Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of human pituitary adenomas

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.

ORGANISM(S): Homo sapiens

SUBMITTER: Damian Morris

PROVIDER: E-GEOD-2175 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Differential gene expression in pituitary adenomas by oligonucleotide array analysis.

Morris Damian G DG Musat Mädälina M Czirják Sándor S Hanzély Zoltán Z Lillington Debra M DM Korbonits Márta M Grossman Ashley B AB

European journal of endocrinology 20050701 1

<h4>Objectives</h4>Microarray technology allows for the expression profile of many thousands of genes to be quantified at the same time, and has resulted in novel discoveries about the tumour biology of a number of cancers. We sought to do this in pituitary adenomas, the most common intracranial neoplasm.<h4>Methods</h4>Affymetrix GeneChip HG-U133A oligonucleotide arrays covering 14 500 well-characterised genes from the human genome were used to study pooled RNA for each of the four major pituit ...[more]

PMID: 15994756

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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.

Dataset Information

Transcription profiling of human pituitary adenomas

Publications

Differential gene expression in pituitary adenomas by oligonucleotide array analysis.

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