pairs of libraries. We identified genes for which expression was consistently changed in long-lived worms. Additional genes emerged in the deeper Tag-seq profiles, including several ‘signature’ genes found among those zup-regulated in long-lived dauer larvae (cki-1, aak-2 and daf-16). Fifty to sixty percent of the genes differentially expressed in daf-2(−) versus daf-2(+) adults had fragmentary or no functional annotation, suggesting the involvement of as yet unstudied pathways in aging. We were able to distinguish between changes in gene expression associated with altered genotype or altered growth conditions. We found 62 cases of possible mRNA isoform switching in the 13 Tag-seq libraries, whereas the 13 SAGE libraries allowed detection of only 15 such occurrences. We observed strong expression of anti-sense transcripts for several mitochondrial genes, but nuclear anti-sense transcripts were neither abundant nor consistently expressed among the libraries.

Tumor suppressor protein SMAR1 modulates the roughness of cell surface: combined AFM and SEM study

BackgroundImaging tools such as scanning electron microscope (SEM) and atomic force microscope (AFM) can be used to produce high-resolution topographic images of biomedical specimens and hence are well suited for imaging alterations in cell morphology. We have studied the correlation of SMAR1 expression with cell surface smoothness in cell lines as well as in different grades of human breast cancer and mouse tumor sections.MethodsWe validated knockdown and overexpression of SMAR1 using RT-PCR as well as Western blotting in human embryonic kidney (HEK) 293, human breast cancer (MCF-7) and mouse melanoma (B16F1) cell lines. The samples were then processed for cell surface roughness studies using atomic force microscopy (AFM) and scanning electron microscopy (SEM). The same samples were used for microarray analysis as well. Tumors sections from control and SMAR1 treated mice as well as tissues sections from different grades of human breast cancer on poly L-lysine coated slides were used for AFM and SEM studies.ResultsTumor sections from mice injected with melanoma cells showed pronounced surface roughness. In contrast, tumor sections obtained from nude mice that were first injected with melanoma cells followed by repeated injections of SMAR1-P44 peptide, exhibited relatively smoother surface profile. Interestingly, human breast cancer tissue sections that showed reduced SMAR1 expression exhibited increased surface roughness compared to the adjacent normal breast tissue. Our AFM data establishes that treatment of cells with SMAR1-P44 results into increase in cytoskeletal volume that is supported by comparative gene expression data showing an increase in the expression of specific cytoskeletal proteins compared to the control cells. Altogether, these findings indicate that tumor suppressor function of SMAR1 might be exhibited through smoothening of cell surface by regulating expression of cell surface proteins.ConclusionTumor suppressor protein SMAR1 might be used as a phenotypic differentiation marker between cancerous and non-cancerous cells.

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

BackgroundDNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database.ResultsGEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories.ConclusionGEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at .

Shared and divergent expression domains on mimeticHeliconiuswings

Heliconius butterfly wing patterns show repeated convergence between species and have adaptive value in mimicry and mate choice, offering an opportunity to connect adaptive changes in phenotype with their underlying genotypes. Here we study forewing ommochrome pigmentation in Heliconius melpomene. We clone two new ommochrome pathway genes for the Lepidoptera, karmoisin and kynurenine formamidase (kf ), and analyze the expression patterns of all known ommochrome genes across pupal wing development. In combination with published work, this generates the first comparative gene expression data for the co-mimics Heliconius erato and H. melpomene. In both species cinnabar expression correlates with the forewing band, but the expression pattern of vermillion differs significantly between the mimics. This demonstrates that both shared and divergent expression patterns are associated with mimetic phenotypes between Heliconius species. Two genes not studied in H. erato, scarlet and possibly kf, also show enhanced expression in the forewing band of H. melpomene, implying co-ordinated upregulation of several members of this biosynthetic pathway during pattern formation.

Functional neurons and melanocytes induced from immortal lines of postnatal neural crest‐like stem cells

Stem cells, that is, cells that can both reproduce themselves and differentiate into functional cell types, attract much interest as potential aids to healing and disease therapy. Embryonic neural crest is pluripotent and generates the peripheral nervous system, melanocytes, and some connective tissues. Neural-crest-related stem cells have been reported previously in postnatal skin: committed melanocytic stem cells in the hair follicle, and pluripotent cell types from the hair follicle and papilla that can produce various sets of lineages. Here we describe novel pluripotent neural crest-like stem cells from neonatal mouse epidermis, with different potencies, isolated as 3 independent immortal lines. Using alternative regulatory factors, they could be converted to large numbers of either Schwann precursor cells, pigmented melanocytes, chondrocytes, or functional sensory neurons showing voltage-gated sodium channels. Some of the neurons displayed abundant active TRPV1 and TRPA1 receptors. Such functional neurons have previously been obtained in culture only with difficulty, by explantation. The system was also used to generate comparative gene expression data for the stem cells, melanocytes, and melanoblasts that sufficiently explain the lack of pigment in melanoblasts and provide a rationale for some genes expressed apparently ectopically in melanomas, such as ephrin receptors.—Sviderskaya, E. V., Easty, D. J., Lawrence, M. A., Sánchez, D. P., Negulyaev, Y. A., Patel, R. H., Anand, P., Korchev, Y. E., Bennett, D. C. Functional neurons and melanocytes induced from immortal lines of postnatal neural crest-like stem cells.

ETS2 Regulating Neurodegenerative Signaling Pathway of Human Neuronal (SH-SY5Y) Cells Exposed to Single and Repeated Low-Dose Sarin (GB)

The mechanistic understanding of low-level sarin-induced neurotoxicity after single or repeated doses has yet to be explored at a cellular level. Using the microarray (Affymetrix-GeneChips) transcription profiling approach, the present study examined gene expression in human SH-SY5Y cells exposed to single (3 and 24 h) or repeated (2 x 24 h) doses of sarin (5 microg/mL) to delineate the possible mechanism. Two hundred twenty-four genes whose expression was significantly (P < 0.01) altered by at least 3-fold were selected by GeneSpringGX analysis. The comparative gene expression data confirmed the transcriptional changes to be related to dose and exposure time of sarin. The effect of a single noncytotoxic sarin dose on gene transcription was variable, whereas repeated doses over 48 h persistently down-regulated genes linked to neurodegenerative mechanisms. Thirty persistently altered genes were validated using real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Similar qRT-PCR profiles obtained in sarin-treated SH-SY5Y and HCN-1A cells confirmed the cell-independent alterations in expression levels. Genes (ETS2, APOE, PSEN1, DDC, and CD9) implicated mainly in the regulation of sarin-induced neuropathogenesis were further confirmed by Western blot and double-immunofluorescence assays. The regulome pathway suggests a new feasible mechanism by which sarin increases ETS2 expression and takes control over other genes involved in the neurodegenerative pathway. The overall data delineate an in vitro experimental model suitable for studying the neuropathology of cells and may provide novel insights into therapeutic interventions.

Gene expression microarray profiles of cumulus cells in lean and overweight-obese polycystic ovary syndrome patients

The aim of this work was to study gene expression patterns of cultured cumulus cells from lean and overweight-obese polycystic ovary syndrome (PCOS) patients using genome-wide oligonucleotide microarray. The study included 25 patients undergoing in vitro fertilization and intra-cytoplasmic sperm injection: 12 diagnosed with PCOS and 13 matching controls. Each of the groups was subdivided into lean (body mass index (BMI) < 24) and overweight (BMI > 27) subgroups. The following comparisons of gene expression data were made: lean PCOS versus lean controls, lean PCOS versus overweight PCOS, all PCOS versus all controls, overweight PCOS versus overweight controls, overweight controls versus lean controls and all overweight versus all lean. The largest number of differentially expressed genes (DEGs), with fold change (FC) |FC| >or= 1.5 and P-value < 0.01, was found in the lean PCOS versus lean controls comparison (487) with most of these genes being down-regulated in PCOS. The second largest group of DEGs originated from the comparison of lean PCOS versus overweight PCOS (305). The other comparisons resulted in a much smaller number of DEGs (174, 109, 125 and 12, respectively). In the comparison of lean PCOS with lean controls, most DEGs were transcription factors and components of the extracellular matrix and two pathways, Wnt/beta-catenin and mitogen-activated protein kinase. When comparing overweight PCOS with overweight controls, most DEGs were of pathways related to insulin signaling, metabolism and energy production. The finding of unique gene expression patterns in cumulus cells from the two PCOS subtypes is in agreement with other studies that have found the two to be separate entities with potentially different pathophysiologies.

Loss of 13q is associated with genes involved in cell cycle and proliferation in dedifferentiated hepatocellular carcinoma

Dedifferentiation of hepatocellular carcinoma implies aggressive clinical behavior and is associated with an increasing number of genomic alterations, eg deletion of 13q. Genes directly or indirectly deregulated due to these genomic alterations are mainly unknown. Therefore this study compares array comparative genomic hybridization and whole genome gene expression data of 23 well, moderately, or poorly dedifferentiated hepatocellular carcinoma, using unsupervised hierarchical clustering. Dedifferentiated carcinoma clearly branched off from well and moderately differentiated carcinoma (P<0.001 χ2-test). Within the dedifferentiated group, 827 genes were upregulated and 33 genes were downregulated. Significance analysis of microarrays for hepatocellular carcinoma with and without deletion of 13q did not display deregulation of any gene located in the deleted region. However, 531 significantly upregulated genes were identified in these cases. A total of 6 genes (BIC, CPNE1, RBPMS, RFC4, RPSA, TOP2A) were among the 20 most significantly upregulated genes both in dedifferentiated carcinoma and in carcinoma with loss of 13q. These genes are involved in cell-cycle control and proliferation. Of 33 downregulated genes in the dedifferentiated subgroup, 4 metallothioneins had the lowest fold change, most probably mediated through inactivation of C/EBPα by the PI3K/AKT cascade. In conclusion dedifferentiation of hepatocellular carcinoma is associated with upregulation of genes involved in cell-cycle control and proliferation. Notably, a significant portion of these genes is also upregulated in carcinoma with deletion of 13q. As no downregulated genes were identified and microRNAs (mir-621, mir-16-1, mir-15a) are located within the deleted region of 13q and may be lost, we speculate that these miRNAs may induce the upregulation of critical cell-cycle control genes.

Gene Regulation in Primates Evolves under Tissue-Specific Selection Pressures

Regulatory changes have long been hypothesized to play an important role in primate evolution. To identify adaptive regulatory changes in humans, we performed a genome-wide survey for genes in which regulation has likely evolved under natural selection. To do so, we used a multi-species microarray to measure gene expression levels in livers, kidneys, and hearts from six humans, chimpanzees, and rhesus macaques. This comparative gene expression data allowed us to identify a large number of genes, as well as specific pathways, whose inter-species expression profiles are consistent with the action of stabilizing or directional selection on gene regulation. Among the latter set, we found an enrichment of genes involved in metabolic pathways, consistent with the hypothesis that shifts in diet underlie many regulatory adaptations in humans. In addition, we found evidence for tissue-specific selection pressures, as well as lower rates of protein evolution for genes in which regulation evolves under natural selection. These observations are consistent with the notion that adaptive circumscribed changes in gene regulation have fewer deleterious pleiotropic effects compared with changes at the protein sequence level.

Genomic Complexity and Recurrent Aberration in Multiple Myeloma: Analysis of a Compendium of aCGH and Gene Expression Profiles.

Multiple Myeloma (MM) is the second most prevalent haematological disorder in the US with great recent progress propelled by various technological and therapeutic advances. Nevertheless, the complexity of MM genomes remains inadequately characterized. We have combined high-resolution (44K Agilent) array comparative genomic hybridization (aCGH) and gene expression data with clinical outcomes in an initial attempt at indexing genomic complexity in MM and its clinical implication in 100 MM patients. We enumerated the Number of Aberrations per Tumor (NAPT) as defined by the ADM-1 algorithm available within CGH Analytics. There appear to be no difference in degree of genetic complexity between hyperdiploid and non-hyperdiploid myeloma. Generally, t(11;14) have low NAPT whereas D2 tumors have high NAPT. Amongst the high-risk genetic subtypes, tumors with maf translocations have relatively low NAPT whereas t(4;14) have high NAPT. Whilst a Multivariate Cox Proportional Hazards regression of survival outcome showed little statistical support for popular indicators such as ploidy and TC classification, results for NAPT were considerably more encouraging (p~ 0.07, median survival of 40 months in low complexity vs 18 months in high). Log-rank tests further supported prognosis based on NAPT independent of clinical status and ploidy. To characterize complexity, we clustered aCGH profiles by clinical status, ploidy and TC classification. Clear patterns of aggregation and recurrent aberration were observed suggesting that they were possibly instrument to aberrant gene expression. Indeed, expression of a large proportion of genes approximately 2Mb of the recurrent breakpoints varied significantly between patients carrying aberrations vis-a-viz others that did not. Comparison against known gene sets showed an enrichment for cell-cycle and apoptosis genes. We are presently characterizing several such breakpoint-associated genes for their functional significance.

Comparison of gene expression data from human and mouse breast cancers: Identification of a conserved breast tumor gene set

The aim of our work was to establish a database for breast cancer gene expression data in order to compare human and mouse breast cancer. We identified human and mouse homologues genes and compared the expression profile of 24 human breast tumors with 6 WAP-SVT/t breast tumors (WAP-SVT/t animals, line 8). Our studies confirmed the heterogeneity in gene expression of human as well as mouse breast cancer cells. However, 63 genes were found to be differentially expressed (upregulated: 40; downregulated: 23 genes) in at least 75% of the breast tumors of both species. To differentiate between early and late events in tumor formation, we compared the 63 differentially expressed genes with a mouse data set obtained from hyperplastic mammary glands. This revealed that the majority of the early deregulated genes are cell proliferation specific. These early changes seem to be necessary although not sufficient for breast cancer formation. Late alterations concern mainly genes belonging to the category of cell communication and metabolism. Interestingly, most of the 63 conserved genes are commonly associated with tumorigenesis.

Expression stability of commonly used reference genes in canine articular connective tissues

BackgroundThe quantification of gene expression in tissue samples requires the use of reference genes to normalise transcript numbers between different samples. Reference gene stability may vary between different tissues, and between the same tissue in different disease states. We evaluated the stability of 9 reference genes commonly used in human gene expression studies. Real-time reverse transcription PCR and a mathematical algorithm were used to establish which reference genes were most stably expressed in normal and diseased canine articular tissues and two canine cell lines stimulated with lipolysaccaride (LPS).ResultsThe optimal reference genes for comparing gene expression data between normal and diseased infrapatella fat pad were RPL13A and YWHAZ (M = 0.56). The ideal reference genes for comparing normal and osteoarthritic (OA) cartilage were RPL13A and SDHA (M = 0.57). The best reference genes for comparing normal and ruptured canine cranial cruciate ligament were B2M and TBP (M = 0.59). The best reference genes for normalising gene expression data from normal and LPS stimulated cell lines were SDHA and YWHAZ (K6) or SDHA and HMBS (DH82), which had expression stability (M) values of 0.05 (K6) and 0.07 (DH82) respectively. The number of reference genes required to reduce pairwise variation (V) to <0.20 was 4 for cell lines, 5 for cartilage, 7 for cranial cruciate ligament and 8 for fat tissue. Reference gene stability was not related to the level of gene expression.ConclusionThe reference genes demonstrating the most stable expression within each different canine articular tissue were identified, but no single reference gene was identified as having stable expression in all different tissue types. This study underlines the necessity to select reference genes on the basis of tissue and disease specific expression profile evaluation and highlights the requirement for the identification of new reference genes with greater expression stability for use in canine articular tissue gene expression studies.

OPTIMIZATION OF AN ANIMAL TEST PROTOCOL FOR TOXICOGENOMICS STUDIES (I); REQUIREMENT STUDY OF A PROTOCOL

Toxicogenomics is a promising new tool for prediction of chemical toxicities including carcinogenicity in a relatively short period. However, it is important to develop a reliable animal test protocol for toxicogenomics studies. The preparation of RNA and tissues is also crucial, since it greatly influences outcomes of gene expression analysis. In the present study, we examined an animal test protocol by comparing gene expression data from different conditions and proposed a reliable animal test protocol for toxicogenomic studies. With regard to the preparation of tissues and RNA, here we present evidence that quality of RNA and tissues is well-preserved even after freezer storage for up to 2.5 years. Gene expression levels were compared using a GeneChip System (RGU34A, Affymetrix, Santa Clara, CA, USA) between RNA samples that were freshly prepared, stored at -80 degrees C or re-prepared from tissue kept at -20 degrees C. None showed degradation and no significant differences in expression were evident among the three sets of samples. The data demonstrate that gene expression analysis by DNA microarray is suitable for RNA or tissues that have been stored at an appropriate temperature.

The Role of Developmental Genetics in Understanding Homology and Morphological Evolution in Plants

Homology assessments are critical to comparative biological studies. Although gene expression data have been proposed as instrumental for defining homologous relationships, several lines of evidence suggest that this type of data can be misleading if used in isolation. The correspondence between the homology of genes and that of structures is not simple, and conclusions can be derived only after careful examination of all available data. For instance, the MADS-box gene family is one of the best-studied families of transcription factors, and it provides several examples of dissociation between genetic and morphological homology. In this regard, we examine the role of APETALA3 and PISTILLATA homologs in the development of petaloid organs, a feature thought to have originated multiple times. We also consider the role of members of the AGAMOUS subfamily in the development of the pistil, a character that originated only once. Additionally, we discuss how serial homology makes gene cooption a very common phenomenon in plants. In spite of the multiple cases of this type of dissociation, comparative developmental genetics can yield other types of information that help assess homologies. Furthermore, comparative gene expression studies provide useful data for dissecting the origin of morphological innovations and are, therefore, key to understanding character evolution. Finally, we provide some guidelines for the critical examination of comparative gene expression data in the context of studying morphological innovations.