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Differential gene expression in pituitary adenomas by oligonucleotide array analysis

ABSTRACT: This series includes the four major subtypes of pituitary adenomas and normal post-mortem pituitary tissue Data Transformation Using Affymetrix Microarray Suite 5.0 global scaling was applied to the quantification data to adjust the average recorded to a target intensity of 100. Data were then exported into the bioinformatics software GeneSpring 6.0 (Silicon Genetics, Redwood City, CA) for further analysis. Data normalization was performed to scale the data so that the average intensity value on each array was 1 by dividing each expression value by the median of the expression levels on each chip. The individual gene expression levels for each of the 4 pituitary adenoma subtype arrays was divided by the expression level in the normal pituitary array. Thus, the data are presented as relative to the expression in normal pituitary tissue. Filtering was then performed to identify genes over-expressed or under-expressed at least 2.0 fold in tumours compared to normal pituitary. TABLE 1: The genes / ESTs differentially overexpressed >= 2-fold in at least one pituitary adenoma subtype compared to normal pituitary. Negative values represent underexpression. Where genes are represented by more than one probe set, individual probe data sets are given. TABLE 2: The genes / ESTs differentially underexpressed >= 2-fold in at least one pituitary adenoma subtype compared to normal pituitary. Negative values represent underexpression. Where genes are represented by more than one probe set, individual probe data sets are given. Keywords = pituitary tumor Keywords: other

ORGANISM(S): Homo sapiens

PROVIDER: GSE2175 | GEO | 2005/05/23

SECONDARY ACCESSION(S): PRJNA91221

REPOSITORIES: GEO

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Project description:Background. Most colorectal cancers (CRC) arise in a progression through adenoma to carcinoma phenotypes as a consequence of altered genetic information. Clinical progression of CRC may occur in parallel with distinctive signaling alterations. We designed multidirectional analyses integrating microarray-based data with biostatistics and bioinformatics to elucidate the signaling and metabolic alterations underlying CRC development in the adenoma-carcinoma sequence. Methodology/Principal Findings. Studies were performed on normal mucosa, adenoma, and CRC samples obtained during surgery or colonoscopy. Collections of cryostat sections prepared from the tissue samples were evaluated by a pathologist to control the relative cell type content. RNA was isolated from 105 macro- and 40 microdissected specimens. The measurements were done using Affymetrix GeneChip HG-U133plus2, and probe set data were generated using two normalization algorithms: MAS5 and GCRMA with LVS. The data were evaluated using pair-wise comparisons and data decomposition into SVD modes. The method selected for the functional analysis used the Kolmogorov-Smirnov test. Based on a consensus of the results obtained by two tissue handling procedures, two normalization algorithms, and two probe set sorting criteria, we identified six KEGG signaling and metabolic pathways (cell cycle, DNA replication, p53 signaling pathway, purine metabolism, pyrimidine metabolism, and RNA polymerase) that are significantly altered in both macro- and microdissected tumor samples compared to normal colon. On the other hand, pathways altered between benign and malignant tumors were identified only in the macrodissected tissues. Conclusion/Significance. Multidirectional analyses of microarray data allow the identification of essential signaling alterations underlying CRC development. Although the proposed strategy is computationally complex and labor–intensive, it may reduce the number of false results. Gene expression profiles of 40 tissue samples representing distant full-thickness normal colon, normal colon mucosa dissected from tumor, adenoma, and carcinoma. Gene expression profiles of 105 tissue samples representing colon carcinomas, adenocarcinomas, and normal colon samples.

Project description:Pituitary adenomas cause significant endocrine and mass-related morbidity. Not much is known about mechanisms underlying pituitary tumor pathogenesis.We searched for a side population (SP) in pituitary tumor, representing cells with high efflux capacity and potentially enriching for cancer/tumor stem cells (CSC/TSC). Human pituitary adenomas contain a SP irrespective of hormonal phenotype. This adenoma SP, as well as the further purified SP (pSP) depleted from endothelial and immune cells, enriches for cells that express ‘tumor stemness’ markers and signaling pathways, including epithelial-mesenchymal transition (EMT)-linked factors. The adenomas were found to contain self-renewing sphere-forming cells, considered a property of TSC. The sphere-initiating cells were retrieved in the pSP.Because benign pituitary adenomas do not grow in vitro and failed to expand in immunodeficient mice, the pituitary tumor cell line AtT20 was further used. We identified a SP in this cell line and found it more tumorigenic than the main population (MP). Of the two EMT-regulatory pathways tested, inhibition of Cxcr4 signaling reduced EMT-linked cell motility in vitro as well as xenograft tumor growth, whereas activation of TGFβ had no effect.The tumor pSP showed upregulated expression of the pituitary stem cell marker SOX2. Pituitaries from dopamine receptor D2 knockout (Drd2-/-) mice bearing prolactinomas, contain more pSP, Sox2+ and colony-forming cells than wildtype glands.In conclusion, we detected a SP in pituitary tumors and identified TSC-associated characteristics. Our study may contribute to a better understanding of pituitary tumor pathogenesis and lead to new therapeutic targets. We determined gene expression profiles for 9 human pituitary adenoma samples (5 x NF-A; 4 x GH-A). The samples were obtained immediately after transsphenoidal resection (by the neurosurgeon Dr. van Loon, Division Neurosurgery, University Hospitals Leuven). Informed consent was received from the patients. Hormonal phenotype was determined by the Department of Imaging and Pathology (University Hospitals Leuven). For each sample, total SP and MP cells were sorted by FACS. Separate assays were run subsequently for the two fractions. As such we present data from 18 microarrays.

Project description:Pituitary adenomas cause significant endocrine and mass-related morbidity. Not much is known about mechanisms underlying pituitary tumor pathogenesis. We searched for a side population (SP) in pituitary tumor, representing cells with high efflux capacity and potentially enriching for cancer/tumor stem cells (CSC/TSC). Human pituitary adenomas contain a SP irrespective of hormonal phenotype. This adenoma SP, as well as the further purified SP (pSP) depleted from endothelial and immune cells, enriches for cells that express ‘tumor stemness’ markers and signaling pathways, including epithelial-mesenchymal transition (EMT)-linked factors. The adenomas were found to contain self-renewing sphere-forming cells, considered a property of TSC. The sphere-initiating cells were retrieved in the pSP. Because benign pituitary adenomas do not grow in vitro and failed to expand in immunodeficient mice, the pituitary tumor cell line AtT20 was further used. We identified a SP in this cell line and found it more tumorigenic than the main population (MP). Of the two EMT-regulatory pathways tested, inhibition of Cxcr4 signaling reduced EMT-linked cell motility in vitro as well as xenograft tumor growth, whereas activation of TGFβ had no effect. The tumor pSP showed upregulated expression of the pituitary stem cell marker SOX2. Pituitaries from dopamine receptor D2 knockout (Drd2-/-) mice bearing prolactinomas, contain more pSP, Sox2+ and colony-forming cells than wildtype glands. In conclusion, we detected a SP in pituitary tumors and identified TSC-associated characteristics. Our study may contribute to a better understanding of pituitary tumor pathogenesis and lead to new therapeutic targets. We determined gene expression profiles for 5 human pituitary adenoma samples (all NF-A type). The samples were obtained immediately after transsphenoidal resection (by the neurosurgeon Dr. van Loon, Division Neurosurgery, University Hospitals Leuven). Informed consent was received from the patients. Hormonal phenotype was determined by the Department of Imaging and Pathology (University Hospitals Leuven). For each sample, CD31¯/CD45¯ SP (purified SP or pSP) and pMP cells were sorted by FACS. Separate assays were run subsequently for the two fractions. As such we present data from 10 microarrays.

Project description:Transcriptional Profiling of the Transition from Normal Intestine to Adenoma in the APC(Min/+) Mouse. Tissue was from male 91-days old APC(Min/+) mouse (an animal model for human colon cancer). RNA was purified using Trizol and labeled for hybridization to high density oligonucleotide Affymetrix MG_U74Av2 arrays, using manufacturer protocol. We measured the relative expression level of >12000 genes and ESTs. ----------------------------------------- Samples used in analysis: * GSM12501: Normal intestine diet #1 sample C1_0112 Dnmt+/- Min/+ * GSM12502: Tumor diet #1 sample T1_0112 Dnmt+/- Min/+ * GSM12503: Normal intestine diet #1 sample C2_0112 Dnmt+/+ Min/+ * GSM12504: Tumor diet #1 sample T2_0112 Dnmt+/+ Min/+ * GSM12505: Normal intestine diet #2 sample C1_003 Dnmt+/- Min/+ * GSM12506: Tumor diet #2 sample T1_003 Dnmt+/- Min/+ * GSM12507: Normal intestine diet #2 sample C2_003 Dnmt+/+ Min/+ * GSM12508: Tumor diet #2 sample T2_003 Dnmt+/+ Min/+ * GSM12509: Normal intestine diet #3 sample C1_005 Dnmt+/- Min/+ * GSM12510: Tumor diet #3 sample T1_005 Dnmt+/- Min/+ * GSM12511: Normal intestine diet #3 sample C2_005 Dnmt+/+ Min/+ * GSM12512: Tumor diet #3 sample T2_005 Dnmt+/+ Min/+ - - - - - - - - - - - - - - - - - - - - - Comparisons were performed as described in Chen Z, Ge B, Hudson TJ and Rozen R. Gene Expression Patterns 1, 89-93, 2002. Comparing Normal intestine vs Adenoma. - - - - - - - - - - - - - - - - - - - - - This resulted in the identification of differentially expressed transcripts. Identified transcripts were clustered based on functional information which was publicly available at time of analysis, obtained through the NetAffx WEB portal (www.Affymetrix.com) and literature. Keywords = Mouse Keywords = Min Keywords = normal Keywords = intestine Keywords = tumor Keywords = tumour Keywords = colon cancer Keywords = gene expression Keywords = beta-catenin Keywords = high density oligonucleotide microarrays Keywords = familial adenomatous polyposis Keywords = FAP Keywords = colorectal cancer Keywords = Affymetrix MGU74Av2 GeneChip probe array Keywords = mouse model Keywords = APC Keywords = adenomatous polyposis coli Keywords: ordered

Project description:This series represent several subgroups of experiments designed to investigate the role of basal immunoglobulin signaling in immature B cell development. The first subgroup of arrays (Ctrl Mhi, Cre Mhi, Cre Mlo) was done to identify the changes in gene expression in immature B cells as a consequence of inducible deletion of surface IgM expression via Cre-LoxP mediated excision of Ig heavy chain. The second subgroup of arrays (GFPneg, GFPpos, FxE Ctrl, FxE HA) was done to identify the changes in gene expression in immature B cells as a consequence of blockade of tyrosine kinase signaling with herbimycin A treatment. The third subgroup of arrays (FxD, FxE, B6 Mneg, HEL Mhi) was done to establish gene expression profiles of immature B, pre B and pro B cells as reference platforms for the other two subgroups. (Tze etal. Public Library of Science Biology, 2005) The appended supplementary tables are described as follows: TABLE 1: Transformed array signal intensities used for statistical analysis. Listed are all probe sets excluding masked probe sets and Affymetrix hybridization control probe sets. Results are based on the following definitions: - Values with detection p values <0.1 were considered present. - Signal intensities with detection = "A" or with values < 20 were set to "20". TABLE 2: Genes differentially expressed between Ctrl Mhi and Cre Mlo cell populations and associated signal values. Results are based on the following definitions: - 2-fold or greater difference in means - difference in mean expression values > 200 - P < 0.01 (by Student's T test) TABLE 3: Probesets used for clustering in Figures 2 and 3 of publication TABLE 4: Probesets used for clustering in Figure 7 of publication TABLE 5: Correlation coefficients between all cell populations. Correlation coefficients were calculated as an additional method to demonstrate the relationship of the various cell populations to each other. Shown are the correlation coefficients generated using the mean expression values for each of the 101 transcripts from Figure 7 of publication. Keywords = bone marrow B cells

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Differential gene expression in pituitary adenomas by oligonucleotide array analysis

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