Comprehensive copy number and gene expression profiling of the 17q23 amplicon in human breast cancer

The biological significance of DNA amplification in cancer is thought to be due to the selection of increased expression of a single or few important genes. However, systematic surveys of the copy number and expression of all genes within an amplified region of the genome have not been performed. Here we have used a combination of molecular, genomic, and microarray technologies to identify target genes for 17q23, a common region of amplification in breast cancers with poor prognosis. Construction of a 4-Mb genomic contig made it possible to define two common regions of amplification in breast cancer cell lines. Analysis of 184 primary breast tumors by fluorescence in situ hybridization on tissue microarrays validated these results with the highest amplification frequency (12.5%) observed for the distal region. Based on GeneMap'99 information, 17 known genes and 26 expressed sequence tags were localized to the contig. Analysis of genomic sequence identified 77 additional transcripts. A comprehensive analysis of expression levels of these transcripts in six breast cancer cell lines was carried out by using complementary DNA microarrays. The expression patterns varied from one cell line to another, and several overexpressed genes were identified. Of these, RPS6KB1, MUL, APPBP2, and TRAP240 as well as one uncharacterized expressed sequence tag were located in the two common amplified regions. In summary, comprehensive analysis of the 17q23 amplicon revealed a limited number of highly expressed genes that may contribute to the more aggressive clinical course observed in breast cancer patients with 17q23-amplified tumors.

Expression profiling and sequence diversity of novel DREB genes from common bean (Phaseolus vulgaris L.) and their association with drought-related traits

Common bean is a major dietary component in several countries, but its productivity is negatively affected by abiotic stresses. Dissecting candidate genes involved in abiotic stress tolerance is a paramount step toward the improvement of common bean performance under such constraints. Thereby, this thesis presents a systematic analysis of the DEHYDRATION RESPONSIVE ELEMENT-BINDING (DREB) gene subfamily, which encompasses genes that regulate several processes during stress responses, but with limited information for common bean. First, a series of in silico analyses with sequences retrieved from the P. vulgaris genome on Phytozome supported the categorization of 54 putative PvDREB genes distributed within six phylogenetic subgroups (A-1 to A-6), along the 11 chromosomes. Second, we cloned four novel PvDREB genes and determined their inducibility-factors, including the dehydration-, salinity- and cold-inducible genes PvDREB1F and PvDREB5A, and the dehydration- and cold-inducible genes PvDREB2A and PvDREB6B. Afterwards, nucleotide polymorphisms were searched through Sanger sequencing along those genes, revealing a high number of single nucleotide polymorphisms within PvDREB6B by the comparison of Mesoamerican and Andean genotypes. The nomenclature of PvDREB6B is discussed in details. Furthermore, we used the BARCBean6K_3 SNP platform to identify and genotype the closest SNP to each one of the 54 PvDREB genes. We selected PvDREB6B for a broader study encompassing a collection of wild common bean accessions of Mesoamerican origin. The population structure of the wild beans was accessed using sequence polymorphisms of PvDREB6B. The genetic clusters were partially associated with variation in latitude, altitude, precipitation and temperature throughout the areas such beans are distributed. With an emphasis on drought stress, an adapted tube-screening method in greenhouse conditions enabled the phenotyping of several drought-related traits in the wild collection. Interestingly, our data revealed a correlation between root depth, plant height and biomass and the environmental data of the location of the accessions. Correlation was also observed between the population structure determined through PvDREB6B and the environmental data. An association study combining data from the SNP array and DREB polymorphisms enabled the detection of SNP associated with drought-related traits through a compressed mixed linear model (CMLM) analysis. This thesis highlighted important features of DREB genes in common bean, revealing candidates for further strategies aimed at improvement of abiotic stress tolerance, with emphasis on drought tolerance

Systematic expression profiling of the mouse transcriptome using RIKEN cDNA mircoarrays

The number of known mRNA transcripts in the mouse has been greatly expanded by the RIKEN Mouse Gene Encyclopedia project. Validation of their reproducible expression in a tissue is an important contribution to the study of functional genomics. In this report, we determine the expression profile of 57,931 clones on 20 mouse tissues using cDNA microarrays. Of these 57,931 clones, 22,928 clones correspond to the FANTOM2 clone set. The set represents 20,234 transcriptional units (TUs) out of 33,409 TUs in the FANTOM2 set. We identified 7206 separate clones that satisfied stringent criteria for tissue-specific expression. Gene Ontology terms were assigned for these 7206 clones, and the proportion of 'molecular function' ontology for each tissue-specific clone was examined. These data will provide insights into the function of each tissue. Tissue-specific gene expression profiles obtained using our cDNA microarrays were also compared with the data extracted from the GNF Expression Atlas based on Affymetrix microarrays. One major outcome of the RIKEN transcriptome analysis is the identification of numerous nonprotein-coding mRNAs. The expression profile was also used to obtain evidence of expression for putative noncoding RNAs. In addition, 1926 clones (70%) of 2768 clones that were categorized as unknown EST, and 1969 (58%) clones of 3388 clones that were categorized as unclassifiable were also shown to be reproducibly expressed.

Microarray expression profiling in melanoma reveals a BRAF mutation signature

We have used microarray gene expression pro. ling and machine learning to predict the presence of BRAF mutations in a panel of 61 melanoma cell lines. The BRAF gene was found to be mutated in 42 samples (69%) and intragenic mutations of the NRAS gene were detected in seven samples (11%). No cell line carried mutations of both genes. Using support vector machines, we have built a classifier that differentiates between melanoma cell lines based on BRAF mutation status. As few as 83 genes are able to discriminate between BRAF mutant and BRAF wild-type samples with clear separation observed using hierarchical clustering. Multidimensional scaling was used to visualize the relationship between a BRAF mutation signature and that of a generalized mitogen-activated protein kinase ( MAPK) activation ( either BRAF or NRAS mutation) in the context of the discriminating gene list. We observed that samples carrying NRAS mutations lie somewhere between those with or without BRAF mutations. These observations suggest that there are gene-specific mutation signals in addition to a common MAPK activation that result from the pleiotropic effects of either BRAF or NRAS on other signaling pathways, leading to measurably different transcriptional changes.

Gene-expression profiling reveals distinct expression patterns for classic versus variant Merkel cell phenotypes and new classifier genes to distinguish Merkel cell from small-cell lung carcinoma

Merkel cell carcinoma (MCC) is a rare aggressive skin tumor which shares histopathological and genetic features with small-cell lung carcinoma (SCLC), both are of neuroendocrine origin. Comparable to SCLC, MCC cell lines are classified into two different biochemical subgroups designated as 'Classic' and 'Variant'. With the aim to identify typical gene-expression signatures associated with these phenotypically different MCC cell lines subgroups and to search for differentially expressed genes between MCC and SCLC, we used cDNA arrays to pro. le 10 MCC cell lines and four SCLC cell lines. Using significance analysis of microarrays, we defined a set of 76 differentially expressed genes that allowed unequivocal identification of Classic and Variant MCC subgroups. We assume that the differential expression levels of some of these genes reflect, analogous to SCLC, the different biological and clinical properties of Classic and Variant MCC phenotypes. Therefore, they may serve as useful prognostic markers and potential targets for the development of new therapeutic interventions specific for each subgroup. Moreover, our analysis identified 17 powerful classifier genes capable of discriminating MCC from SCLC. Real-time quantitative RT-PCR analysis of these genes on 26 additional MCC and SCLC samples confirmed their diagnostic classification potential, opening opportunities for new investigations into these aggressive cancers.

Expression profiling in alcoholism research

This article represents the proceedings of a symposium at the 2004 International Society for Biomedical Research on Alcoholism in Mannheim, Germany, organized and co-chaired by Susan E. Bergeson and Wolfgang Sommer. The presentations and presenter were (1) Gene Expression in Brains of AlcoholPreferring and Non-Preferring Rats, by Howard J. Edenberg (2) Candidate Treatment Targets for Alcoholism: Leads from Functional Genomics Approaches, by Wolfgang Sommer (3) Microarray Analysis of Acute and Chronic Alcohol Response in Brain, by Susan E. Bergeson (4) On the Integration of QTL and Gene Expression Analysis, by Robert J. Hitzemann (5) Microarray and Proteomic Analysis of the Human Alcoholic Brain, by Peter R. Dodd.

Expression profiling correlates with treatment response in women with advanced serous epithelial ovarian cancer

The majority of epithelial ovarian carcinomas are of serous subtype, with most women presenting at an advanced stage. Approximately 70% respond to initial chemotherapy but eventually relapse. We aimed to find markers of treatment response that might be suitable for routine use, using the gene expression profile of tumor tissue. Thirty one women with histologically-confirmed late-stage serous ovarian cancer were classified into 3 groups based on response to treatment (nonresponders, responders with relapse less than 12 months and responders with no relapse within 12 months). Gene expression profiles of these specimens were analyzed with respect to treatment response and survival (minimum 36 months follow-up). Patients' clinical features did not correlate with prognosis, or with specific gene expression patterns of their tumors. However women who did not respond to treatment could be distinguished from those who responded with no relapse within 12 months based on 34 gene transcripts (p < 0.02). Poor prognosis was associated with high expression of inhibitor of differentiation-2 (ID2) (p = 0.001). High expression of decorin (DCN) and ID2 together was strongly associated with reduced survival (p = 0.003), with an estimated 7-fold increased risk of dying (95% CI 1.9-29.6; 14 months survival) compared with low expression (44 months). Immunohistochemical analysis revealed both nuclear and cytoplasmic distribution of ID2 in ovarian tumors. High percentage of nuclear staining vas associated with poor survival, although not statistically significantly. In conclusion, elevated expression of ID2 and DCN was significantly associated with poor prognosis in a homogeneous group of ovarian cancer patients for whom survival could not be predicted from clinical factors. (c) 2006 Wiley-Liss, Inc.

Expression profiling of purified mouse gonadal somatic cells during the critical time window of sex determination reveals novel candidate genes for human sexual dysgenesis syndromes

Despite the identification of SRY as the testis-determining gene in mammals, the genetic interactions controlling the earliest steps of male sex determination remain poorly understood. In particular, the molecular lesions underlying a high proportion of human XY gonadal dysgenesis, XX maleness and XX true hermaphroditism remain undiscovered. A number of screens have identified candidate genes whose expression is modulated during testis or ovary differentiation in mice, but these screens have used whole gonads, consisting of multiple cell types, or stages of gonadal development well beyond the time of sex determination. We describe here a novel reporter mouse line that expresses enhanced green fluorescent protein under the control of an Sf1 promoter fragment, marking Sertoli and granulosa cell precursors during the critical period of sex determination. These cells were purified from gonads of male and female transgenic embryos at 10.5 dpc (shortly after Sry transcription is activated) and 11.5 dpc (when Sox9 transcription begins), and their transcriptomes analysed using Affymetrix genome arrays. We identified 266 genes, including Dhh, Fgf9 and Ptgds, that were upregulated and 50 genes that were downregulated in 11.5 dpc male somatic gonad cells only, and 242 genes, including Fst, that were upregulated in 11.5 dpc female somatic gonad cells only. The majority of these genes are novel genes that lack identifiable homology, and several human orthologues were found to map to chromosomal loci implicated in disorders of sexual development. These genes represent an important resource with which to piece together the earliest steps of sex determination and gonad development, and provide new candidates for mutation searching in human sexual dysgenesis syndromes.

The human genome and gene expression profiling

The mapping and sequencing of the human genome has generated a large resource for answering questions about human disease. This achievement is akin in scientific importance to developing the periodic table of elements. Plastic surgery has always been at the frontier medical research. This resource will help us to improve our understanding on the many unknown physiological and pathogical conditions we deal with daily, such as wound heating keloid scar formation, Dupuytren's disease, rheumatoid arthritis, vascular malformation and carcinogenesis. We are primed in obtaining both disease and normal tissues to use this resource and applying it to clinical use. This review is about the human genome, the basis of gene expression profiling and how it will affect our clinical and research practices in the future and for those embarking on the use of this new technology as a research tool, we provide a brief insight on its limitations and pitfalls. (C) 2006 The British Association of Plastic Surgeons. Published by Elsevier Ltd. All rights reserved.

Molecular classification of cutaneous malignant melanoma by gene expression profiling

The most common human cancers are malignant neoplasms of the skin(1,2). Incidence of cutaneous melanoma is rising especially steeply, with minimal progress in non-surgical treatment of advanced disease(3,4). Despite significant effort to identify independent predictors of melanoma outcome, no accepted histopathological, molecular or immunohistochemical marker defines subsets of this neoplasm(2,3). Accordingly, though melanoma is thought to present with different 'taxonomic' forms, these are considered part of a continuous spectrum rather than discrete entities(2). Here we report the discovery of a subset of melanomas identified by mathematical analysis of gene expression in a series of samples. Remarkably, many genes underlying the classification of this subset are differentially regulated in invasive melanomas that form primitive tubular networks in vitro, a feature of some highly aggressive metastatic melanomas(5). Global transcript analysis can identify unrecognized subtypes of cutaneous melanoma and predict experimentally verifiable phenotypic characteristics that may be of importance to disease progression.

Retrotransposon expression profiling: Unveiling the hidden SINE transcriptome through Next-Generation Sequencing data analysis

Of the ~1.7 million SINE elements in the human genome, only a tiny number are estimated to be active in transcription by RNA polymerase (Pol) III. Tracing the individual loci from which SINE transcripts originate is complicated by their highly repetitive nature. By exploiting RNA-Seq datasets and unique SINE DNA sequences, we devised a bioinformatic pipeline allowing us to identify Pol III-dependent transcripts of individual SINE elements. When applied to ENCODE transcriptomes of seven human cell lines, this search strategy identified ~1300 Alu loci and ~1100 MIR loci corresponding to detectable transcripts, with ~120 and ~60 respectively Alu and MIR loci expressed in at least three cell lines. In vitro transcription of selected SINEs did not reflect their in vivo expression properties, and required the native 5’-flanking region in addition to internal promoter. We also identified a cluster of expressed AluYa5-derived transcription units, juxtaposed to snaR genes on chromosome 19, formed by a promoter-containing left monomer fused to an Alu-unrelated downstream moiety. Autonomous Pol III transcription was also revealed for SINEs nested within Pol II-transcribed genes raising the possibility of an underlying mechanism for Pol II gene regulation by SINE transcriptional units. Moreover the application of our bioinformatic pipeline to both RNA-seq data of cells subjected to an in vitro pro-oncogenic stimulus and of in vivo matched tumor and non-tumor samples allowed us to detect increased Alu RNA expression as well as the source loci of such deregulation. The ability to investigate SINE transcriptomes at single-locus resolution will facilitate both the identification of novel biologically relevant SINE RNAs and the assessment of SINE expression alteration under pathological conditions.

Expression profiling of type 2 diabetes susceptibility genes in the pancreatic islets, adipose tissue and liver of obese mice

Type 2 diabetes (T2D) is characterized by impaired beta cell function and insulin resistance. T2D susceptibility genes identified by Genome-wide association studies (GWAS) are likely to have roles in both impaired insulin secretion from the beta cell as well as insulin resistance. The aim of this study was to use gene expression profiling to assess the effect of the diabetic milieu on the expression of genes involved in both insulin secretion and insulin resistance. We measured the expression of 43 T2D susceptibility genes in the islets, adipose and liver of leptin-deficient Ob/Ob mice compared with Ob/+ littermates. The same panel of genes were also profiled in cultured rodent adipocytes, hepatocytes and beta cells in response to high glucose conditions, to distinguish expression effects due to elevated glycemia from those on the causal pathway to diabetes or induced by other factors in the diabetic microenviroment. We found widespread deregulation of these genes in tissues from Ob/Ob mice, with differential regulation of 23 genes in adipose, 18 genes in liver and one gene (Tcf7l2) in islets of diabetic animals (Ob/Ob) compared to control (Ob/+) animals. However, these expression changes were in most cases not noted in glucose-treated adipocyte, hepatocyte or beta cell lines, indicating that they may not be an effect of hyperglycemia alone. This study indicates that expression changes are apparent with diabetes in both the insulin producing beta cells, but also in peripheral tissues involved in insulin resistance. This suggests that incidence or progression of diabetic phenotypes in a mouse model of diabetes is driven by both secretory and peripheral defects. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart New York.

Gene expression profiling in hearts of transgenic mice overexpressing guanylyl cyclase domain of the GC-A receptor

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Gene expression profiling in hearts of transgenic mice overexpressing guanylyl cyclase domain of the GC-A receptor

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.