Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Pancreatic Cancer 1

ABSTRACT: This is the experiment set used for a paper written in collaboration with Hopkins. It compares genes that are differentially expressed between normal pancreas, pancreatic cell lines and pancreatic adenocarcinoma. Pancreatic cancer is the fifth leading cause of cancer death in the United States. We used cDNA microarrays to analyze global gene expression patterns in 14 pancreatic cancer cell lines, 17 resected infiltrating pancreatic cancer tissues, and 5 samples of normal pancreas to identify genes that are differentially expressed in pancreatic cancer. We found more than 400 cDNAs corresponding to genes that were differentially expressed in the pancreatic cancer tissues and cell lines as compared to normal pancreas. These genes that tended to be expressed at higher levels in pancreatic cancers were associated with a variety of processes, including cell-cell and cell-matrix interactions, cytoskeletal remodeling, proteolytic activity, and Ca(++) homeostasis. Two prominent clusters of genes were related to the high rates of cellular proliferation in pancreatic cancer cell lines and the host desmoplastic response in the resected pancreatic cancer tissues. Of 149 genes identified as more highly expressed in the pancreatic cancers compared with normal pancreas, 103 genes have not been previously reported in association with pancreatic cancer. The expression patterns of 14 of these highly expressed genes were validated by either immunohistochemistry or reverse transcriptase-polymerase chain reaction as being expressed in pancreatic cancer. The overexpression of one gene in particular, 14-3-3 sigma, was found to be associated with aberrant hypomethylation in the majority of pancreatic cancers analyzed. The genes and expressed sequence tags presented in this study provide clues to the pathobiology of pancreatic cancer and implicate a large number of potentially new molecular markers for the detection and treatment of pancreatic cancer. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Using regression correlation

ORGANISM(S): Homo sapiens

SUBMITTER: Mari Olsen

PROVIDER: E-GEOD-3654 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Exploration of global gene expression patterns in pancreatic adenocarcinoma using cDNA microarrays.

Iacobuzio-Donahue Christine A CA Maitra Anirban A Olsen Mari M Lowe Anson W AW van Heek N Tjarda NT Rosty Christophe C Walter Kim K Sato Norihiro N Parker Antony A Ashfaq Raheela R Jaffee Elizabeth E Ryu Byungwoo B Jones Jessa J Eshleman James R JR Yeo Charles J CJ Cameron John L JL Kern Scott E SE Hruban Ralph H RH Brown Patrick O PO Goggins Michael M

The American journal of pathology 20030401 4

Pancreatic cancer is the fifth leading cause of cancer death in the United States. We used cDNA microarrays to analyze global gene expression patterns in 14 pancreatic cancer cell lines, 17 resected infiltrating pancreatic cancer tissues, and 5 samples of normal pancreas to identify genes that are differentially expressed in pancreatic cancer. We found more than 400 cDNAs corresponding to genes that were differentially expressed in the pancreatic cancer tissues and cell lines as compared to norm ...[more]

PMID: 12651607

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Project description:Summary: Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes (luminal A, luminal B, ERBB2-associated, basal-like and normal-like) with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes. HEEBO oligonucleotide microarrays from the Stanford Functional Genomics Facility were used to perform gene expression profiling of 50 human breast epithelial cell lines, in comparison to a universal RNA reference. Expression data were analyzed by hierarchical clustering to identify subgroups, and gene set enrichment analysis to identify subgroup-specific gene pathways.

Project description:The first goal of the study was to find the genes that explain the difference in progression of age-related retinal degeneration (ageRD) between the inbred strains C57BL/6J-c2J (B6a) and BALB/cByJ (C). The specific goal was to find the candidate genes that explain the chromosome 6 and chromosome 10 quantitative trait loci (QTL) found in a previous study. Genes differentially expressed in retina between both strains and that map to the QTL are candidate genes. By integrating different approaches: microarray study, knowledge-based candidate gene search and screening of genetic variants, we found 35 candidate genes for chromosome 6 QTL and 14 candidate genes for chromosome 10 QTL. Five genes for each QTL were selected for sequencing and qPCR analysis. One gene, Tnfaip3 was selected for phenotypic testing and was excluded as the quantitative trait gene for chr10 QTL. The second goal of the study was to find biological processes and pathways associated with ageRD by Gene Ontology analysis of the microarray data. We concentrated on GO terms overrepresented in either strain at 8 months; the age when there is a difference in the phenotype (outer nuclear layer thickness). The GO analysis revealed that transcripts associated with inflammation, mitochondrial envelope, DNA repairing and oxidative stress were increased in the ageRD sensitive C strain with age (8 months). In the ageRD resistant B6a strain transcripts associated with antioxidant response, regulation of blood vessel size and growth factor activity were increased with age. Transcripts associated with cell remodeling and lipid metabolism were increased in either strain with age. This study aims to identify gene expression differences in posterior eyecups between the strains C and B6a at 4 months and at 8 months. Twelve animals were used per strain and time point for a total of 48 mice. Total RNA for 3 animals (6 eyes) were pooled giving a total of 4 biological replicates per strain and time point. The 4-month C samples labeled with Cy5 were hybridized with the 4-month B6a samples labeled with Cy3 (4 biological replicates); the 8-month C samples labeled with Cy5 were hybridized with the 8-month B6a samples labeled with Cy3, for 8 arrays (4 biological replicates). A second set of eight arrays were used to analyzed the same RNA samples but with the dye orientation reversed, yielding a total of 16 arrays in the experiment. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc.

Dataset Information

Pancreatic Cancer 1

Publications

Exploration of global gene expression patterns in pancreatic adenocarcinoma using cDNA microarrays.

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